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+# 实验 S0：good/bad case 分裂的统一分解（margin vs differential residual）
+
+> **状态：** 已完成（2026-07-20；含 S0b 方向化修正与一轮 strict review 修复）
+>
+> 用户指令：核心要务是分析为什么部分 case 下 Frontier work、部分不 work 的 system 根因；本 card 是该诊断 campaign 的第一个 slice，仅使用 frozen artifacts，零 GPU 成本。人工 review 由用户的直接指令（"只有做好这个分析我们才能推进下一步"）满足。
+
+## Claim 与决策
+
+- **Parent claim：** ongoing.md H2——误差机制是 action-conditioned residual；本实验把它细化为"分裂从哪来"。
+- **现象（已冻结）：** 同一 best-effort Frontier 栈上，Q30/Q235 的 Trace-PD 与多数 PO 面 selection 近优，而 Fixed-PD 面 14–58% regret；失败 objective 随负载档切换（Q30 低压 TPOT/E2E 全反、高压 TTFT 56–58%）；A1 collective profile 修复了 Q235 Trace-PO p90 21.2%→0.3% 但对 Fixed-PD 33% 完全无效（本 card frozen-inputs/q235-ablation-a1）。
+- **Competing hypotheses：**
+  - **H-SCALE：** 分裂完全由「config-differential residual vs 真机 decision margin」的关系解释：good case 的 sim/real 比值跨 config 近似均匀（乘性偏移，argmin 不变），bad case 的比值跨 config 分散且超过 margin。workload shape 本身不需要出现在解释里。
+  - **H-THRESH：** 绝对 service-time 高估近似均匀，但与离散机制（MNS admission cap、MoE token-bucket、graph bucket）交互后被转换为 config-differential 误差；fixed uniform workload 把所有请求同步到同一 state 轨迹，使阈值交叉对整个 cell 相干生效；trace 的长度/到达异质性把阈值效应摊平。
+  - **H-STATE：** 失败由 simulator 闭环 batch state 分布漂移主导（Q235：sim decode batch 13.5 vs real 3.9 + B4→B5 profile cliff 正反馈）；即使打破 workload 同步性，闭环漂移仍可翻转排序。
+  - 三者关系：H-SCALE 是现象层（必要条件），H-THRESH/H-STATE 是 differential residual 的两种产生机制，可共存但可判别（见事前预测）。
+- **事前预测：**
+  - H-SCALE 成立 ⟺ 对每个 case×objective，failure 恰好发生在「top 邻域 log-ratio spread > log1p(真机相对 margin)」处（两侧同为 log-space 尺度），无反例。
+  - H-THRESH 独有：bad case 的 differential 误差集中于阈值语义分量（first-scheduling wait、bucket 跳变段），且 sim-only 反事实（去阈值/加 jitter）恢复排序——Q30 高压 TTFT 的 admission 反事实已支持一例。
+  - H-STATE 独有：差异化误差在去掉阈值分量后仍在 execution 项内（Q235 Fixed-PD 的 own-composition −20.07 vs exact-state +10.90 已支持一例）。
+- **判定规则：** S0 只裁决 H-SCALE 与「分量定位」（queue vs execution）；H-THRESH/H-STATE 的干预判别属 S1+（sim-only 反事实）与 GPU 实验（需另行 review）。若 H-SCALE 出现反例（good case 有 spread>margin 仍选对，或 bad case spread<margin），必须原样报告，不得平滑。
+
+## Setup
+
+- **输入（全部 frozen，runs/frontier-split-rootcause-v0/frozen-inputs/）：** q30-trace-pd（graph-piecewise comparison）、q30-fixed-hi（fixed-pd/fixed-po 高压面）、q30-expansion-lo（低压 fixed-pd/fixed-po/trace-po）、q235-fourcase-a0、q235-ablation-a1（+provenance）、q235-state-diag、q30-admission-diag。来源 cpfs 路径与 SHA 见各目录内 manifest/launch 记录。
+- **计算（每 case×objective）：** per-config 比值 r_c=sim_c/real_c；config-uniform scale=geomean(r_c)；differential residual=log-ratio spread（全 surface 与真机 top-3 邻域各一）；真机 relative margin（best 与 2nd-best、best 与 sim-winner 的真机值差）；failure flag=regret>5%；H-SCALE 检验=failure ⟺ 邻域 spread>log1p(margin)（review 修正：初版直接以 ln 差比较普通 relative margin，尺度不一致；修正后 70 行 verdict 不变）。
+- **分量定位：** q30-admission-diag 提供 TTFT=first-scheduling wait+prefill execution 分解；q235-state-diag 提供 own-composition vs exact-state contrast；把这些已知分量证据合并进统一表。
+- **交叉核对：** 重算的 regret 必须与各 frozen comparison.md 表一致（抽查 58.0%、33.0%、0.0%）；A0 vs A1 的 Q235 对比必须复现 trace-po p90 21.2%→0.3%、fixed-pd 四项不变。
+
+## 预期产物与 review
+
+- runs/frontier-split-rootcause-v0/analyze_split_decomposition.py（只读 frozen-inputs，确定性输出）
+- runs/frontier-split-rootcause-v0/results/decomposition.{json,md}：统一表，每行 case×objective，列出 winner、regret、scale、spread（全/邻域）、margin、H-SCALE verdict、已知分量归因
+- runs/frontier-split-rootcause-v0/results/margin-vs-residual.png：x=真机 margin，y=邻域 differential residual，点色=selection 对错；H-SCALE 成立则对错点被对角线分离
+- 人工验收：编排者亲自重跑脚本、抽查交叉核对数字、亲自查看渲染图
+
+## 复现信息
+
+- **Code：** AITuner branch feature/sim，自 HEAD 18c0b25 起；worker/reviewer job-id 见下方「Review 与 provenance 补记」；脚本与产物随本 card 同一 commit 入库（含 frozen-inputs 本地拷贝）。
+- **Environment：** 本地 workstation，CPU-only，python3+matplotlib；不访问远端。
+- **已知 deviation：** frozen-inputs 是 cpfs 原件的本地拷贝（scp，2026-07-20）；q30-expansion-lo 的低压 Fixed-PD 面已被高压面取代为 primary，本分析将两档并列为独立观测，不混合。
+
+## 结果
+
+- **观察事实：**
+  - 70 行（14 个 case surface）全部算出，无数据缺口；四组硬性交叉核对通过；连续运行产物 SHA 一致。
+  - **H-SCALE 判为必要非充分**：23 个 material failure（regret>5%）全部满足「top-3 邻域 log spread > log1p(margin)」，无一例失败发生在 residual 小于 margin 处；但另有 40/70 行同样满足该条件却均非 material failure（其中仅 16 行 exact winner match，其余 24 行是小 regret 的 winner 错位——14 个 MNS 精确 tie 与 10 个 strict reversal）——无方向 spread 不携带决策信息。
+  - **S0b 方向化后的机制普查**：23 个 material failure 的 winner-deciding pair 分布为 tp-axis 11、mixed 10、mns-axis 2（Q235 A0/A1 Fixed-PD 的 8 个 TPOT/E2E failure 全为 tp-axis；Q30 Fixed-PD 高低压为 tp/mixed）；仅有的 2 个 mns-axis failure 是 Q235 A0/A1 Trace-PD E2E p90（regret 6.2%，勉强越过 5% 门槛）。trace 面严格反序中 tp-axis 为 0（q30 trace-pd 三轴全 0）。
+  - **A1 对照的轴分解**：serving-matched collective profile 把 Q235 两个 PO 面的 tp-axis 反序从 4/4 清零（trace-po p90 regret 21.2%→0.3%），但 Fixed-PD 仅 5→4、四项 regret 一位小数不动——prefill 路径的 TP-differential 误差源=collective profile（可修），decode 耦合的 TP-differential 误差另有来源。
+  - **MNS 不敏感缺陷**：14 个 winner-label mismatch 是 simulator 逐位相等的 tie，全部 mns-axis（如 q30 fixed-po 的 MNS16↔32、q235 fixed-pd 的 MNS64↔128）；tie 计入后 MNS 边界误差 31 与 TP 严格反序 32 相当，但 MNS 侧 regret 小。
+  - **成功的鲁棒性**：23 个 exact-winner success 中 17 个 margin-robust（margin≥1%），6 个 fragile（含 q30 trace-pd E2E p90 的 0.1% margin 与 q235 A1 fixed-po 四项）。
+  - **面级 scale 对照**：prefill-only 面 geomean scale 0.96–1.37×（绝对预测基本准确），含 decode 的面 4.3–130×——绝对误差灾难集中于 decode。
+- **异常：** 无数据异常。strict review（FAIL：3 Major/1 Minor）指出 H-SCALE 尺度混用（log spread vs relative margin）、tie 轴普查缺失、card 状态过期、Q235 一致性表述过强；全部修复，修复后 70 行 verdict 逐行不变。
+- **含义：** 分裂的现象层解释是「margin 保护 + config-differential 误差」。机制层上，21/23 个 material failure 由 TP/mixed pair 决定，且所有大 regret（≥13%）failure 都发生在含 decode 的面上：其中 Q235 Fixed-PD 有 state-drift 直接证据、Q30 高压 TTFT 有 admission 反事实证据，而 **Q30 低压 TPOT/E2E 反转的机制尚未诊断**（S1 目标）。「decode 耦合的 TP-differential 误差是主要载体」是当前最强归纳，不是对全部 failure 的已证机制归因；2 个 mns-axis 边缘 failure（6.2%）在该归纳之外。trace 面成功伴随「TP 反序为零 + TP margin 宽」，但「误差小」与「margin 宽」谁是主因仍未判——这正是 H-THRESH vs H-STATE 的判别缺口。轴标签与机制不一一对应（Q30 admission 是 MNS 阈值机制但 deciding pair 为 tp/mixed，因 TP 改变到达压力）。
+- **Claim update：** H2（action-conditioned residual）supported 且被细化：residual 的决策相关分量集中在 TP 轴、由 decode 状态耦合产生；H-SCALE 降级为必要条件；H-THRESH/H-STATE 保持 competing，待 S1 判别。
+- **下一步：** S1（sim-only 反事实：Q30 低压 Fixed-PD TPOT 反转的分量定位——这是唯一无机制解释的 material failure；fixed workload jitter 判别 H-THRESH vs H-STATE）；GPU 判别实验（加压 Trace-PD、jittered Fixed-PD 真机面，dash1–4）另行出 card 供 review。
+
+## Review 与 provenance 补记
+
+- S0 worker：codex `task-mrsn1s9c-z6ha0w`；S0b：`task-mrsnjzn6-k18x4n`（resume）；strict reviewer（fresh 只读）：`task-mrsocmlb-386btc`（verdict FAIL）；修复轮：`task-mrsop06n-pwxo0b`（fresh writable）。编排者独立验收：脚本重跑、SHA 比对、两图目视检查。
+- 产物 SHA（修复后）：decomposition.json `81ea56b2…`、decomposition.md `4d19af54…`、margin-vs-residual.png `df2110c4…`、decision-pair-axis.png `2e787301…`。
diff --git a/.research/ongoing.md b/.research/ongoing.md
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--- a/.research/ongoing.md
+++ b/.research/ongoing.md
@@ -3,14 +3,16 @@
 > 2026-07-17｜写给未参与项目的读者，可直接作为 presentation 讲稿。历史过程与复现信息见 `../runs/*/` 各 experiment card、`../docs/` 各 campaign 文档。
 >
 > **2026-07-19 update：** Qwen235 Fixed-PD 的错误排序在 exact real state composition 下已经翻正，主因是 simulator closed-loop batch state，而不是 collective。Qwen30 Fixed-PD 的 56--58% TTFT regret 也已定位：Frontier 将 decode service time 高估 4--8×，使 TP4 的 modeled concurrency 越过 MNS admission cap并产生虚假排队；去掉该等待后 Frontier 与真机都判定 TP4 topology 更快。详见 [`experiments/qwen30-fixed-pd-ttft-admission-diagnosis-20260719.md`](experiments/qwen30-fixed-pd-ttft-admission-diagnosis-20260719.md)。
+>
+> **2026-07-20 update：** 对全部 14 个 frozen case surface（70 个 case×objective）做了统一的 margin-vs-residual 分解与方向化机制普查（[`experiments/frontier-split-rootcause-s0-20260720.md`](experiments/frontier-split-rootcause-s0-20260720.md)）。三个要点：(1) 「residual 超过 margin」是失败的必要条件但远非充分——good/bad 分裂不能用无方向误差量解释；(2) 23 个 material failure 的 winner-deciding pair 中 21 个落在 TP 轴或 mixed（其余 2 个是 6.2% regret 的边缘 mns-axis case），trace 面的 TP 反序为零；A1 measured collective 把 Qwen235 两个 prefill-only 面的 TP 反序清零（trace-PO p90 regret 21.2%→0.3%）却对 Fixed-PD 完全无效——prefill 路径的 TP 差异化误差源是 collective profile（可修），decode 耦合的 TP 差异化误差是当前所有 material failure 的载体；(3) 「Fixed-PD 失败因为高压」被否证：失败 Fixed-PD 的真机 in-flight（14.05）低于全对的 Trace-PD（38.69），且低压 Fixed-PD 同样失败、失败 objective 随负载切换。另有次要缺陷：14 个 winner 错位来自 simulator 对 MNS 逐位不敏感的精确 tie。
 
 ## 一眼看懂
 
 - **Topic / problem：** LLM serving 的自动、低成本配置调优（AITuner）。当前主线问题：用 simulator 给部署配置（并行度、批量上限等）排序，什么时候可信？需要补多少真机证据？算上这些成本还划算吗？
 - **Central claim：** simulator 要能帮助配置调优，必须先满足 scheduler transition 的 liveness/coverage，再满足「配置相关残差小于真机 decision margin」；前者决定 capacity 是否有定义，后者决定排序是否正确。(ID: C0)
 - **当前结论：** 早先 35 个 trace stall 不是 Frontier scheduler liveness failure：adapter 为不满 16-token 的 prefix block 错误生成了 cache identity，Frontier 又没有 fail-fast。修正为完整 block、使用真实 graph buckets/KV blocks 和 `piecewise`/`KERNEL_ONLY` profile 后，Qwen30 Trace-PD 的全部 12 个 cell 完成 129/129 request，Frontier 对 TTFT/TPOT/E2E 的 6 个 argmin 均与三次 fresh-server 真机一致；但绝对 latency 仍高估 4--511×。这只证明一个 MoE Trace-PD surface 的 selection fidelity，不能外推到 prefill-only、fixed workload 或 235B。
-- **最大 uncertainty / risk：** 这个正确选择是否依赖 Trace-PD 的 queue/margin 偶然性；Fixed-PD、Trace-P、Fixed-P 与大型 FP8 MoE 是否仍保留正确 config ranking。Q235 还缺少同栈 profile/runtime contract，不能复用旧 vLLM 0.10.2 数据。
-- **下一项 critical action：** 完成 Qwen30 其余三项 fixed/trace × PD/P surface。Fixed case 已先启动无请求 vLLM runtime-state preflight；Trace-P 的 graph-aligned Frontier 12-cell CPU surface 正在运行。Q235 先做 vLLM 0.20 TP4/TP8 compatibility gate，随后才允许新 profile。
+- **最大 uncertainty / risk：** trace 面成功的原因未判——是 decode 耦合的 TP 差异化误差在 trace 状态分布下真的变小，还是只是被宽 TP margin 掩盖。这决定「sim 剪枝可信域」的边界怎么画，也决定加压 trace 是否会失败。
+- **下一项 critical action：** 判别两个失败机制假设（离散阈值转换 vs 闭环 state 漂移）：先做零 GPU 的 sim-only jitter 反事实与 Q30 低压 Fixed-PD TPOT 反转分量定位，再按结果决定 dash1–4 上的加压 Trace-PD / jittered Fixed-PD 真机判别面。
 - **停止条件：** T1 出 verdict 且成本账本建立后：pass 且摊销论证成立 → 转向「sim 剪枝 + 真机终选」的 hybrid 机制设计；fail → 转入失败机制归因；两条路都无 insight 增量 → 收敛写作。
 
 ## 核心概念
@@ -34,9 +36,10 @@
       - **Supporting：** 235B prefill-only regret=0；235B fixed-shape mixed 的 top set 全中；30B 加 per-TP 校准后 regret 0.76%（但这是外部端到端 scale 给出的上界，不是原生 profile 保真度）。
       - **Counterevidence：** 修正 prefix trace contract 后的 TP2/MNS16 `none`-graph run 完成但 p50 TPOT 约 96 ms，真机为约 14 ms；然而该比较尚未对齐 real vLLM 的 `FULL_AND_PIECEWISE` graph path。
       - **下一项 discriminative experiment：** 补齐 `KERNEL_ONLY` graph family并以 `piecewise` 重跑相同 trace；若 full surface 仍错，graph omission 不再是可用解释。
-    - **Hypothesis（机制，active）：** 误差机制是 action-conditioned residual——执行状态的转移（并行拓扑、kernel family、graph mode、batch 组成）使按算子 profile 的组合预测跨配置不可复合；残差大于 margin 时排序失败。(ID: H2；supported)
+    - **Hypothesis（机制，active）：** 误差机制是 action-conditioned residual——执行状态的转移（并行拓扑、kernel family、graph mode、batch 组成）使按算子 profile 的组合预测跨配置不可复合；残差大于 margin 时排序失败。(ID: H2；supported，已细化)
       - **Supporting：** 三个 TP 档的端到端校准系数为 0.72/0.47/0.35，残差确实随配置剧烈变化；235B 的批量上限交互预测错误但被 2× margin 容忍；30B prefill-only 在低负载近似对齐、饱和后按 TP 反向放大，最终 τ-b=−1。
-      - **下一步：** 按 collective 通信 → batch 组成 → 调度器逐步轨迹的单变量顺序定位组合性失效点（对应 experiment card 中 A1/A2/A3 消融阶梯）。
+      - **细化（2026-07-20 统一普查）：** 决策相关的残差分量集中在 TP 轴且由 decode 状态耦合产生——prefill-only 面的绝对 scale 仅 0.96–1.37× 且 measured collective 即可清除其 TP 反序，而含 decode 的面 scale 4.3–130×、全部 material failure 都由 TP/mixed pair 决定。「residual>margin」只是必要条件；失败还需要残差对准 winner-deciding pair。
+      - **下一步：** 判别两个 competing 机制假设——离散阈值转换（admission cap/profile cliff 把均匀高估转成差异化误差；打破 fixed workload 的同步性应恢复排序）vs 闭环 state 漂移（打破同步性也救不了）。最便宜路径：sim-only jitter 反事实 + Q30 低压 Fixed-PD TPOT 反转的分量定位（唯一无机制解释的 material failure）。
   - **Subclaim：** 成本论证只有在摊销前提下成立。(ID: C3)
     - **Hypothesis（active）：** 每个 model×硬件×runtime 的一次性对齐成本，摊销到大配置面、频繁重调（引擎版本 churn 的频率证据见 claim map）或禁止在线实验的场景后，低于重复真机调优。(ID: H3；untested——分母已实测，分子未入账)
       - **下一步：** 建 cost ledger（见「下一步」）。
@@ -52,7 +55,7 @@
 ## Key evidence（最多 3 条）
 
 - **E1（否证「prefill-only 是充分 easy condition」，支持 H2）：** 30B BF16、去掉 decode/prefix/混合 batch 后，真机最优是 TP4（8 vs 7 req/s/GPU），simulator 却把 TP4 排最差（6 vs 8）：top set 无交集，regret 12.5%，τ-b=−1。产物：`../runs/frontier-phase-factorial-v0/results/final/`（dash0，12.07 H20-GPUh）。
-- **E2（margin 可掩盖残差，支持 C0/H2）：** 235B FP8 的 prefill-only 与 fixed-shape mixed 都选对 top set，但 simulator 漏掉并发上限（max-num-seqs）×批 token 上限（max-num-batched-tokens）的交互棋盘格，并把 10/34 个真机 anchor 误判为不可行；真机头部 margin 有 2×，残差被容忍。产物：`../runs/frontier-multicase-sufficiency-v0/best_effort/fixed_cohort_evidence/`、`../runs/frontier-multicase-sufficiency-v1/results/t0-final/`。
+- **E2（统一机制普查：material failure 全部由 decode 耦合的 TP 差异化误差决定，支持 H2 细化）：** 对 14 个 frozen surface、70 个 case×objective 的方向化分解显示：23 个 material failure 中 21 个由 TP/mixed pair 决定（仅 2 个 6.2% 边缘 mns-axis case）、trace 面 TP 反序为零；measured collective（A1）把 Qwen235 两个 prefill-only 面的 TP 反序清零（trace-PO p90 regret 21.2%→0.3%）但对 Fixed-PD 的 33% 无效；「residual>margin」仅为失败的必要条件。产物：[`../runs/frontier-split-rootcause-v0/results/`](../runs/frontier-split-rootcause-v0/results/decomposition.md)（实验 card：[`experiments/frontier-split-rootcause-s0-20260720.md`](experiments/frontier-split-rootcause-s0-20260720.md)）。
 - **E3（selection 与 calibration 分开）：** 用完整 block projection、`piecewise` 和 graph-compatible KERNEL_ONLY profile 后，Qwen30 Trace-PD 的 12/12 sim cells 完成，6 个 mean/p90 latency objective 的 argmin 都与真机一致；但 sim/real latency ratio 仍为 4--511×。产物：[`../runs/frontier-fidelity-envelope-v1/graph-piecewise-experiment-card.md`](../runs/frontier-fidelity-envelope-v1/graph-piecewise-experiment-card.md)。
 
 ## 下一步（最多 3 项）
diff --git a/runs/frontier-split-rootcause-v0/analyze_split_decomposition.py b/runs/frontier-split-rootcause-v0/analyze_split_decomposition.py
new file mode 100644
index 0000000..4e3d178
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/analyze_split_decomposition.py
@@ -0,0 +1,1444 @@
+#!/usr/bin/env python3
+"""Analyze frozen good/bad Frontier selection cases by margin and residual."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import math
+import os
+import re
+from dataclasses import dataclass
+from pathlib import Path
+from statistics import fmean
+from typing import Any
+
+
+HERE = Path(__file__).resolve().parent
+DEFAULT_INPUT_ROOT = HERE / "frozen-inputs"
+DEFAULT_RESULTS_ROOT = HERE / "results"
+
+OBJECTIVE_ORDER = {
+    "ttft_mean_ms": 0,
+    "ttft_p90_ms": 1,
+    "tpot_mean_ms": 2,
+    "tpot_p90_ms": 3,
+    "e2e_mean_ms": 4,
+    "e2e_p90_ms": 5,
+}
+
+CONFIG_PATTERN = re.compile(
+    r"^tp(?P<tp>[0-9]+)(?:_ep(?P<ep>[0-9]+))?_mns(?P<mns>[0-9]+)$"
+)
+INVERSION_AXES = ("tp-axis", "mns-axis", "mixed")
+
+
+@dataclass(frozen=True)
+class Surface:
+    case: str
+    objective: str
+    values: dict[str, tuple[float, float]]
+    expected_configs: tuple[str, ...]
+    expected_sim_winner: str
+    expected_real_winner: str
+    expected_regret: float | None
+    sources: tuple[str, ...]
+
+
+def load_json(path: Path) -> dict[str, Any]:
+    with path.open() as handle:
+        value = json.load(handle)
+    if not isinstance(value, dict):
+        raise ValueError(f"expected JSON object: {path}")
+    return value
+
+
+def atomic_write(path: Path, text: str) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    temporary = path.with_suffix(path.suffix + ".tmp")
+    temporary.write_text(text)
+    os.replace(temporary, path)
+
+
+def positive_float(value: Any, context: str) -> float:
+    if not isinstance(value, (int, float)) or isinstance(value, bool):
+        raise ValueError(f"non-numeric value for {context}: {value!r}")
+    result = float(value)
+    if not math.isfinite(result) or result <= 0:
+        raise ValueError(f"non-positive or non-finite value for {context}: {value!r}")
+    return result
+
+
+def normalized_objective(metric: str, statistic: str) -> str:
+    return f"{metric.removesuffix('_ms')}_{statistic}_ms"
+
+
+def objective_key(objective: str) -> tuple[int, str]:
+    return OBJECTIVE_ORDER.get(objective, len(OBJECTIVE_ORDER)), objective
+
+
+def config_dimensions(config: str) -> tuple[tuple[int, int | None], int]:
+    match = CONFIG_PATTERN.fullmatch(config)
+    if match is None:
+        raise ValueError(f"unrecognized config name: {config}")
+    ep = int(match.group("ep")) if match.group("ep") is not None else None
+    return (int(match.group("tp")), ep), int(match.group("mns"))
+
+
+def pair_axis(left: str, right: str) -> str:
+    if left == right:
+        return "none"
+    left_plan, left_mns = config_dimensions(left)
+    right_plan, right_mns = config_dimensions(right)
+    plan_differs = left_plan != right_plan
+    mns_differs = left_mns != right_mns
+    if plan_differs and not mns_differs:
+        return "tp-axis"
+    if mns_differs and not plan_differs:
+        return "mns-axis"
+    if plan_differs and mns_differs:
+        return "mixed"
+    raise ValueError(f"distinct configs have identical dimensions: {left}, {right}")
+
+
+def load_q30_trace_pd(input_root: Path) -> list[Surface]:
+    relative = Path("q30-trace-pd/comparison.json")
+    data = load_json(input_root / relative)
+    if data.get("schema") != "frontier-qwen30-piecewise-graph-comparison-v1":
+        raise ValueError(f"unexpected schema: {relative}")
+    configs = tuple(sorted(data["cells"]))
+    surfaces = []
+    for source_objective, selection in sorted(
+        data["selection"].items(),
+        key=lambda item: objective_key(
+            normalized_objective(*item[0].split(":"))
+        ),
+    ):
+        metric, statistic = source_objective.split(":")
+        objective = normalized_objective(metric, statistic)
+        values = {}
+        for config in configs:
+            cell = data["cells"][config]["metrics"][metric]
+            values[config] = (
+                positive_float(cell[f"sim_{statistic}_ms"], f"{relative}:{config}:sim"),
+                positive_float(cell[f"real_{statistic}_ms"], f"{relative}:{config}:real"),
+            )
+        surfaces.append(
+            Surface(
+                case="q30 trace-pd",
+                objective=objective,
+                values=values,
+                expected_configs=configs,
+                expected_sim_winner=selection["sim_winner"],
+                expected_real_winner=selection["real_winner"],
+                expected_regret=None,
+                sources=(str(relative),),
+            )
+        )
+    return surfaces
+
+
+def load_q30_case(
+    input_root: Path,
+    case: str,
+    comparison_relative: Path,
+    audit_relative: Path,
+) -> list[Surface]:
+    comparison = load_json(input_root / comparison_relative)
+    audit = load_json(input_root / audit_relative)
+    if comparison.get("schema") != "qwen30-latency-case-frontier-real-comparison-v1":
+        raise ValueError(f"unexpected schema: {comparison_relative}")
+    if audit.get("schema") != "qwen30-latency-case-real-audit-v1":
+        raise ValueError(f"unexpected schema: {audit_relative}")
+    configs = tuple(sorted(set(comparison["cells"]) | set(audit["configs"])))
+    surfaces = []
+    for source_objective, selection in sorted(
+        comparison["selection"].items(),
+        key=lambda item: objective_key(
+            normalized_objective(*item[0].split(":"))
+        ),
+    ):
+        metric, statistic = source_objective.split(":")
+        objective = normalized_objective(metric, statistic)
+        values = {}
+        for config in configs:
+            if config not in comparison["cells"] or config not in audit["configs"]:
+                continue
+            sim = comparison["cells"][config]["metrics"].get(metric, {}).get(statistic)
+            real = (
+                audit["configs"][config]["metrics"]
+                .get(metric, {})
+                .get(f"pooled_{statistic}_ms")
+            )
+            if sim is None or real is None:
+                continue
+            values[config] = (
+                positive_float(sim, f"{comparison_relative}:{config}:sim"),
+                positive_float(real, f"{audit_relative}:{config}:real"),
+            )
+        surfaces.append(
+            Surface(
+                case=case,
+                objective=objective,
+                values=values,
+                expected_configs=configs,
+                expected_sim_winner=selection["sim_winner"],
+                expected_real_winner=selection["real_winner"],
+                expected_regret=selection.get("selected_config_real_regret"),
+                sources=(str(comparison_relative), str(audit_relative)),
+            )
+        )
+    return surfaces
+
+
+def load_q235_campaign(
+    input_root: Path, campaign: str, relative: Path
+) -> list[Surface]:
+    data = load_json(input_root / relative)
+    if data.get("schema") != "qwen235-v020-simulator-real-comparison-v1":
+        raise ValueError(f"unexpected schema: {relative}")
+    surfaces = []
+    for case_name in ("fixed-pd", "fixed-po", "trace-pd", "trace-po"):
+        case = data["cases"][case_name]
+        configs = tuple(sorted(set(case["sim"]) | set(case["real"])))
+        for objective, selection in sorted(
+            case["comparison"].items(), key=lambda item: objective_key(item[0])
+        ):
+            values = {}
+            for config in configs:
+                if config not in case["sim"] or config not in case["real"]:
+                    continue
+                sim = case["sim"][config].get(objective)
+                real = case["real"][config].get(objective)
+                if sim is None or real is None:
+                    continue
+                values[config] = (
+                    positive_float(sim, f"{relative}:{case_name}:{config}:sim"),
+                    positive_float(real, f"{relative}:{case_name}:{config}:real"),
+                )
+            surfaces.append(
+                Surface(
+                    case=f"q235 {campaign} {case_name}",
+                    objective=objective,
+                    values=values,
+                    expected_configs=configs,
+                    expected_sim_winner=selection["sim_winner"],
+                    expected_real_winner=selection["real_winner"],
+                    expected_regret=selection.get("selected_real_regret"),
+                    sources=(str(relative),),
+                )
+            )
+    return surfaces
+
+
+def load_surfaces(input_root: Path) -> list[Surface]:
+    surfaces = load_q30_trace_pd(input_root)
+    q30_specs = (
+        (
+            "q30 fixed-pd high",
+            Path("q30-fixed-hi/fixed-pd/comparison.json"),
+            Path("q30-fixed-hi/fixed-pd/real-audit.json"),
+        ),
+        (
+            "q30 fixed-po high",
+            Path("q30-fixed-hi/fixed-po/comparison.json"),
+            Path("q30-fixed-hi/fixed-po/real-audit.json"),
+        ),
+        (
+            "q30 fixed-pd low",
+            Path("q30-expansion-lo/fixed-pd-comparison.json"),
+            Path("q30-expansion-lo/fixed-pd-real-audit.json"),
+        ),
+        (
+            "q30 fixed-po low",
+            Path("q30-expansion-lo/fixed-po-comparison.json"),
+            Path("q30-expansion-lo/fixed-po-real-audit.json"),
+        ),
+        (
+            "q30 trace-po low",
+            Path("q30-expansion-lo/trace-po-comparison.json"),
+            Path("q30-expansion-lo/trace-po-real-audit.json"),
+        ),
+    )
+    for case, comparison, audit in q30_specs:
+        surfaces.extend(load_q30_case(input_root, case, comparison, audit))
+    surfaces.extend(
+        load_q235_campaign(
+            input_root, "A0", Path("q235-fourcase-a0/comparison.json")
+        )
+    )
+    surfaces.extend(
+        load_q235_campaign(
+            input_root, "A1", Path("q235-ablation-a1/comparison.json")
+        )
+    )
+    return surfaces
+
+
+def analyze_surface(surface: Surface) -> tuple[dict[str, Any], list[str]]:
+    anomalies = []
+    paired_configs = tuple(sorted(surface.values))
+    missing_configs = sorted(set(surface.expected_configs) - set(paired_configs))
+    if missing_configs:
+        anomalies.append(
+            f"{surface.case} / {surface.objective}: missing paired sim+real data for "
+            + ", ".join(missing_configs)
+        )
+    if len(paired_configs) < 2:
+        return (
+            {
+                "case": surface.case,
+                "objective": surface.objective,
+                "sim_winner": None,
+                "real_winner": None,
+                "regret": None,
+                "config_uniform_scale": None,
+                "log_ratio_spread_all": None,
+                "log_ratio_spread_real_top3": None,
+                "real_relative_margin_best_vs_second": None,
+                "sim_winner_real_relative_loss": None,
+                "failure": None,
+                "h_scale_condition_spread_gt_log_margin": None,
+                "h_scale_verdict": "N/A",
+                "winner_match": None,
+                "winner_deciding_axis": None,
+                "winner_pair_m_s_percent": None,
+                "winner_pair_delta_s_percent": None,
+                "winner_pair_strict_reversal": None,
+                "winner_pair_relation": "N/A",
+                "n_inv_tp": None,
+                "n_inv_mns": None,
+                "n_inv_mixed": None,
+                "n_tie_tp": None,
+                "n_tie_mns": None,
+                "n_tie_mixed": None,
+                "fragile_success": None,
+                "pairwise_vs_real_winner": [],
+                "paired_config_count": len(paired_configs),
+                "expected_config_count": len(surface.expected_configs),
+                "real_top3_configs": [],
+                "missing_configs": missing_configs,
+                "sources": list(surface.sources),
+            },
+            anomalies,
+        )
+
+    sim_ranking = sorted(paired_configs, key=lambda config: (surface.values[config][0], config))
+    real_ranking = sorted(paired_configs, key=lambda config: (surface.values[config][1], config))
+    sim_winner = sim_ranking[0]
+    real_winner = real_ranking[0]
+    real_best = surface.values[real_winner][1]
+    regret = surface.values[sim_winner][1] / real_best - 1.0
+    margin = surface.values[real_ranking[1]][1] / real_best - 1.0
+    log_ratios = {
+        config: math.log(surface.values[config][0] / surface.values[config][1])
+        for config in paired_configs
+    }
+    spread_all = max(log_ratios.values()) - min(log_ratios.values())
+    top3 = tuple(real_ranking[:3])
+    top3_ratios = [log_ratios[config] for config in top3]
+    spread_top3 = max(top3_ratios) - min(top3_ratios)
+    scale = math.exp(fmean(log_ratios.values()))
+    failure = regret > 0.05
+    residual_exceeds_log_margin = spread_top3 > math.log1p(margin)
+    h_scale_holds = failure == residual_exceeds_log_margin
+
+    pairwise = []
+    inversion_counts = {axis: 0 for axis in INVERSION_AXES}
+    sim_at_real_winner = surface.values[real_winner][0]
+    for config in paired_configs:
+        sim_value, real_value = surface.values[config]
+        real_pair_log = math.log(real_value / real_best)
+        sim_pair_log = math.log(sim_value / sim_at_real_winner)
+        pair_margin_percent = 100.0 * real_pair_log
+        delta_percent = 100.0 * (sim_pair_log - real_pair_log)
+        axis = pair_axis(real_winner, config)
+        inversion = real_value > real_best and sim_value < sim_at_real_winner
+        delta_inversion = (
+            pair_margin_percent > 0
+            and delta_percent < -pair_margin_percent
+        )
+        if inversion != delta_inversion:
+            anomalies.append(
+                f"{surface.case} / {surface.objective} / {config}: direct inversion "
+                f"test disagrees with delta < -margin"
+            )
+        if inversion:
+            inversion_counts[axis] += 1
+        pairwise.append(
+            {
+                "config": config,
+                "axis_vs_real_winner": axis,
+                "real_pair_margin_percent": pair_margin_percent,
+                "signed_pairwise_delta_percent": delta_percent,
+                "inversion": inversion,
+            }
+        )
+
+    winner_pair = next(item for item in pairwise if item["config"] == sim_winner)
+    winner_match = sim_winner == real_winner
+    if winner_match:
+        winner_pair_relation = "match"
+    elif winner_pair["inversion"]:
+        winner_pair_relation = "reversal"
+    elif surface.values[sim_winner][0] == sim_at_real_winner:
+        winner_pair_relation = "sim-tie"
+    else:
+        winner_pair_relation = "non-reversal"
+    tie_counts = {axis: 0 for axis in INVERSION_AXES}
+    if winner_pair_relation == "sim-tie":
+        tie_counts[winner_pair["axis_vs_real_winner"]] += 1
+
+    if sim_winner != surface.expected_sim_winner:
+        anomalies.append(
+            f"{surface.case} / {surface.objective}: recomputed sim winner "
+            f"{sim_winner} != frozen JSON {surface.expected_sim_winner}"
+        )
+    if real_winner != surface.expected_real_winner:
+        anomalies.append(
+            f"{surface.case} / {surface.objective}: recomputed real winner "
+            f"{real_winner} != frozen JSON {surface.expected_real_winner}"
+        )
+    if surface.expected_regret is not None and not math.isclose(
+        regret, float(surface.expected_regret), rel_tol=1e-12, abs_tol=1e-12
+    ):
+        anomalies.append(
+            f"{surface.case} / {surface.objective}: recomputed regret "
+            f"{regret:.12g} != frozen JSON {float(surface.expected_regret):.12g}"
+        )
+
+    return (
+        {
+            "case": surface.case,
+            "objective": surface.objective,
+            "sim_winner": sim_winner,
+            "real_winner": real_winner,
+            "regret": regret,
+            "config_uniform_scale": scale,
+            "log_ratio_spread_all": spread_all,
+            "log_ratio_spread_real_top3": spread_top3,
+            "real_relative_margin_best_vs_second": margin,
+            "sim_winner_real_relative_loss": regret,
+            "failure": failure,
+            "h_scale_condition_spread_gt_log_margin": residual_exceeds_log_margin,
+            "h_scale_verdict": "HOLDS" if h_scale_holds else "COUNTEREXAMPLE",
+            "winner_match": winner_match,
+            "winner_deciding_axis": pair_axis(real_winner, sim_winner),
+            "winner_pair_m_s_percent": winner_pair["real_pair_margin_percent"],
+            "winner_pair_delta_s_percent": winner_pair["signed_pairwise_delta_percent"],
+            "winner_pair_strict_reversal": winner_pair["inversion"],
+            "winner_pair_relation": winner_pair_relation,
+            "n_inv_tp": inversion_counts["tp-axis"],
+            "n_inv_mns": inversion_counts["mns-axis"],
+            "n_inv_mixed": inversion_counts["mixed"],
+            "n_tie_tp": tie_counts["tp-axis"],
+            "n_tie_mns": tie_counts["mns-axis"],
+            "n_tie_mixed": tie_counts["mixed"],
+            "fragile_success": winner_match and margin < 0.01,
+            "pairwise_vs_real_winner": pairwise,
+            "paired_config_count": len(paired_configs),
+            "expected_config_count": len(surface.expected_configs),
+            "real_top3_configs": list(top3),
+            "missing_configs": missing_configs,
+            "sources": list(surface.sources),
+        },
+        anomalies,
+    )
+
+
+def row_index(rows: list[dict[str, Any]]) -> dict[tuple[str, str], dict[str, Any]]:
+    return {(row["case"], row["objective"]): row for row in rows}
+
+
+def cross_checks(rows: list[dict[str, Any]]) -> tuple[list[dict[str, Any]], list[str]]:
+    by_key = row_index(rows)
+    checks = []
+    anomalies = []
+
+    def check(name: str, observed: float, expected_percent: float) -> None:
+        observed_percent = observed * 100.0
+        passed = round(observed_percent, 1) == expected_percent
+        checks.append(
+            {
+                "name": name,
+                "observed_percent": observed_percent,
+                "expected_percent": expected_percent,
+                "passed": passed,
+            }
+        )
+        if not passed:
+            anomalies.append(
+                f"hard cross-check failed: {name}: observed {observed_percent:.6f}% "
+                f"vs expected {expected_percent:.1f}%"
+            )
+
+    check(
+        "q30 high-pressure fixed-pd TTFT mean regret",
+        by_key[("q30 fixed-pd high", "ttft_mean_ms")]["regret"],
+        58.0,
+    )
+    check(
+        "q235 A0 fixed-pd TPOT mean regret",
+        by_key[("q235 A0 fixed-pd", "tpot_mean_ms")]["regret"],
+        33.0,
+    )
+    check(
+        "q235 A1 fixed-pd TPOT mean regret",
+        by_key[("q235 A1 fixed-pd", "tpot_mean_ms")]["regret"],
+        33.0,
+    )
+    trace_pd_rows = [row for row in rows if row["case"] == "q30 trace-pd"]
+    trace_passed = len(trace_pd_rows) == 6 and all(
+        round(row["regret"] * 100.0, 1) == 0.0 for row in trace_pd_rows
+    )
+    checks.append(
+        {
+            "name": "q30 trace-pd all-objective regret",
+            "observed_percent": [row["regret"] * 100.0 for row in trace_pd_rows],
+            "expected_percent": [0.0] * 6,
+            "passed": trace_passed,
+        }
+    )
+    if not trace_passed:
+        anomalies.append(
+            "hard cross-check failed: q30 trace-pd does not have six objectives all at 0.0% regret"
+        )
+
+    def check_sequence(
+        name: str, observed: list[float], expected_percent: list[float]
+    ) -> None:
+        observed_percent = [value * 100.0 for value in observed]
+        passed = [round(value, 1) for value in observed_percent] == expected_percent
+        checks.append(
+            {
+                "name": name,
+                "observed_percent": observed_percent,
+                "expected_percent": expected_percent,
+                "passed": passed,
+            }
+        )
+        if not passed:
+            anomalies.append(
+                f"hard cross-check failed: {name}: observed "
+                f"{[round(value, 6) for value in observed_percent]} vs expected "
+                f"{expected_percent}"
+            )
+
+    check_sequence(
+        "q235 Trace-PO TTFT p90 A0 to A1 regret",
+        [
+            by_key[("q235 A0 trace-po", "ttft_p90_ms")]["regret"],
+            by_key[("q235 A1 trace-po", "ttft_p90_ms")]["regret"],
+        ],
+        [21.2, 0.3],
+    )
+    fixed_pd_objectives = (
+        "tpot_mean_ms",
+        "tpot_p90_ms",
+        "e2e_mean_ms",
+        "e2e_p90_ms",
+    )
+    fixed_pd_expected = [33.0, 37.2, 30.7, 34.6]
+    check_sequence(
+        "q235 Fixed-PD TPOT/E2E regrets unchanged from A0 to A1",
+        [
+            by_key[(f"q235 {campaign} fixed-pd", objective)]["regret"]
+            for campaign in ("A0", "A1")
+            for objective in fixed_pd_objectives
+        ],
+        fixed_pd_expected + fixed_pd_expected,
+    )
+    return checks, anomalies
+
+
+def known_attribution(input_root: Path) -> dict[str, Any]:
+    q30_relative = Path("q30-admission-diag/result.json")
+    q235_relative = Path("q235-state-diag/state-diagnosis-exact.json")
+    q30 = load_json(input_root / q30_relative)
+    q235 = load_json(input_root / q235_relative)
+    if q30.get("schema") != "qwen30-fixed-pd-ttft-admission-diagnosis-v1":
+        raise ValueError(f"unexpected schema: {q30_relative}")
+    if q235.get("schema") != "qwen235-fixed-pd-state-diagnosis-v1":
+        raise ValueError(f"unexpected schema: {q235_relative}")
+
+    q30_cells = []
+    for config, cell in sorted(q30["cells"].items()):
+        q30_cells.append(
+            {
+                "config": config,
+                "sim_tpot_over_real": cell["tpot_overprediction_ratio"],
+                "sim_required_slots": cell["simulator"]["required_slots"],
+                "mns": cell["mns"],
+                "real_required_slots_upper_bound": cell["real"]["required_slots_upper_bound"],
+                "sim_first_scheduling_wait_ms": cell["simulator"]["first_scheduling_delay_ms"],
+                "sim_queue_free_ttft_ms": cell["simulator"]["queue_free_ttft_ms"],
+                "sim_ttft_ms": cell["simulator"]["ttft_ms"],
+                "real_ttft_ms": cell["real"]["ttft_ms"],
+                "real_waiting_max": cell["real"]["periodic_queue"]["waiting_max"],
+            }
+        )
+
+    q235_configs = []
+    for config in sorted(q235["simulator"]):
+        q235_configs.append(
+            {
+                "config": config,
+                "sim_own_decode_batch_mean": q235["simulator"][config]["decode_batch_size"]["mean"],
+                "real_exact_decode_batch_mean": q235["real_iteration_state"][config]["decode_batch_size"]["mean"],
+                "real_token_weighted_iteration_ms": q235["real_iteration_state"][config]["decode_token_weighted_iteration_elapsed_ms"],
+                "exact_state_matched_sim_ms": q235["exact_state_matched"]["configs"][config]["components_ms"]["total"],
+                "exact_state_coverage": q235["exact_state_matched"]["configs"][config]["coverage"],
+            }
+        )
+
+    component_order = (
+        "total",
+        "moe_compute",
+        "attention",
+        "tp_dp_communication",
+        "ep_communication",
+        "moe_routing",
+        "dense_mlp_compute",
+        "pipeline_communication",
+        "runtime_overhead",
+    )
+    q235_components = []
+    own = q235["simulator_internal_all_step_tp8_minus_tp4_ms"]
+    exact = q235["exact_state_matched"]["tp8_minus_tp4_ms"]
+    for component in component_order:
+        q235_components.append(
+            {
+                "component": component,
+                "own_composition_tp8_minus_tp4_ms": own[component],
+                "exact_state_tp8_minus_tp4_ms": exact[component],
+            }
+        )
+    return {
+        "q30_admission": {
+            "source": str(q30_relative),
+            "verdict": q30["verdict"],
+            "cells": q30_cells,
+            "contrasts": q30["contrasts"],
+        },
+        "q235_state": {
+            "source": str(q235_relative),
+            "verdict": q235["verdict"],
+            "configs": q235_configs,
+            "components": q235_components,
+            "contrast_decomposition": q235["contrast_decomposition"],
+            "reference": q235["reference"],
+        },
+    }
+
+
+def directional_summary(rows: list[dict[str, Any]]) -> dict[str, Any]:
+    case_order = list(dict.fromkeys(row["case"] for row in rows))
+    by_case = []
+    for case in case_order:
+        case_rows = [row for row in rows if row["case"] == case]
+        by_case.append(
+            {
+                "case": case,
+                "n_inv_tp": sum(row["n_inv_tp"] for row in case_rows),
+                "n_inv_mns": sum(row["n_inv_mns"] for row in case_rows),
+                "n_inv_mixed": sum(row["n_inv_mixed"] for row in case_rows),
+                "n_tie_tp": sum(row["n_tie_tp"] for row in case_rows),
+                "n_tie_mns": sum(row["n_tie_mns"] for row in case_rows),
+                "n_tie_mixed": sum(row["n_tie_mixed"] for row in case_rows),
+            }
+        )
+    fragile = [
+        {
+            "case": row["case"],
+            "objective": row["objective"],
+            "real_relative_margin_percent": 100.0
+            * row["real_relative_margin_best_vs_second"],
+        }
+        for row in rows
+        if row["fragile_success"]
+    ]
+    material_failures = [
+        {
+            "case": row["case"],
+            "objective": row["objective"],
+            "winner_deciding_axis": row["winner_deciding_axis"],
+            "winner_pair_m_s_percent": row["winner_pair_m_s_percent"],
+            "winner_pair_delta_s_percent": row["winner_pair_delta_s_percent"],
+            "regret": row["regret"],
+        }
+        for row in rows
+        if row["failure"]
+    ]
+    boundary_winner_ties = [
+        {
+            "case": row["case"],
+            "objective": row["objective"],
+            "real_winner": row["real_winner"],
+            "sim_winner": row["sim_winner"],
+            "winner_deciding_axis": row["winner_deciding_axis"],
+        }
+        for row in rows
+        if row["winner_pair_relation"] == "sim-tie"
+    ]
+    return {
+        "axis_inversions_total": {
+            "tp-axis": sum(row["n_inv_tp"] for row in rows),
+            "mns-axis": sum(row["n_inv_mns"] for row in rows),
+            "mixed": sum(row["n_inv_mixed"] for row in rows),
+        },
+        "axis_inversions_by_case": by_case,
+        "axis_ties_total": {
+            "tp-axis": sum(row["n_tie_tp"] for row in rows),
+            "mns-axis": sum(row["n_tie_mns"] for row in rows),
+            "mixed": sum(row["n_tie_mixed"] for row in rows),
+        },
+        "strict_winner_reversal_count": sum(
+            row["winner_pair_relation"] == "reversal" for row in rows
+        ),
+        "sim_tie_winner_mismatch_count": sum(
+            row["winner_pair_relation"] == "sim-tie" for row in rows
+        ),
+        "boundary_winner_ties": boundary_winner_ties,
+        "material_failures": material_failures,
+        "margin_robust_success_count": sum(
+            row["winner_match"] and not row["fragile_success"] for row in rows
+        ),
+        "fragile_success_count": len(fragile),
+        "fragile_successes": fragile,
+    }
+
+
+def analyze(input_root: Path) -> dict[str, Any]:
+    surfaces = load_surfaces(input_root)
+    rows = []
+    anomalies = []
+    for surface in surfaces:
+        row, row_anomalies = analyze_surface(surface)
+        rows.append(row)
+        anomalies.extend(row_anomalies)
+    checks, check_anomalies = cross_checks(rows)
+    anomalies.extend(check_anomalies)
+    counterexamples = [
+        {"case": row["case"], "objective": row["objective"]}
+        for row in rows
+        if row["h_scale_verdict"] == "COUNTEREXAMPLE"
+    ]
+    data_gaps = [
+        {
+            "case": row["case"],
+            "objective": row["objective"],
+            "missing_configs": row["missing_configs"],
+        }
+        for row in rows
+        if row["missing_configs"] or row["h_scale_verdict"] == "N/A"
+    ]
+    directional = directional_summary(rows)
+    return {
+        "schema": "frontier-split-rootcause-decomposition-v2",
+        "definitions": {
+            "objective_direction": "all objectives are minimized",
+            "config_uniform_scale": "geomean_c(sim_c / real_c) over paired configs",
+            "log_ratio_spread_all": "max_c(log(sim_c / real_c)) - min_c(log(sim_c / real_c))",
+            "log_ratio_spread_real_top3": "log-ratio spread over the three configs with lowest real objective values",
+            "real_relative_margin_best_vs_second": "real_second / real_best - 1",
+            "regret": "real_sim_winner / real_best - 1, recomputed from per-config values",
+            "failure": "regret > 0.05",
+            "h_scale_verdict": "HOLDS iff failure equals (top-3 log-ratio spread > log1p(real relative margin))",
+            "signed_pairwise_delta_percent": "100 * (log(sim_c / sim_w) - log(real_c / real_w)); negative favors c relative to real",
+            "real_pair_margin_percent": "100 * log(real_c / real_w)",
+            "pair_inversion": "real_c > real_w and sim_c < sim_w, equivalently delta_c < -m_c",
+            "winner_pair_tie": "sim_s == sim_w with real_s > real_w; a decision-boundary winner-label mismatch, not a strict inversion",
+            "winner_deciding_axis": "axis difference between real winner w and sim winner s; none for a winner match",
+            "fragile_success": "winner match and real best-vs-second relative margin < 0.01",
+        },
+        "summary": {
+            "row_count": len(rows),
+            "case_count": len({row["case"] for row in rows}),
+            "failure_count": sum(row["failure"] is True for row in rows),
+            "winner_mismatch_count": sum(row["winner_match"] is False for row in rows),
+            "h_scale_counterexample_count": len(counterexamples),
+            "h_scale_counterexamples": counterexamples,
+            "data_gap_count": len(data_gaps),
+        },
+        "directional_summary": directional,
+        "rows": rows,
+        "cross_checks": checks,
+        "data_gaps": data_gaps,
+        "anomalies": anomalies,
+        "known_attribution": known_attribution(input_root),
+    }
+
+
+def percent(value: float | None, digits: int = 1) -> str:
+    if value is None:
+        return "N/A"
+    return f"{value * 100.0:.{digits}f}%"
+
+
+def multiple(value: float | None) -> str:
+    if value is None:
+        return "N/A"
+    return f"{value:.3f}x"
+
+
+def percent_points(value: float | None, signed: bool = False) -> str:
+    if value is None:
+        return "N/A"
+    sign = "+" if signed else ""
+    return f"{value:{sign}.1f}%"
+
+
+def markdown(result: dict[str, Any]) -> str:
+    summary = result["summary"]
+    lines = [
+        "# Frontier good/bad split decomposition",
+        "",
+        "All 70 rows are recomputed from frozen per-config JSON values. Lower is better for every objective. "
+        "`scale` is the geometric mean of `sim/real`; spreads are shown as `100 ×` log-space width, while `real margin` is the ordinary relative difference `100 × (real_second / real_best - 1)`. "
+        "H-SCALE compares the log-space spread with `log1p(real margin)`, not directly with the ordinary relative margin. "
+        "The real top-3 neighborhood is selected independently for every row. Directional `m_s` and `delta_s` are already expressed in log-percentage points.",
+        "",
+        f"- Rows / case surfaces: {summary['row_count']} / {summary['case_count']}.",
+        f"- Failures (`regret > 5%`): {summary['failure_count']}.",
+        f"- Exact winner mismatches: {summary['winner_mismatch_count']}.",
+        f"- H-SCALE counterexamples: {summary['h_scale_counterexample_count']}.",
+        "",
+        "## Unified decomposition",
+        "",
+        "| case | objective | sim winner | real winner | regret | scale | spread all | spread real top-3 | real margin (relative) | sim-winner real loss | failure | H-SCALE | deciding axis | m_s | delta_s | n_inv_tp | n_inv_mns | n_inv_mixed | fragile success |",
+        "|---|---|---|---|---:|---:|---:|---:|---:|---:|---|---|---|---:|---:|---:|---:|---:|---|",
+    ]
+    for row in result["rows"]:
+        lines.append(
+            "| {case} | {objective} | {sim} | {real} | {regret} | {scale} | "
+            "{spread_all} | {spread_top3} | {margin} | {loss} | {failure} | {verdict} | "
+            "{axis} | {pair_margin} | {delta} | {n_tp} | {n_mns} | {n_mixed} | {fragile} |".format(
+                case=row["case"],
+                objective=row["objective"],
+                sim=row["sim_winner"] or "N/A",
+                real=row["real_winner"] or "N/A",
+                regret=percent(row["regret"]),
+                scale=multiple(row["config_uniform_scale"]),
+                spread_all=percent(row["log_ratio_spread_all"]),
+                spread_top3=percent(row["log_ratio_spread_real_top3"]),
+                margin=percent(row["real_relative_margin_best_vs_second"]),
+                loss=percent(row["sim_winner_real_relative_loss"]),
+                failure=(
+                    "yes" if row["failure"] is True else "no" if row["failure"] is False else "N/A"
+                ),
+                verdict=row["h_scale_verdict"],
+                axis=row["winner_deciding_axis"] or "N/A",
+                pair_margin=percent_points(row["winner_pair_m_s_percent"]),
+                delta=percent_points(row["winner_pair_delta_s_percent"], signed=True),
+                n_tp=row["n_inv_tp"] if row["n_inv_tp"] is not None else "N/A",
+                n_mns=row["n_inv_mns"] if row["n_inv_mns"] is not None else "N/A",
+                n_mixed=(
+                    row["n_inv_mixed"] if row["n_inv_mixed"] is not None else "N/A"
+                ),
+                fragile=(
+                    "yes"
+                    if row["fragile_success"] is True
+                    else "no"
+                    if row["fragile_success"] is False
+                    else "N/A"
+                ),
+            )
+        )
+
+    lines.extend(
+        [
+            "",
+            "## H-SCALE verdict",
+            "",
+        ]
+    )
+    if summary["h_scale_counterexample_count"] == 0:
+        lines.append(
+            "H-SCALE holds on every available row: failure occurs exactly when the real-top-3 differential residual exceeds `log1p` of the real best-vs-second relative margin."
+        )
+    else:
+        failure_counterexamples = sum(
+            row["failure"] is True and row["h_scale_verdict"] == "COUNTEREXAMPLE"
+            for row in result["rows"]
+        )
+        nonfailure_counterexamples = summary["h_scale_counterexample_count"] - failure_counterexamples
+        lines.extend(
+            [
+                "H-SCALE is not sufficient as stated; the following rows are counterexamples to the biconditional:",
+                "",
+                f"All {nonfailure_counterexamples} observed counterexamples are non-failures with spread > `log1p(margin)`; "
+                f"there are {failure_counterexamples} failures with spread <= `log1p(margin)`. Thus the threshold is necessary for the observed failures but not sufficient to predict them.",
+                "",
+                "| case | objective | failure | spread real top-3 | real margin | counterexample type |",
+                "|---|---|---|---:|---:|---|",
+            ]
+        )
+        for row in result["rows"]:
+            if row["h_scale_verdict"] != "COUNTEREXAMPLE":
+                continue
+            kind = (
+                "failure with spread <= log1p(margin)"
+                if row["failure"]
+                else "non-failure with spread > log1p(margin)"
+            )
+            lines.append(
+                f"| {row['case']} | {row['objective']} | "
+                f"{'yes' if row['failure'] else 'no'} | "
+                f"{percent(row['log_ratio_spread_real_top3'])} | "
+                f"{percent(row['real_relative_margin_best_vs_second'])} | {kind} |"
+            )
+
+    directional = result["directional_summary"]
+    lines.extend(
+        [
+            "",
+            "## S0b directional conclusions",
+            "",
+            "Directional pair statistics remove the S0 range statistic's ambiguity by measuring every config against the real winner. "
+            "Strict inversions use the frozen-value test `real_c > real_w and sim_c < sim_w`; simulator ties are not counted as inversions.",
+            "",
+            "### (a) Which config axis decides each material failure?",
+            "",
+            "| case | objective | real winner → sim winner | deciding axis | m_s | delta_s | -delta_s | regret |",
+            "|---|---|---|---|---:|---:|---:|---:|",
+        ]
+    )
+    for row in result["rows"]:
+        if not row["failure"]:
+            continue
+        lines.append(
+            f"| {row['case']} | {row['objective']} | {row['real_winner']} → "
+            f"{row['sim_winner']} | {row['winner_deciding_axis']} | "
+            f"{percent_points(row['winner_pair_m_s_percent'])} | "
+            f"{percent_points(row['winner_pair_delta_s_percent'], signed=True)} | "
+            f"{percent_points(-row['winner_pair_delta_s_percent'])} | "
+            f"{percent(row['regret'])} |"
+        )
+
+    lines.extend(
+        [
+            "",
+            "### (b) Where do TP-axis and MNS-axis inversions and boundary ties concentrate?",
+            "",
+            "`n_inv_*` counts sum strict `(real winner, c)` pair inversions across all objectives in each case; a row can contain more than one inverted pair. "
+            "`n_tie_*` counts cover exact simulator ties only for the simulator-selected winner versus the real winner. Ties remain decision-boundary winner-label mismatches, not strict reversals.",
+            "",
+            "| case | n_inv_tp | n_inv_mns | n_inv_mixed | n_tie_tp | n_tie_mns | n_tie_mixed |",
+            "|---|---:|---:|---:|---:|---:|---:|",
+        ]
+    )
+    for item in directional["axis_inversions_by_case"]:
+        lines.append(
+            f"| {item['case']} | {item['n_inv_tp']} | {item['n_inv_mns']} | "
+            f"{item['n_inv_mixed']} | {item['n_tie_tp']} | {item['n_tie_mns']} | "
+            f"{item['n_tie_mixed']} |"
+        )
+    totals = directional["axis_inversions_total"]
+    tie_totals = directional["axis_ties_total"]
+    lines.append(
+        f"| **total** | **{totals['tp-axis']}** | **{totals['mns-axis']}** | "
+        f"**{totals['mixed']}** | **{tie_totals['tp-axis']}** | "
+        f"**{tie_totals['mns-axis']}** | **{tie_totals['mixed']}** |"
+    )
+
+    def concentrated(axis_key: str) -> str:
+        ranked = sorted(
+            (
+                (item[axis_key], item["case"])
+                for item in directional["axis_inversions_by_case"]
+                if item[axis_key] > 0
+            ),
+            key=lambda item: (-item[0], item[1]),
+        )
+        return ", ".join(f"{case} ({count})" for count, case in ranked[:5])
+
+    by_key = row_index(result["rows"])
+    q30_ttft_axes = [
+        by_key[("q30 fixed-pd high", objective)]["winner_deciding_axis"]
+        for objective in ("ttft_mean_ms", "ttft_p90_ms")
+    ]
+    q235_fixed_pd_failures = [
+        row
+        for row in result["rows"]
+        if row["case"] in ("q235 A0 fixed-pd", "q235 A1 fixed-pd")
+        and row["failure"]
+    ]
+    q235_fixed_pd_axes = {
+        row["winner_deciding_axis"] for row in q235_fixed_pd_failures
+    }
+    q235_consistency = (
+        "The eight Q235 A0/A1 Fixed-PD failures are all tp-axis. This does not conflict with the A0/MNS64 state-drift diagnosis, but does not constitute additional state-drift evidence for A1/MNS128."
+        if len(q235_fixed_pd_failures) == 8 and q235_fixed_pd_axes == {"tp-axis"}
+        else "The Q235 A0/A1 Fixed-PD failures do not match the expected eight tp-axis cases; no state-drift compatibility claim is made."
+    )
+    lines.extend(
+        [
+            "",
+            f"- Among strict inversions, TP-axis cases are most concentrated in: {concentrated('n_inv_tp')}.",
+            f"- Among strict inversions, MNS-axis cases are most concentrated in: {concentrated('n_inv_mns')}.",
+            f"- {q235_consistency}",
+            f"- Q30 admission evidence does not map one-to-one to an MNS-axis deciding pair: high-pressure Fixed-PD TTFT mean is **{q30_ttft_axes[0]}** and p90 is **{q30_ttft_axes[1]}**. "
+            "This is an axis/mechanism mismatch, not a direct causal contradiction: changing TP changes offered arrival pressure, while the diagnosed nonlinear event is crossing the MNS admission cap. It rules out the simpler claim that an MNS-threshold mechanism must appear as an mns-axis winner pair.",
+            f"- All {directional['sim_tie_winner_mismatch_count']} exact simulator winner ties are mns-axis. Including these boundary errors gives MNS **{totals['mns-axis']} + {tie_totals['mns-axis']} = {totals['mns-axis'] + tie_totals['mns-axis']}**, comparable to TP's **{totals['tp-axis']}** strict inversions.",
+            "",
+            "The exact ties below show that Frontier is completely insensitive to MNS changes within the corresponding case/objective cell:",
+            "",
+            "| case | objective | real winner ↔ simulator-selected tied winner (MNS pair) |",
+            "|---|---|---|",
+        ]
+    )
+    for item in directional["boundary_winner_ties"]:
+        lines.append(
+            f"| {item['case']} | {item['objective']} | {item['real_winner']} ↔ "
+            f"{item['sim_winner']} |"
+        )
+
+    lines.extend(
+        [
+            "",
+            "### (c) How many exact-winner successes are margin-robust?",
+            "",
+            f"Among exact winner matches, **{directional['margin_robust_success_count']}** are margin-robust (`margin >= 1%`) and "
+            f"**{directional['fragile_success_count']}** are fragile (`margin < 1%`). "
+            f"Separately, {directional['sim_tie_winner_mismatch_count']} winner-label mismatches come from exact simulator ties and sit on the decision boundary rather than being strict inversions.",
+            "",
+            "| fragile-success case | objective | real margin |",
+            "|---|---|---:|",
+        ]
+    )
+    for item in directional["fragile_successes"]:
+        lines.append(
+            f"| {item['case']} | {item['objective']} | "
+            f"{item['real_relative_margin_percent']:.1f}% |"
+        )
+
+    lines.extend(
+        [
+            "",
+            "## Cross-checks",
+            "",
+            "| check | observed | frozen expectation | result |",
+            "|---|---:|---:|---|",
+        ]
+    )
+    for check in result["cross_checks"]:
+        observed = check["observed_percent"]
+        expected = check["expected_percent"]
+        if isinstance(observed, list):
+            observed_text = ", ".join(f"{value:.1f}%" for value in observed)
+            expected_text = ", ".join(f"{value:.1f}%" for value in expected)
+        else:
+            observed_text = f"{observed:.1f}%"
+            expected_text = f"{expected:.1f}%"
+        lines.append(
+            f"| {check['name']} | {observed_text} | {expected_text} | "
+            f"{'PASS' if check['passed'] else 'FAIL'} |"
+        )
+
+    lines.extend(["", "## Data gaps", ""])
+    if result["data_gaps"]:
+        for gap in result["data_gaps"]:
+            missing = ", ".join(gap["missing_configs"]) or "insufficient paired configs"
+            lines.append(f"- {gap['case']} / {gap['objective']}: N/A because {missing}.")
+    else:
+        lines.append("No per-config sim/real pairing gaps were found in the requested surfaces.")
+
+    lines.extend(["", "## 异常", ""])
+    if result["anomalies"]:
+        lines.extend(f"- {item}" for item in result["anomalies"])
+    else:
+        lines.append("- 无。重算 winner/regret 与 frozen JSON 一致，硬性交叉核对均通过。")
+
+    lines.extend(
+        [
+            "",
+            "## Figure",
+            "",
+            "`margin-vs-residual.png` uses x = `100 × log1p(real best-vs-second relative margin)` and y = `100 ×` real-top-3 log-ratio spread. "
+            "Both axes are logarithmic because the real margins span six orders of magnitude. Green means exact winner match; red means winner mismatch. "
+            "The diagonal is the H-SCALE threshold, while failure itself is defined by regret, not by exact winner match.",
+            "",
+            "`decision-pair-axis.png` is a mechanism census, not a hypothesis test: for a strict winner reversal, `-delta_s > m_s` is algebraically equivalent to the mismatch. "
+            "The frozen surfaces also contain deterministic winner-label mismatches caused by exact simulator ties; those points lie on `-delta_s = m_s` and are not counted as strict inversions. "
+            "Color identifies the winner-deciding config axis and marker area is proportional to regret.",
+            "",
+            "## A0 vs A1 对照",
+            "",
+            "A1 repairs the Q235 Trace-PO p90 ranking error but leaves the four large Fixed-PD TPOT/E2E regrets unchanged.",
+            "",
+            "| case / objective | A0 regret | A1 regret |",
+            "|---|---:|---:|",
+        ]
+    )
+    by_key = row_index(result["rows"])
+    a0_a1_rows = (
+        ("trace-po / ttft_p90_ms", "trace-po", "ttft_p90_ms"),
+        ("fixed-pd / tpot_mean_ms", "fixed-pd", "tpot_mean_ms"),
+        ("fixed-pd / tpot_p90_ms", "fixed-pd", "tpot_p90_ms"),
+        ("fixed-pd / e2e_mean_ms", "fixed-pd", "e2e_mean_ms"),
+        ("fixed-pd / e2e_p90_ms", "fixed-pd", "e2e_p90_ms"),
+    )
+    for label, case, objective in a0_a1_rows:
+        a0 = by_key[(f"q235 A0 {case}", objective)]["regret"]
+        a1 = by_key[(f"q235 A1 {case}", objective)]["regret"]
+        lines.append(f"| {label} | {percent(a0)} | {percent(a1)} |")
+    lines.extend(
+        [
+            "",
+            "Thus Trace-PO TTFT p90 changes **21.2% → 0.3%**, whereas Fixed-PD remains **33.0% / 37.2% / 30.7% / 34.6%** in both A0 and A1.",
+            "",
+            "## 已知分量归因摘要",
+            "",
+            "### Q30 high-pressure Fixed-PD TTFT: first-scheduling wait vs execution-side TTFT",
+            "",
+            "`queue-free TTFT` is the execution-side TTFT after removing first-scheduling wait; in the frozen diagnostic, simulated TTFT is their sum (up to floating-point rounding).",
+            "",
+            "| config | sim TPOT / real | sim slots / MNS | real slots upper / MNS | first-scheduling wait | queue-free TTFT | sim TTFT | real TTFT | real waiting max |",
+            "|---|---:|---:|---:|---:|---:|---:|---:|---:|",
+        ]
+    )
+    q30 = result["known_attribution"]["q30_admission"]
+    for cell in q30["cells"]:
+        lines.append(
+            f"| {cell['config']} | {cell['sim_tpot_over_real']:.2f}x | "
+            f"{cell['sim_required_slots']:.1f}/{cell['mns']} | "
+            f"{cell['real_required_slots_upper_bound']:.1f}/{cell['mns']} | "
+            f"{cell['sim_first_scheduling_wait_ms']:.1f} ms | "
+            f"{cell['sim_queue_free_ttft_ms']:.1f} ms | "
+            f"{cell['sim_ttft_ms']:.1f} ms | {cell['real_ttft_ms']:.1f} ms | "
+            f"{cell['real_waiting_max']} |"
+        )
+    contrasts = q30["contrasts"]
+    lines.extend(
+        [
+            "",
+            "For TP4/MNS32 minus TP2/MNS64, the observed simulator contrast is "
+            f"**{contrasts['observed_sim_ttft_tp4_minus_tp2_ms']:+.1f} ms**; removing first-scheduling wait changes it to "
+            f"**{contrasts['queue_free_sim_ttft_tp4_minus_tp2_ms']:+.1f} ms**, aligned with the real contrast "
+            f"**{contrasts['real_ttft_tp4_minus_tp2_ms']:+.1f} ms**. This localizes the Q30 high-pressure TTFT reversal to admission queueing, while the upstream service-time overprediction remains unattributed in the frozen data.",
+            "",
+            "### Q235 Fixed-PD: own-composition vs exact-state contrast",
+            "",
+            "Positive TP8−TP4 means TP8 is slower and therefore agrees with the real TP4 winner.",
+            "",
+            "| config | sim own decode batch mean | real exact decode batch mean | real token-weighted iteration | exact-state matched sim | coverage |",
+            "|---|---:|---:|---:|---:|---:|",
+        ]
+    )
+    q235 = result["known_attribution"]["q235_state"]
+    for config in q235["configs"]:
+        lines.append(
+            f"| {config['config']} | {config['sim_own_decode_batch_mean']:.3f} | "
+            f"{config['real_exact_decode_batch_mean']:.3f} | "
+            f"{config['real_token_weighted_iteration_ms']:.4f} ms | "
+            f"{config['exact_state_matched_sim_ms']:.4f} ms | "
+            f"{config['exact_state_coverage'] * 100.0:.1f}% |"
+        )
+    lines.extend(
+        [
+            "",
+            "| component | own-composition TP8−TP4 | exact-state TP8−TP4 |",
+            "|---|---:|---:|",
+        ]
+    )
+    for component in q235["components"]:
+        lines.append(
+            f"| {component['component']} | "
+            f"{component['own_composition_tp8_minus_tp4_ms']:+.4f} ms | "
+            f"{component['exact_state_tp8_minus_tp4_ms']:+.4f} ms |"
+        )
+    decomposition = q235["contrast_decomposition"]
+    reference = q235["reference"]
+    lines.extend(
+        [
+            "",
+            f"The total contrast flips from **{decomposition['simulator_internal_tp8_minus_tp4_ms']:+.4f} ms** on Frontier's own composition to "
+            f"**{decomposition['exact_state_matched_tp8_minus_tp4_ms']:+.4f} ms** at exact real state, a "
+            f"**{decomposition['state_composition_shift_ms']:+.4f} ms** state-composition shift. "
+            f"The exact real iteration contrast is **{reference['exact_iteration_tp8_minus_tp4_ms']:+.4f} ms** and the frozen real TPOT contrast is "
+            f"**{reference['observed_real_tp8_minus_tp4_ms']:+.4f} ms**. This supports closed-loop state/composition drift for Q235 Fixed-PD; it does not by itself attribute every remaining conditional execution residual.",
+            "",
+        ]
+    )
+    return "\n".join(lines)
+
+
+def render_plot(rows: list[dict[str, Any]], output: Path) -> None:
+    os.environ.setdefault(
+        "MPLCONFIGDIR", "/tmp/aituner-frontier-split-rootcause-matplotlib"
+    )
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import matplotlib.pyplot as plt
+
+    usable = [
+        row
+        for row in rows
+        if row["real_relative_margin_best_vs_second"] is not None
+        and row["log_ratio_spread_real_top3"] is not None
+    ]
+    if not usable:
+        raise ValueError("no complete rows available for margin-vs-residual plot")
+
+    plt.rcParams.update(
+        {
+            "font.family": "DejaVu Sans",
+            "font.size": 8,
+            "axes.titlesize": 10,
+            "axes.labelsize": 9,
+        }
+    )
+    fig, ax = plt.subplots(figsize=(13.0, 9.0), dpi=180)
+    colors = {True: "#2a9d8f", False: "#d1495b"}
+    labels = {True: "winner match", False: "winner mismatch"}
+    for match in (True, False):
+        selected = [row for row in usable if row["winner_match"] is match]
+        ax.scatter(
+            [
+                math.log1p(row["real_relative_margin_best_vs_second"]) * 100.0
+                for row in selected
+            ],
+            [row["log_ratio_spread_real_top3"] * 100.0 for row in selected],
+            s=28,
+            color=colors[match],
+            edgecolor="white",
+            linewidth=0.4,
+            alpha=0.88,
+            label=labels[match],
+            zorder=3,
+        )
+
+    for index, row in enumerate(usable):
+        x = math.log1p(row["real_relative_margin_best_vs_second"]) * 100.0
+        y = row["log_ratio_spread_real_top3"] * 100.0
+        dx = 3 if index % 2 == 0 else -3
+        dy = 3 if (index // 2) % 2 == 0 else -5
+        ax.annotate(
+            row["case"],
+            (x, y),
+            xytext=(dx, dy),
+            textcoords="offset points",
+            ha="left" if dx > 0 else "right",
+            va="bottom" if dy > 0 else "top",
+            fontsize=4.5,
+            color="#303030",
+            alpha=0.82,
+            clip_on=True,
+            zorder=4,
+        )
+
+    max_value = max(
+        max(
+            math.log1p(row["real_relative_margin_best_vs_second"])
+            for row in usable
+        ),
+        max(row["log_ratio_spread_real_top3"] for row in usable),
+    ) * 100.0
+    min_value = min(
+        min(
+            math.log1p(row["real_relative_margin_best_vs_second"])
+            for row in usable
+        ),
+        min(row["log_ratio_spread_real_top3"] for row in usable),
+    ) * 100.0
+    lower = min_value / 5.0
+    upper = max_value * 2.0
+    ax.plot(
+        [lower, upper],
+        [lower, upper],
+        linestyle="--",
+        color="#555555",
+        linewidth=1.0,
+        label="spread = log1p(margin)",
+        zorder=2,
+    )
+    ax.set_xscale("log")
+    ax.set_yscale("log")
+    ax.set_xlim(left=lower, right=upper)
+    ax.set_ylim(bottom=lower, top=upper)
+    ax.set_xlabel("Real best-vs-second log margin: 100 × log1p(relative margin)")
+    ax.set_ylabel("Top-3 differential residual: 100 × log-ratio spread")
+    ax.set_title("Frontier selection: real margin vs config-differential residual")
+    ax.grid(True, color="#d8d8d8", linewidth=0.5, alpha=0.7, zorder=1)
+    ax.legend(frameon=False, loc="upper left")
+    fig.tight_layout()
+    output.parent.mkdir(parents=True, exist_ok=True)
+    temporary = output.with_suffix(output.suffix + ".tmp")
+    fig.savefig(
+        temporary,
+        format="png",
+        dpi=180,
+        metadata={"Software": "analyze_split_decomposition.py"},
+    )
+    plt.close(fig)
+    os.replace(temporary, output)
+
+
+def render_decision_pair_axis_plot(
+    rows: list[dict[str, Any]], output: Path
+) -> None:
+    os.environ.setdefault(
+        "MPLCONFIGDIR", "/tmp/aituner-frontier-split-rootcause-matplotlib"
+    )
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import matplotlib.pyplot as plt
+    from matplotlib.lines import Line2D
+
+    usable = [
+        row
+        for row in rows
+        if row["winner_match"] is False
+        and row["winner_pair_m_s_percent"] > 0
+        and -row["winner_pair_delta_s_percent"] > 0
+    ]
+    if not usable:
+        raise ValueError("no winner mismatches available for decision-pair-axis plot")
+
+    plt.rcParams.update(
+        {
+            "font.family": "DejaVu Sans",
+            "font.size": 8,
+            "axes.titlesize": 10,
+            "axes.labelsize": 9,
+        }
+    )
+    colors = {
+        "tp-axis": "#3572b0",
+        "mns-axis": "#e07a1f",
+        "mixed": "#7b4ab5",
+    }
+    fig, ax = plt.subplots(figsize=(11.0, 8.0), dpi=180)
+    for axis in INVERSION_AXES:
+        selected = [row for row in usable if row["winner_deciding_axis"] == axis]
+        ax.scatter(
+            [row["winner_pair_m_s_percent"] for row in selected],
+            [-row["winner_pair_delta_s_percent"] for row in selected],
+            s=[1000.0 * row["regret"] for row in selected],
+            color=colors[axis],
+            edgecolor="white",
+            linewidth=0.6,
+            alpha=0.82,
+            label=axis,
+            zorder=3,
+        )
+
+    values = [row["winner_pair_m_s_percent"] for row in usable] + [
+        -row["winner_pair_delta_s_percent"] for row in usable
+    ]
+    lower = min(values) / 1.8
+    upper = max(values) * 1.8
+    ax.plot(
+        [lower, upper],
+        [lower, upper],
+        linestyle="--",
+        color="#555555",
+        linewidth=1.0,
+        label="reversal boundary",
+        zorder=2,
+    )
+    ax.set_xscale("log")
+    ax.set_yscale("log")
+    ax.set_xlim(lower, upper)
+    ax.set_ylim(lower, upper)
+    ax.set_xlabel("Winner-pair real log margin $m_s$ (%)")
+    ax.set_ylabel("Simulator preference strength $-\\delta_s$ (%)")
+    ax.set_title("Winner-deciding pair census by config axis")
+    ax.grid(True, color="#d8d8d8", linewidth=0.5, alpha=0.7, zorder=1)
+    axis_handles = [
+        Line2D(
+            [0],
+            [0],
+            marker="o",
+            linestyle="none",
+            markerfacecolor=colors[axis],
+            markeredgecolor="white",
+            markersize=7,
+            label=axis,
+        )
+        for axis in INVERSION_AXES
+    ]
+    axis_handles.append(
+        Line2D(
+            [0],
+            [0],
+            linestyle="--",
+            color="#555555",
+            linewidth=1.0,
+            label="reversal boundary",
+        )
+    )
+    axis_legend = ax.legend(
+        handles=axis_handles, frameon=False, loc="upper left", title="deciding axis"
+    )
+    ax.add_artist(axis_legend)
+    size_handles = [
+        ax.scatter(
+            [],
+            [],
+            s=10.0 * regret_percent,
+            facecolor="none",
+            edgecolor="#555555",
+            linewidth=0.7,
+            label=f"{regret_percent}%",
+        )
+        for regret_percent in (5, 20, 50)
+    ]
+    ax.legend(
+        handles=size_handles,
+        frameon=False,
+        loc="lower right",
+        title="regret (marker area)",
+    )
+    fig.tight_layout()
+    output.parent.mkdir(parents=True, exist_ok=True)
+    temporary = output.with_suffix(output.suffix + ".tmp")
+    fig.savefig(
+        temporary,
+        format="png",
+        dpi=180,
+        metadata={"Software": "analyze_split_decomposition.py"},
+    )
+    plt.close(fig)
+    os.replace(temporary, output)
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--input-root", type=Path, default=DEFAULT_INPUT_ROOT)
+    parser.add_argument("--results-root", type=Path, default=DEFAULT_RESULTS_ROOT)
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    result = analyze(args.input_root.resolve())
+    results_root = args.results_root.resolve()
+    atomic_write(
+        results_root / "decomposition.json",
+        json.dumps(result, indent=2, sort_keys=True) + "\n",
+    )
+    atomic_write(results_root / "decomposition.md", markdown(result))
+    render_plot(result["rows"], results_root / "margin-vs-residual.png")
+    render_decision_pair_axis_plot(
+        result["rows"], results_root / "decision-pair-axis.png"
+    )
+    print(
+        json.dumps(
+            {
+                "status": "PASS" if not result["anomalies"] else "ANOMALY",
+                "rows": result["summary"]["row_count"],
+                "h_scale_counterexamples": result["summary"]["h_scale_counterexample_count"],
+                "anomalies": len(result["anomalies"]),
+            },
+            sort_keys=True,
+        )
+    )
+    if result["anomalies"]:
+        raise SystemExit("analysis anomalies found; see results/decomposition.md")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1-prov/aituner.commit b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1-prov/aituner.commit
new file mode 100644
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--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1-prov/aituner.commit
@@ -0,0 +1 @@
+10567da5238db57c29a45e09ebd40343a7d1a543
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1-prov/artifacts.sha256 b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1-prov/artifacts.sha256
new file mode 100644
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--- /dev/null
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+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial3/results/result.json"
+          ],
+          "ttft_mean_ms": 1043.6429704051557,
+          "ttft_p90_ms": 2605.180658050813
+        }
+      },
+      "sim": {
+        "tp4_ep1_mns128": {
+          "e2e_mean_ms": 698.2455408721717,
+          "e2e_p50_ms": 208.8217362068434,
+          "e2e_p90_ms": 2102.42229741975,
+          "e2e_p95_ms": 2868.6579248910534,
+          "tpot_mean_ms": null,
+          "tpot_p50_ms": null,
+          "tpot_p90_ms": null,
+          "tpot_p95_ms": null,
+          "ttft_mean_ms": 698.2455408721717,
+          "ttft_p50_ms": 208.8217362068434,
+          "ttft_p90_ms": 2102.42229741975,
+          "ttft_p95_ms": 2868.6579248910534
+        },
+        "tp4_ep1_mns64": {
+          "e2e_mean_ms": 698.0132356513792,
+          "e2e_p50_ms": 208.8217362068434,
+          "e2e_p90_ms": 2102.42229741975,
+          "e2e_p95_ms": 2868.6579248910534,
+          "tpot_mean_ms": null,
+          "tpot_p50_ms": null,
+          "tpot_p90_ms": null,
+          "tpot_p95_ms": null,
+          "ttft_mean_ms": 698.0132356513792,
+          "ttft_p50_ms": 208.8217362068434,
+          "ttft_p90_ms": 2102.42229741975,
+          "ttft_p95_ms": 2868.6579248910534
+        },
+        "tp8_ep8_mns128": {
+          "e2e_mean_ms": 487.42679595918156,
+          "e2e_p50_ms": 253.39288448911512,
+          "e2e_p90_ms": 1264.1466431938486,
+          "e2e_p95_ms": 1656.1837032209396,
+          "tpot_mean_ms": null,
+          "tpot_p50_ms": null,
+          "tpot_p90_ms": null,
+          "tpot_p95_ms": null,
+          "ttft_mean_ms": 487.42679595918156,
+          "ttft_p50_ms": 253.39288448911512,
+          "ttft_p90_ms": 1264.1466431938486,
+          "ttft_p95_ms": 1656.1837032209396
+        },
+        "tp8_ep8_mns64": {
+          "e2e_mean_ms": 487.3699604726311,
+          "e2e_p50_ms": 253.41330144894124,
+          "e2e_p90_ms": 1264.1466431938486,
+          "e2e_p95_ms": 1656.1837032209396,
+          "tpot_mean_ms": null,
+          "tpot_p50_ms": null,
+          "tpot_p90_ms": null,
+          "tpot_p95_ms": null,
+          "ttft_mean_ms": 487.3699604726311,
+          "ttft_p50_ms": 253.41330144894124,
+          "ttft_p90_ms": 1264.1466431938486,
+          "ttft_p95_ms": 1656.1837032209396
+        }
+      }
+    }
+  },
+  "real_root": "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1",
+  "schema": "qwen235-v020-simulator-real-comparison-v1",
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen235-collective-profile-ablation-20260719-r1"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1/comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1/comparison.md
new file mode 100644
index 0000000..fc3325a
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-ablation-a1/comparison.md
@@ -0,0 +1,24 @@
+# Qwen235 vLLM 0.20 Frontier vs real
+
+| case | metric | Frontier winner | real winner | match | regret | pair agreement |
+|---|---|---|---|---:|---:|---:|
+| fixed-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 100.0% |
+| fixed-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.2% | 100.0% |
+| fixed-pd | tpot_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 33.0% | 0.0% |
+| fixed-pd | tpot_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 37.2% | 0.0% |
+| fixed-pd | e2e_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 30.7% | 0.0% |
+| fixed-pd | e2e_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 34.6% | 0.0% |
+| fixed-po | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 100.0% |
+| fixed-po | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 100.0% |
+| fixed-po | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 100.0% |
+| fixed-po | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 100.0% |
+| trace-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 66.7% |
+| trace-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 66.7% |
+| trace-pd | tpot_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | yes | 0.0% | 66.7% |
+| trace-pd | tpot_p90_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | yes | 0.0% | 66.7% |
+| trace-pd | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.6% | 83.3% |
+| trace-pd | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 6.2% | 83.3% |
+| trace-po | ttft_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns128 | no | 1.4% | 66.7% |
+| trace-po | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.3% | 100.0% |
+| trace-po | e2e_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns128 | no | 1.4% | 66.7% |
+| trace-po | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.3% | 100.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.json
new file mode 100644
index 0000000..fb5ede7
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.json
@@ -0,0 +1,952 @@
+{
+  "cases": {
+    "fixed-pd": {
+      "comparison": {
+        "e2e_mean_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp4_ep1_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.3067524317507717,
+          "sim_winner": "tp8_ep8_mns128",
+          "winner_match": false
+        },
+        "e2e_p90_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp4_ep1_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.3456375801249614,
+          "sim_winner": "tp8_ep8_mns128",
+          "winner_match": false
+        },
+        "tpot_mean_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp4_ep1_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.33025510615656906,
+          "sim_winner": "tp8_ep8_mns128",
+          "winner_match": false
+        },
+        "tpot_p90_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp4_ep1_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.37228890038064755,
+          "sim_winner": "tp8_ep8_mns128",
+          "winner_match": false
+        },
+        "ttft_mean_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp8_ep8_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.04237011756982145,
+          "sim_winner": "tp4_ep1_mns128",
+          "winner_match": false
+        },
+        "ttft_p90_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 1.0,
+          "real_winner": "tp8_ep8_mns64",
+          "reversals": [],
+          "selected_real_regret": 0.002088257708717345,
+          "sim_winner": "tp8_ep8_mns128",
+          "winner_match": false
+        }
+      },
+      "real": {
+        "tp4_ep1_mns128": {
+          "e2e_mean_ms": 5729.31677040774,
+          "e2e_p90_ms": 5871.668232022785,
+          "request_samples": 387,
+          "tpot_mean_ms": 21.044200828709027,
+          "tpot_p90_ms": 21.59612646244247,
+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns128/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns128/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns128/trial3/results/result.json"
+          ],
+          "ttft_mean_ms": 363.00995954954925,
+          "ttft_p90_ms": 369.09779999405146
+        },
+        "tp4_ep1_mns64": {
+          "e2e_mean_ms": 5769.497427325912,
+          "e2e_p90_ms": 5888.945628073998,
+          "request_samples": 387,
+          "tpot_mean_ms": 21.187139407074238,
+          "tpot_p90_ms": 21.653656356547977,
+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns64/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns64/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp4_ep1_mns64/trial3/results/result.json"
+          ],
+          "ttft_mean_ms": 366.7432916322386,
+          "ttft_p90_ms": 369.99153497163206
+        },
+        "tp8_ep8_mns128": {
+          "e2e_mean_ms": 7486.7986220007915,
+          "e2e_p90_ms": 7901.13743103575,
+          "request_samples": 387,
+          "tpot_mean_ms": 27.994155607374484,
+          "tpot_p90_ms": 29.63612463562658,
+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns128/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns128/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns128/trial3/results/result.json"
+          ],
+          "ttft_mean_ms": 348.25438050341427,
+          "ttft_p90_ms": 365.8816539682448
+        },
+        "tp8_ep8_mns64": {
+          "e2e_mean_ms": 7484.121415326708,
+          "e2e_p90_ms": 7908.651847974397,
+          "request_samples": 387,
+          "tpot_mean_ms": 27.978544004773987,
+          "tpot_p90_ms": 29.650389521346227,
+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns64/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns64/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/fixed-pd/real/tp8_ep8_mns64/trial3/results/result.json"
+          ],
+          "ttft_mean_ms": 349.5577253122725,
+          "ttft_p90_ms": 365.11919100303203
+        }
+      },
+      "sim": {
+        "tp4_ep1_mns128": {
+          "e2e_mean_ms": 22734.095381397616,
+          "e2e_p50_ms": 23441.595611495926,
+          "e2e_p90_ms": 23484.306701188103,
+          "e2e_p95_ms": 23489.511452611594,
+          "tpot_mean_ms": 87.77349881741111,
+          "tpot_p50_ms": 90.6067822139126,
+          "tpot_p90_ms": 90.60678221391389,
+          "tpot_p95_ms": 90.60678221391389,
+          "ttft_mean_ms": 351.8531829577845,
+          "ttft_p50_ms": 351.44748294051453,
+          "ttft_p90_ms": 381.14669406792245,
+          "ttft_p95_ms": 385.3185272085611
+        },
+        "tp4_ep1_mns64": {
+          "e2e_mean_ms": 22734.095381397616,
+          "e2e_p50_ms": 23441.595611495926,
+          "e2e_p90_ms": 23484.306701188103,
+          "e2e_p95_ms": 23489.511452611594,
+          "tpot_mean_ms": 87.77349881741111,
+          "tpot_p50_ms": 90.6067822139126,
+          "tpot_p90_ms": 90.60678221391389,
+          "tpot_p95_ms": 90.60678221391389,
+          "ttft_mean_ms": 351.8531829577845,
+          "ttft_p50_ms": 351.44748294051453,
+          "ttft_p90_ms": 381.14669406792245,
+          "ttft_p95_ms": 385.3185272085611
+        },
+        "tp8_ep8_mns128": {
+          "e2e_mean_ms": 16059.899811799207,
+          "e2e_p50_ms": 17256.45308650381,
+          "e2e_p90_ms": 17280.553823012277,
+          "e2e_p95_ms": 17282.746891876577,
+          "tpot_mean_ms": 61.58781555229474,
+          "tpot_p50_ms": 66.32324900760649,
+          "tpot_p90_ms": 66.3246446898248,
+          "tpot_p95_ms": 66.3246446898248,
+          "ttft_mean_ms": 355.00684596404665,
+          "ttft_p50_ms": 355.16695480338,
+          "ttft_p90_ms": 368.8582878708644,
+          "ttft_p95_ms": 370.503089520021
+        },
+        "tp8_ep8_mns64": {
+          "e2e_mean_ms": 16059.899811799207,
+          "e2e_p50_ms": 17256.45308650381,
+          "e2e_p90_ms": 17280.553823012277,
+          "e2e_p95_ms": 17282.746891876577,
+          "tpot_mean_ms": 61.58781555229474,
+          "tpot_p50_ms": 66.32324900760649,
+          "tpot_p90_ms": 66.3246446898248,
+          "tpot_p95_ms": 66.3246446898248,
+          "ttft_mean_ms": 355.00684596404665,
+          "ttft_p50_ms": 355.16695480338,
+          "ttft_p90_ms": 368.8582878708644,
+          "ttft_p95_ms": 370.503089520021
+        }
+      }
+    },
+    "fixed-po": {
+      "comparison": {
+        "e2e_mean_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp8_ep8_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.05873813644442971,
+          "sim_winner": "tp4_ep1_mns128",
+          "winner_match": false
+        },
+        "e2e_p90_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp8_ep8_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.016760786592592503,
+          "sim_winner": "tp4_ep1_mns128",
+          "winner_match": false
+        },
+        "ttft_mean_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp8_ep8_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
+            ]
+          ],
+          "selected_real_regret": 0.058746722254088946,
+          "sim_winner": "tp4_ep1_mns128",
+          "winner_match": false
+        },
+        "ttft_p90_ms": {
+          "informative_pairs": 4,
+          "pair_direction_agreement": 0.0,
+          "real_winner": "tp8_ep8_mns128",
+          "reversals": [
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns64",
+              "tp8_ep8_mns128"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns64"
+            ],
+            [
+              "tp4_ep1_mns128",
+              "tp8_ep8_mns128"
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+          "tpot_p90_ms": null,
+          "trials": [
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp4_ep1_mns64/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp4_ep1_mns64/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp4_ep1_mns64/trial3/results/result.json"
+          ],
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+          "tpot_p90_ms": null,
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+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns128/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns128/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns128/trial3/results/result.json"
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+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial1/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial2/results/result.json",
+            "/home/admin/cpfs/wjh/aituner/qwen235-v020-fourcase-20260719-r1/real/trace-po/real/tp8_ep8_mns64/trial3/results/result.json"
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+          "ttft_p90_ms": 2341.4108333476474,
+          "ttft_p95_ms": 2898.493085937801
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+      }
+    }
+  },
+  "schema": "qwen235-v020-simulator-real-comparison-v1"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.md
new file mode 100644
index 0000000..1e05500
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-fourcase-a0/comparison.md
@@ -0,0 +1,24 @@
+# Qwen235 vLLM 0.20 Frontier vs real
+
+| case | metric | Frontier winner | real winner | match | regret | pair agreement |
+|---|---|---|---|---:|---:|---:|
+| fixed-pd | ttft_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | no | 4.2% | 0.0% |
+| fixed-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.2% | 100.0% |
+| fixed-pd | tpot_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 33.0% | 0.0% |
+| fixed-pd | tpot_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 37.2% | 0.0% |
+| fixed-pd | e2e_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 30.7% | 0.0% |
+| fixed-pd | e2e_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | no | 34.6% | 0.0% |
+| fixed-po | ttft_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | no | 5.9% | 0.0% |
+| fixed-po | ttft_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | no | 1.7% | 0.0% |
+| fixed-po | e2e_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | no | 5.9% | 0.0% |
+| fixed-po | e2e_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | no | 1.7% | 0.0% |
+| trace-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 66.7% |
+| trace-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | yes | 0.0% | 66.7% |
+| trace-pd | tpot_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | yes | 0.0% | 66.7% |
+| trace-pd | tpot_p90_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | yes | 0.0% | 66.7% |
+| trace-pd | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 0.6% | 83.3% |
+| trace-pd | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | no | 6.2% | 66.7% |
+| trace-po | ttft_mean_ms | tp4_ep1_mns64 | tp8_ep8_mns128 | no | 7.0% | 0.0% |
+| trace-po | ttft_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns64 | no | 21.2% | 0.0% |
+| trace-po | e2e_mean_ms | tp4_ep1_mns64 | tp8_ep8_mns128 | no | 7.0% | 0.0% |
+| trace-po | e2e_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns64 | no | 21.2% | 0.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.json
new file mode 100644
index 0000000..0a6061f
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.json
@@ -0,0 +1,1587 @@
+{
+  "contrast_decomposition": {
+    "exact_state_matched_tp8_minus_tp4_ms": 10.902788634037428,
+    "residual_vs_exact_iteration_ms": 1.7850640558340523,
+    "residual_vs_frozen_real_tpot_ms": 3.9527886340374287,
+    "simulator_internal_tp8_minus_tp4_ms": -20.06625468177714,
+    "state_composition_shift_ms": 30.969043315814567
+  },
+  "exact_state_matched": {
+    "configs": {
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+          "dense_mlp_compute": 0.20457670875208997,
+          "ep_communication": 0.0,
+          "moe_compute": 11.818199308522054,
+          "moe_routing": 1.3660523028556315,
+          "pipeline_communication": 0.0,
+          "runtime_overhead": 0.0,
+          "total": 34.25746674314369,
+          "tp_dp_communication": 13.007265841334672
+        },
+        "coverage": 1.0,
+        "supported_decode_tokens": 32895,
+        "total_decode_tokens": 32895,
+        "unsupported": {}
+      },
+      "tp8_ep8_mns64": {
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+          "dense_mlp_compute": 0.17382455581232167,
+          "ep_communication": 6.535508227248577,
+          "moe_compute": 9.840752983018692,
+          "moe_routing": 1.5044582710663996,
+          "pipeline_communication": 0.0,
+          "runtime_overhead": 0.0,
+          "total": 45.160255377181116,
+          "tp_dp_communication": 6.535508227248577
+        },
+        "coverage": 1.0,
+        "supported_decode_tokens": 32895,
+        "total_decode_tokens": 32895,
+        "unsupported": {}
+      }
+    },
+    "method": "decode-token-weighted exact (context_tokens, generation_requests) composition from vLLM iteration details; no interpolation",
+    "tp8_minus_tp4_ms": {
+      "attention": -2.130420408899373,
+      "dense_mlp_compute": -0.030752152939768296,
+      "ep_communication": 6.535508227248577,
+      "moe_compute": -1.9774463255033616,
+      "moe_routing": 0.13840596821076812,
+      "pipeline_communication": 0.0,
+      "runtime_overhead": 0.0,
+      "total": 10.902788634037428,
+      "tp_dp_communication": -6.471757614086094
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+  },
+  "proxy_matched": {
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+        "coverage": 1.0,
+        "supported_samples": 45,
+        "total_samples": 45,
+        "unsupported": {}
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+      "tp8_ep8_mns64": {
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+        "supported_samples": 21,
+        "total_samples": 21,
+        "unsupported": {}
+      }
+    },
+    "method": "exact batch-size lookup; each simulator config is reweighted to its own frozen-real steady Running histogram; no interpolation",
+    "tp8_minus_tp4_ms": {
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+      "runtime_overhead": 0.0,
+      "total": -8.551708299286375,
+      "tp_dp_communication": -5.40098776531321
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+  },
+  "real": {
+    "tp4_ep1_mns64": {
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+      "proxy_only": true,
+      "steady_rule": "prompt throughput >= 95% of 3276.8 tokens/s",
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+          "post_attention_layernorm": 1738
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+        "serialized_component_sum_over_stage_span": {
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+          "n": 1738
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+        "trace_batches": 1738,
+        "trace_path": "/home/admin/cpfs/wjh/aituner/qwen235-fixed-pd-state-diagnosis-20260719-r1/frontier-optrace/tp8_ep8_mns64/frontier_metrics/qwen3_235b_a22b/online_serving/qwen235_fixed_pd_state_tp8_ep8_mns64/op_traces.jsonl"
+      }
+    }
+  },
+  "simulator_internal_all_step_tp8_minus_tp4_ms": {
+    "attention": -7.461942625219683,
+    "dense_mlp_compute": -0.12314137296116046,
+    "ep_communication": 6.235402017662346,
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+    "moe_routing": -0.2861742505642797,
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+    "runtime_overhead": 0.0,
+    "total": -20.06625468177714,
+    "tp_dp_communication": -6.571107062807271
+  },
+  "status": "PASS",
+  "verdict": "Exact real state composition flips Frontier to the correct TP4 winner; the ranking error is caused by closed-loop state/composition mismatch, not a conditional stage reversal."
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.md
new file mode 100644
index 0000000..70092bd
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-exact.md
@@ -0,0 +1,54 @@
+# Qwen235 Fixed-PD state diagnosis
+
+**Verdict:** Exact real state composition flips Frontier to the correct TP4 winner; the ranking error is caused by closed-loop state/composition mismatch, not a conditional stage reversal.
+
+| Config | Real Running proxy mean | Sim decode batch mean | Proxy coverage |
+|---|---:|---:|---:|
+| tp4_ep1_mns64 | 4.667 | 13.537 | 100.0% |
+| tp8_ep8_mns64 | 12.238 | 18.938 | 100.0% |
+
+| Config | Real exact decode batch mean | Real token-weighted iteration ms | Matched simulator ms | Exact coverage |
+|---|---:|---:|---:|---:|
+| tp4_ep1_mns64 | 3.890 | 18.4710 | 34.2575 | 100.0% |
+| tp8_ep8_mns64 | 10.921 | 27.5887 | 45.1603 | 100.0% |
+
+## Frontier internal component contrast over its own executed composition
+
+Decode-token-weighted over both pure-decode and mixed prefill/decode steps.
+
+| Component | TP8 - TP4 (ms/decoded token step) |
+|---|---:|
+| moe_compute | -32.4544 |
+| total | -20.0663 |
+| attention | -7.4619 |
+| tp_dp_communication | -6.5711 |
+| ep_communication | +6.2354 |
+| moe_routing | -0.2862 |
+| dense_mlp_compute | -0.1231 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Frontier component contrast at exact real token composition
+
+Positive means TP8 slower; negative means Frontier gives TP8 an advantage.
+
+| Component | TP8 - TP4 (ms/step) |
+|---|---:|
+| total | +10.9028 |
+| ep_communication | +6.5355 |
+| tp_dp_communication | -6.4718 |
+| attention | -2.1304 |
+| moe_compute | -1.9774 |
+| moe_routing | +0.1384 |
+| dense_mlp_compute | -0.0308 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Interpretation boundary
+
+- Real observed TPOT contrast: +6.9500 ms/token.
+- Real exact-iteration contrast: +9.1177 ms/decode-token-weighted step.
+- vLLM 10-second Running is active requests, not per-iteration decode batch; context lengths and graph buckets are unavailable in frozen logs.
+- Frontier state outputs have no direct graph bucket/padding/launch-overhead field; graph effects remain folded into predictors.
+- For TP8 shared-domain sync, total is ledger stage_end-start (critical path); op categories are serialized work estimates and are not additive because overlap and lane-summed wait diagnostics are represented separately.
+- Component deltas identify where Frontier creates its own TP8 advantage; without real per-stage measurements they are not yet root-cause proof.
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.json
new file mode 100644
index 0000000..00dc957
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.json
@@ -0,0 +1,1405 @@
+{
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+  "verdict": "State-composition mismatch is insufficient: after reweighting Frontier to measured real decode composition, it still predicts TP8 faster."
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.md
new file mode 100644
index 0000000..a93d3bc
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis-optrace.md
@@ -0,0 +1,48 @@
+# Qwen235 Fixed-PD state diagnosis
+
+**Verdict:** State-composition mismatch is insufficient: after reweighting Frontier to measured real decode composition, it still predicts TP8 faster.
+
+| Config | Real Running proxy mean | Sim decode batch mean | Proxy coverage |
+|---|---:|---:|---:|
+| tp4_ep1_mns64 | 4.667 | 13.537 | 100.0% |
+| tp8_ep8_mns64 | 12.238 | 18.938 | 100.0% |
+
+## Frontier internal component contrast over its own executed composition
+
+Decode-token-weighted over both pure-decode and mixed prefill/decode steps.
+
+| Component | TP8 - TP4 (ms/decoded token step) |
+|---|---:|
+| moe_compute | -32.4544 |
+| total | -20.0663 |
+| attention | -7.4619 |
+| tp_dp_communication | -6.5711 |
+| ep_communication | +6.2354 |
+| moe_routing | -0.2862 |
+| dense_mlp_compute | -0.1231 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Frontier internal component contrast at real Running proxy
+
+Positive means TP8 slower; negative means Frontier gives TP8 an advantage.
+
+| Component | TP8 - TP4 (ms/step) |
+|---|---:|
+| moe_compute | -16.0581 |
+| total | -8.5517 |
+| ep_communication | +6.8248 |
+| tp_dp_communication | -5.4010 |
+| moe_routing | +0.3109 |
+| attention | -0.2407 |
+| dense_mlp_compute | +0.0018 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Interpretation boundary
+
+- Real observed TPOT contrast: +6.9500 ms/token.
+- vLLM 10-second Running is active requests, not per-iteration decode batch; context lengths and graph buckets are unavailable in frozen logs.
+- Frontier state outputs have no direct graph bucket/padding/launch-overhead field; graph effects remain folded into predictors.
+- For TP8 shared-domain sync, total is ledger stage_end-start (critical path); op categories are serialized work estimates and are not additive because overlap and lane-summed wait diagnostics are represented separately.
+- Component deltas identify where Frontier creates its own TP8 advantage; without real per-stage measurements they are not yet root-cause proof.
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.json
new file mode 100644
index 0000000..579aa9c
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.json
@@ -0,0 +1,1361 @@
+{
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+      "stage_rows": 1738
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+  },
+  "simulator_internal_all_step_tp8_minus_tp4_ms": {
+    "attention": -13.695027512244868,
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+  "status": "PASS",
+  "verdict": "Active-batch-count mismatch alone is insufficient: after exact reweighting to each config's real Running histogram, Frontier still predicts TP8 faster."
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.md
new file mode 100644
index 0000000..381adb4
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q235-state-diag/state-diagnosis.md
@@ -0,0 +1,47 @@
+# Qwen235 Fixed-PD state diagnosis
+
+**Verdict:** Active-batch-count mismatch alone is insufficient: after exact reweighting to each config's real Running histogram, Frontier still predicts TP8 faster.
+
+| Config | Real Running proxy mean | Sim decode batch mean | Proxy coverage |
+|---|---:|---:|---:|
+| tp4_ep1_mns64 | 4.667 | 13.537 | 100.0% |
+| tp8_ep8_mns64 | 12.238 | 18.938 | 100.0% |
+
+## Frontier internal component contrast over its own executed composition
+
+Decode-token-weighted over both pure-decode and mixed prefill/decode steps.
+
+| Component | TP8 - TP4 (ms/decoded token step) |
+|---|---:|
+| total | -73.6733 |
+| moe_compute | -45.2710 |
+| attention | -13.6950 |
+| tp_dp_communication | -12.7244 |
+| moe_routing | -1.7759 |
+| dense_mlp_compute | -0.2890 |
+| ep_communication | +0.0821 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Frontier internal component contrast at real Running proxy
+
+Positive means TP8 slower; negative means Frontier gives TP8 an advantage.
+
+| Component | TP8 - TP4 (ms/step) |
+|---|---:|
+| total | -46.0760 |
+| moe_compute | -26.3387 |
+| tp_dp_communication | -12.1532 |
+| attention | -6.2393 |
+| moe_routing | -1.2405 |
+| dense_mlp_compute | -0.1769 |
+| ep_communication | +0.0726 |
+| pipeline_communication | +0.0000 |
+| runtime_overhead | +0.0000 |
+
+## Interpretation boundary
+
+- Real observed TPOT contrast: +6.9500 ms/token.
+- vLLM 10-second Running is active requests, not per-iteration decode batch; context lengths and graph buckets are unavailable in frozen logs.
+- Frontier ledger exposes additive execution components but no direct graph bucket/padding/launch-overhead field; graph effects remain folded into predictors.
+- Component deltas identify where Frontier creates its own TP8 advantage; without real per-stage measurements they are not yet root-cause proof.
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.json
new file mode 100644
index 0000000..b81ebf0
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.json
@@ -0,0 +1,173 @@
+{
+  "boundary": "This identifies where the selection error is created, but the frozen real logs do not attribute service-time overprediction to one operator.",
+  "cells": {
+    "tp2_mns64": {
+      "arrival_rate_requests_per_s": 2.25,
+      "mns": 64,
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+          "running_mean": 7.257142857142857,
+          "samples": 35,
+          "waiting_max": 0,
+          "waiting_mean": 0.0
+        },
+        "required_slots_upper_bound": 7.548483722821714,
+        "slot_margin_lower_bound": 56.451516277178285,
+        "tpot_ms": 12.393283087182931,
+        "ttft_ms": 194.56193759030603
+      },
+      "simulator": {
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+        "queue_free_ttft_ms": 191.02937373774816,
+        "request_execution_ms": 25761.91467886552,
+        "required_slots": 57.96430802744742,
+        "slot_margin": 6.035691972552577,
+        "tpot_ms": 100.27798158873513,
+        "ttft_ms": 229.2526648211283,
+        "ttft_queue_fraction": 0.16672997503956338
+      },
+      "tp": 2,
+      "tpot_overprediction_ratio": 8.091316956395687
+    },
+    "tp4_mns16": {
+      "arrival_rate_requests_per_s": 4.5,
+      "mns": 16,
+      "real": {
+        "e2e_ms": 3252.7993474094965,
+        "periodic_queue": {
+          "running_max": 16,
+          "running_mean": 15.166666666666666,
+          "samples": 18,
+          "waiting_max": 0,
+          "waiting_mean": 0.0
+        },
+        "required_slots_upper_bound": 14.637597063342735,
+        "slot_margin_lower_bound": 1.362402936657265,
+        "tpot_ms": 12.267737219892378,
+        "ttft_ms": 124.49453797538061
+      },
+      "simulator": {
+        "first_scheduling_delay_ms": 64906.25631809643,
+        "queue_free_ttft_ms": 134.74066995065758,
+        "request_execution_ms": 12108.627705569606,
+        "required_slots": 54.488824675063235,
+        "slot_margin": -38.488824675063235,
+        "tpot_ms": 46.95641974752248,
+        "ttft_ms": 65040.99698804708,
+        "ttft_queue_fraction": 0.9979283732385681
+      },
+      "tp": 4,
+      "tpot_overprediction_ratio": 3.8276349505907024
+    },
+    "tp4_mns32": {
+      "arrival_rate_requests_per_s": 4.5,
+      "mns": 32,
+      "real": {
+        "e2e_ms": 3227.015463910283,
+        "periodic_queue": {
+          "running_max": 16,
+          "running_mean": 14.944444444444445,
+          "samples": 18,
+          "waiting_max": 0,
+          "waiting_mean": 0.0
+        },
+        "required_slots_upper_bound": 14.521569587596273,
+        "slot_margin_lower_bound": 17.478430412403725,
+        "tpot_ms": 12.171863019540417,
+        "ttft_ms": 123.15859724408143
+      },
+      "simulator": {
+        "first_scheduling_delay_ms": 27180.676177927482,
+        "queue_free_ttft_ms": 135.62147333612225,
+        "request_execution_ms": 14643.080360640608,
+        "required_slots": 65.89386162288272,
+        "slot_margin": -33.893861622882724,
+        "tpot_ms": 56.89199563649036,
+        "ttft_ms": 27316.2976512636,
+        "ttft_queue_fraction": 0.9950351444010626
+      },
+      "tp": 4,
+      "tpot_overprediction_ratio": 4.6740581573385525
+    },
+    "tp4_mns64": {
+      "arrival_rate_requests_per_s": 4.5,
+      "mns": 64,
+      "real": {
+        "e2e_ms": 3258.202659738964,
+        "periodic_queue": {
+          "running_max": 17,
+          "running_mean": 14.833333333333334,
+          "samples": 18,
+          "waiting_max": 0,
+          "waiting_mean": 0.0
+        },
+        "required_slots_upper_bound": 14.661911968825338,
+        "slot_margin_lower_bound": 49.338088031174664,
+        "tpot_ms": 12.29409478300949,
+        "ttft_ms": 123.17715882596677
+      },
+      "simulator": {
+        "first_scheduling_delay_ms": 6367.273779218055,
+        "queue_free_ttft_ms": 136.7304324624105,
+        "request_execution_ms": 17736.957363112386,
+        "required_slots": 79.81630813400574,
+        "slot_margin": -15.816308134005737,
+        "tpot_ms": 69.02049776725552,
+        "ttft_ms": 6504.004211680465,
+        "ttft_queue_fraction": 0.9789774993969319
+      },
+      "tp": 4,
+      "tpot_overprediction_ratio": 5.614117914776633
+    }
+  },
+  "contrasts": {
+    "observed_sim_ttft_tp4_minus_tp2_ms": 27087.044986442474,
+    "queue_free_sim_ttft_tp4_minus_tp2_ms": -55.40790040162591,
+    "real_ttft_tp4_minus_tp2_ms": -71.4033403462246
+  },
+  "schema": "qwen30-fixed-pd-ttft-admission-diagnosis-v1",
+  "selection": {
+    "agreement": 0.5909090909090909,
+    "concordant_pairs": 39,
+    "discordant_pairs": 27,
+    "informative_pairs": 66,
+    "real_ranking": [
+      "tp4_mns32",
+      "tp4_mns64",
+      "tp4_mns16",
+      "tp2_mns64",
+      "tp2_mns8",
+      "tp2_mns32",
+      "tp2_mns16",
+      "tp1_mns8",
+      "tp1_mns32",
+      "tp1_mns16",
+      "tp1_mns64",
+      "tp4_mns8"
+    ],
+    "real_winner": "tp4_mns32",
+    "selected_config_real_regret": 0.5797674051508896,
+    "sim_ranking": [
+      "tp2_mns64",
+      "tp1_mns64",
+      "tp4_mns64",
+      "tp1_mns32",
+      "tp2_mns32",
+      "tp4_mns32",
+      "tp4_mns16",
+      "tp2_mns16",
+      "tp1_mns16",
+      "tp4_mns8",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "sim_winner": "tp2_mns64",
+    "tied_pairs": 0,
+    "winner_match": false
+  },
+  "status": "PASS",
+  "verdict": "Frontier overpredicts decode service time, so TP4's higher global arrival rate crosses the MNS admission cap only in simulation. The resulting first-scheduling queue reverses the TP topology ranking; without that queue Frontier itself predicts TP4 faster than TP2, matching real hardware.",
+  "workload": "Qwen3-30B Fixed-PD 4096->256 at 1.125 req/s/GPU"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.md
new file mode 100644
index 0000000..dd90030
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-admission-diag/result.md
@@ -0,0 +1,18 @@
+# Qwen30 Fixed-PD TTFT admission diagnosis
+
+**Verdict:** Frontier overpredicts decode service time, so TP4's higher global arrival rate crosses the MNS admission cap only in simulation. The resulting first-scheduling queue reverses the TP topology ranking; without that queue Frontier itself predicts TP4 faster than TP2, matching real hardware.
+
+| Config | Sim TPOT / real | Sim required slots / MNS | Real slots upper bound / MNS | Sim first-schedule wait | Real waiting max |
+|---|---:|---:|---:|---:|---:|
+| tp2_mns64 | 8.09x | 58.0/64 | 7.5/64 | 38.2 ms | 0 |
+| tp4_mns16 | 3.83x | 54.5/16 | 14.6/16 | 64906.3 ms | 0 |
+| tp4_mns32 | 4.67x | 65.9/32 | 14.5/32 | 27180.7 ms | 0 |
+| tp4_mns64 | 5.61x | 79.8/64 | 14.7/64 | 6367.3 ms | 0 |
+
+## TP4/MNS32 minus TP2/MNS64 TTFT
+
+- Observed Frontier: +27087.0 ms.
+- Frontier without first-scheduling queue: -55.4 ms.
+- Real hardware: -71.4 ms.
+
+**Boundary:** This identifies where the selection error is created, but the frozen real logs do not attribute service-time overprediction to one operator.
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/analysis-launch.log b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/analysis-launch.log
new file mode 100644
index 0000000..2614c49
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/analysis-launch.log
@@ -0,0 +1,2 @@
+Q30_ANALYSIS_ECHO source_real=/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6 source_sim=/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim cases=trace-po,fixed-pd,fixed-po requests=129 configs=12 trials=3 metrics=mean,p90(TTFT,TPOT-if-OSL-gt-1,E2E) gpu_cost=0 output=/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/analysis-r6
+Q30_ANALYSIS_COMPLETE
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.json
new file mode 100644
index 0000000..dbad285
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.json
@@ -0,0 +1,453 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "tpot_ms",
+    "e2e_ms"
+  ],
+  "cells": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2624.2011811364387,
+          "p90": 2624.2011811379484
+        },
+        "tpot_ms": {
+          "mean": 19.350639886513438,
+          "p90": 19.3506398865253
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp1_mns16/tp1/result.json"
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2624.2011811364387,
+          "p90": 2624.2011811379484
+        },
+        "tpot_ms": {
+          "mean": 19.350639886513438,
+          "p90": 19.3506398865253
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp1_mns32/tp1/result.json"
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2624.2011811364387,
+          "p90": 2624.2011811379484
+        },
+        "tpot_ms": {
+          "mean": 19.350639886513438,
+          "p90": 19.3506398865253
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp1_mns64/tp1/result.json"
+    },
+    "tp1_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2624.2011811364387,
+          "p90": 2624.2011811379484
+        },
+        "tpot_ms": {
+          "mean": 19.350639886513438,
+          "p90": 19.3506398865253
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp1_mns8/tp1/result.json"
+    },
+    "tp2_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2808.3844446026824,
+          "p90": 2817.9486849812747
+        },
+        "tpot_ms": {
+          "mean": 21.06177881019329,
+          "p90": 21.09350467849898
+        },
+        "ttft_ms": {
+          "mean": 133.53853570813533,
+          "p90": 142.1523942165379
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp2_mns16/tp2/result.json"
+    },
+    "tp2_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2808.3844446026824,
+          "p90": 2817.9486849812747
+        },
+        "tpot_ms": {
+          "mean": 21.06177881019329,
+          "p90": 21.09350467849898
+        },
+        "ttft_ms": {
+          "mean": 133.53853570813533,
+          "p90": 142.1523942165379
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp2_mns32/tp2/result.json"
+    },
+    "tp2_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2808.3844446026824,
+          "p90": 2817.9486849812747
+        },
+        "tpot_ms": {
+          "mean": 21.06177881019329,
+          "p90": 21.09350467849898
+        },
+        "ttft_ms": {
+          "mean": 133.53853570813533,
+          "p90": 142.1523942165379
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp2_mns64/tp2/result.json"
+    },
+    "tp2_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 2808.3844446026824,
+          "p90": 2817.9486849812747
+        },
+        "tpot_ms": {
+          "mean": 21.06177881019329,
+          "p90": 21.09350467849898
+        },
+        "ttft_ms": {
+          "mean": 133.53853570813533,
+          "p90": 142.1523942165379
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp2_mns8/tp2/result.json"
+    },
+    "tp4_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 3752.684495467103,
+          "p90": 3794.6349827560653
+        },
+        "tpot_ms": {
+          "mean": 28.70502970984996,
+          "p90": 28.949734665706984
+        },
+        "ttft_ms": {
+          "mean": 107.14572231615826,
+          "p90": 118.03470639992497
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp4_mns16/tp4/result.json"
+    },
+    "tp4_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 3752.684495467103,
+          "p90": 3794.6349827560653
+        },
+        "tpot_ms": {
+          "mean": 28.70502970984996,
+          "p90": 28.949734665706984
+        },
+        "ttft_ms": {
+          "mean": 107.14572231615826,
+          "p90": 118.03470639992497
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp4_mns32/tp4/result.json"
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 3752.684495467103,
+          "p90": 3794.6349827560653
+        },
+        "tpot_ms": {
+          "mean": 28.70502970984996,
+          "p90": 28.949734665706984
+        },
+        "ttft_ms": {
+          "mean": 107.14572231615826,
+          "p90": 118.03470639992497
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp4_mns64/tp4/result.json"
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 3752.684495467103,
+          "p90": 3794.6349827560653
+        },
+        "tpot_ms": {
+          "mean": 28.70502970984996,
+          "p90": 28.949734665706984
+        },
+        "ttft_ms": {
+          "mean": 107.14572231615826,
+          "p90": 118.03470639992497
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd/runs/tp4_mns8/tp4/result.json"
+    }
+  },
+  "prefill_only": false,
+  "real_audit": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/analysis-r6/fixed-pd-real-audit.json",
+  "schema": "qwen30-latency-case-frontier-real-comparison-v1",
+  "selection": {
+    "e2e_ms:mean": {
+      "agreement": 0.0,
+      "concordant_pairs": 0,
+      "discordant_pairs": 48,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.26921939465653383,
+      "sim_ranking": [
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8"
+      ],
+      "sim_winner": "tp1_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "e2e_ms:p90": {
+      "agreement": 0.0,
+      "concordant_pairs": 0,
+      "discordant_pairs": 48,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.25730483004000526,
+      "sim_ranking": [
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8"
+      ],
+      "sim_winner": "tp1_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "tpot_ms:mean": {
+      "agreement": 0.0,
+      "concordant_pairs": 0,
+      "discordant_pairs": 48,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.13962124906187545,
+      "sim_ranking": [
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8"
+      ],
+      "sim_winner": "tp1_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "tpot_ms:p90": {
+      "agreement": 0.0,
+      "concordant_pairs": 0,
+      "discordant_pairs": 48,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.13357103696654363,
+      "sim_ranking": [
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8"
+      ],
+      "sim_winner": "tp1_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:mean": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns16",
+      "selected_config_real_regret": 0.0,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": true
+    },
+    "ttft_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp1_mns16"
+      ],
+      "real_winner": "tp4_mns16",
+      "selected_config_real_regret": 0.0,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": true
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-pd"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.md
new file mode 100644
index 0000000..94484d6
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.md
@@ -0,0 +1,10 @@
+# Qwen30 Frontier vs real latency selection
+
+| Objective | Frontier | Real | Match | Regret | Pairwise |
+|---|---|---|---:|---:|---:|
+| ttft_ms:mean | tp4_mns16 | tp4_mns16 | yes | 0.0% | 100.0% |
+| ttft_ms:p90 | tp4_mns16 | tp4_mns16 | yes | 0.0% | 100.0% |
+| tpot_ms:mean | tp1_mns16 | tp4_mns32 | no | 14.0% | 0.0% |
+| tpot_ms:p90 | tp1_mns16 | tp4_mns8 | no | 13.4% | 0.0% |
+| e2e_ms:mean | tp1_mns16 | tp4_mns32 | no | 26.9% | 0.0% |
+| e2e_ms:p90 | tp1_mns16 | tp4_mns8 | no | 25.7% | 0.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.stdout.json
new file mode 100644
index 0000000..1aa57e0
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-comparison.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:mean": {"agreement": 0.0, "concordant_pairs": 0, "discordant_pairs": 48, "informative_pairs": 48, "real_ranking": ["tp4_mns32", "tp4_mns8", "tp4_mns64", "tp4_mns16", "tp2_mns16", "tp2_mns8", "tp2_mns32", "tp2_mns64", "tp1_mns64", "tp1_mns16", "tp1_mns32", "tp1_mns8"], "real_winner": "tp4_mns32", "selected_config_real_regret": 0.26921939465653383, "sim_ranking": ["tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8"], "sim_winner": "tp1_mns16", "tied_pairs": 18, "winner_match": false}, "e2e_ms:p90": {"agreement": 0.0, "concordant_pairs": 0, "discordant_pairs": 48, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp2_mns64", "tp1_mns64", "tp1_mns16", "tp1_mns32", "tp1_mns8"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.25730483004000526, "sim_ranking": ["tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8"], "sim_winner": "tp1_mns16", "tied_pairs": 18, "winner_match": false}, "tpot_ms:mean": {"agreement": 0.0, "concordant_pairs": 0, "discordant_pairs": 48, "informative_pairs": 48, "real_ranking": ["tp4_mns32", "tp4_mns8", "tp4_mns64", "tp4_mns16", "tp2_mns16", "tp2_mns32", "tp2_mns8", "tp2_mns64", "tp1_mns64", "tp1_mns32", "tp1_mns16", "tp1_mns8"], "real_winner": "tp4_mns32", "selected_config_real_regret": 0.13962124906187545, "sim_ranking": ["tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8"], "sim_winner": "tp1_mns16", "tied_pairs": 18, "winner_match": false}, "tpot_ms:p90": {"agreement": 0.0, "concordant_pairs": 0, "discordant_pairs": 48, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns32", "tp2_mns16", "tp2_mns8", "tp2_mns64", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.13357103696654363, "sim_ranking": ["tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8"], "sim_winner": "tp1_mns16", "tied_pairs": 18, "winner_match": false}, "ttft_ms:mean": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns16", "tp4_mns64", "tp4_mns32", "tp4_mns8", "tp2_mns8", "tp2_mns64", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "real_winner": "tp4_mns16", "selected_config_real_regret": 0.0, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": true}, "ttft_ms:p90": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns16", "tp4_mns64", "tp4_mns8", "tp4_mns32", "tp2_mns8", "tp2_mns64", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64", "tp1_mns16"], "real_winner": "tp4_mns16", "selected_config_real_regret": 0.0, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": true}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.json
new file mode 100644
index 0000000..3cab437
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.json
@@ -0,0 +1,1298 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "tpot_ms",
+    "e2e_ms"
+  ],
+  "case_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd",
+  "configs": {
+    "tp1_mns16": {
+      "metrics": {
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+          "trial_stddev_of_means_ms": 3.640625296359905
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+          "pooled_p90_ms": 4.838337488362463,
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+          "trial_mean_of_means_ms": 4.8488702313524765,
+          "trial_stddev_of_means_ms": 0.02240869837530002
+        },
+        "ttft_ms": {
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+          "pooled_p90_ms": 152.70179708022624,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 151.28173231440823,
+          "trial_stddev_of_means_ms": 0.9864045576075636
+        }
+      },
+      "trials": [
+        {
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+          "trial": 1
+        },
+        {
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+          "trial": 2
+        },
+        {
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+          "trial": 3
+        }
+      ]
+    },
+    "tp1_mns32": {
+      "metrics": {
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+              "p90_ms": 63.24575201142579,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns32/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "pooled_mean_ms": 605.5669432571543,
+          "pooled_p90_ms": 610.7392100384459,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 605.5669432571543,
+          "trial_stddev_of_means_ms": 2.5583322144334986
+        },
+        "tpot_ms": {
+          "pooled_mean_ms": 4.264903840417586,
+          "pooled_p90_ms": 4.27982993753935,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 4.264903840417586,
+          "trial_stddev_of_means_ms": 0.008241890125268254
+        },
+        "ttft_ms": {
+          "pooled_mean_ms": 63.8859268507706,
+          "pooled_p90_ms": 67.59266997687519,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 63.8859268507706,
+          "trial_stddev_of_means_ms": 1.5158748686612207
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 605.7536339084077,
+              "p90_ms": 610.4160649701953,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.264924569000695,
+              "p90_ms": 4.281197173161593,
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+            },
+            "ttft_ms": {
+              "mean_ms": 64.06844277909502,
+              "p90_ms": 67.37245502881706,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns64/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 602.9203796349539,
+              "p90_ms": 606.4624059945345,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.256651605550648,
+              "p90_ms": 4.271073574860265,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 62.287057342022194,
+              "p90_ms": 64.74815693218261,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns64/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 608.0268162281014,
+              "p90_ms": 613.2307189982384,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.273135346701415,
+              "p90_ms": 4.29227040974262,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 65.30228043119459,
+              "p90_ms": 69.0081981010735,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns64/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "pooled_mean_ms": 605.0888788116282,
+          "pooled_p90_ms": 610.0081680342555,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 605.0888788116282,
+          "trial_stddev_of_means_ms": 0.8901667424570828
+        },
+        "tpot_ms": {
+          "pooled_mean_ms": 4.256483071855015,
+          "pooled_p90_ms": 4.268226101921182,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 4.256483071855015,
+          "trial_stddev_of_means_ms": 0.0026292150472670742
+        },
+        "ttft_ms": {
+          "pooled_mean_ms": 64.47646671392322,
+          "pooled_p90_ms": 68.37363401427865,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 64.47646671392322,
+          "trial_stddev_of_means_ms": 1.0383603866006366
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 606.0357820910452,
+              "p90_ms": 611.1916180234402,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.2545578456668816,
+              "p90_ms": 4.264190204544213,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 65.67109757204099,
+              "p90_ms": 71.20707002468407,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns8/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 604.2691217230041,
+              "p90_ms": 608.334549004212,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.2554127314675245,
+              "p90_ms": 4.26826358307153,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 63.79063503163354,
+              "p90_ms": 67.93791998643428,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns8/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 604.9617326208354,
+              "p90_ms": 610.0081680342555,
+              "samples": 129
+            },
+            "tpot_ms": {
+              "mean_ms": 4.259478638430637,
+              "p90_ms": 4.271154976669904,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 63.96766753809512,
+              "p90_ms": 67.67752906307578,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-pd/real/tp4_mns8/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    }
+  },
+  "prefill_only": false,
+  "schema": "qwen30-latency-case-real-audit-v1",
+  "trace_manifests": {
+    "tp1": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.215,
+      "last_arrival_s": 595.3488372093024,
+      "output_tokens": [
+        128
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp1/private/real_requests.jsonl",
+      "private_jsonl_sha256": "fa903f38c522a1ab5fa6325697f7aebd8ce17c0809ecee5cba7f28ec7eb6a030",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp1/public/frontier.csv",
+      "public_csv_sha256": "d33dd9fcd1aea6c6a6fb6730d8bfe30392ad6827f4132682ad151cccabe4bf2d",
+      "requests": 129,
+      "row_vector_sha256": "6cb1cdd992eca886c8f1611ee83ec1373ff162bd1b608a8ce23974885b393aea",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 1
+    },
+    "tp2": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.43,
+      "last_arrival_s": 297.6744186046512,
+      "output_tokens": [
+        128
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp2/private/real_requests.jsonl",
+      "private_jsonl_sha256": "51d9e597d5efec87f9a6a7ea425ee1fa95eb4d80db8cadaaef8acbab0f024919",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp2/public/frontier.csv",
+      "public_csv_sha256": "c3d7ce76385f348e8082d9aae1449384e9710a2d4c9a0b8b5d36bac28a5f2434",
+      "requests": 129,
+      "row_vector_sha256": "51947bb92449fc5be3ecaafb5b0ba08acd848ff5c6cff9a04a66bd3fda74d45e",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 2
+    },
+    "tp4": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.86,
+      "last_arrival_s": 148.8372093023256,
+      "output_tokens": [
+        128
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp4/private/real_requests.jsonl",
+      "private_jsonl_sha256": "90450c8ca24055ed18d3edeb43255380decb7de285ff982b48cb4211775f0326",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd/tp4/public/frontier.csv",
+      "public_csv_sha256": "c78ced228c0df8a20874f14cc620a4e259a828d9fc876a8dc022fb0280af1591",
+      "requests": 129,
+      "row_vector_sha256": "ce55943d20be72c04040e4bbeb0621d529590594dd11e968eefcf788895564a1",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 4
+    }
+  },
+  "traces_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-pd",
+  "winners": {
+    "e2e_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 604.4058500071964
+    },
+    "e2e_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 610.0081680342555
+    },
+    "tpot_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 4.254808547439789
+    },
+    "tpot_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 4.268226101921182
+    },
+    "ttft_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns16",
+      "winner_value_ms": 63.03574686938565
+    },
+    "ttft_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp1_mns16"
+      ],
+      "winner": "tp4_mns16",
+      "winner_value_ms": 66.4233659626916
+    }
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.md
new file mode 100644
index 0000000..9edf269
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.md
@@ -0,0 +1,12 @@
+# Qwen30 real latency case audit
+
+Prefill-only: `False`.
+
+| Objective | Real winner | Value (ms) |
+|---|---|---:|
+| ttft_ms:pooled_mean_ms | tp4_mns16 | 63.04 |
+| ttft_ms:pooled_p90_ms | tp4_mns16 | 66.42 |
+| tpot_ms:pooled_mean_ms | tp4_mns32 | 4.25 |
+| tpot_ms:pooled_p90_ms | tp4_mns8 | 4.27 |
+| e2e_ms:pooled_mean_ms | tp4_mns32 | 604.41 |
+| e2e_ms:pooled_p90_ms | tp4_mns8 | 610.01 |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.stdout.json
new file mode 100644
index 0000000..01ed58b
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-pd-real-audit.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:pooled_mean_ms": {"ranking": ["tp4_mns32", "tp4_mns8", "tp4_mns64", "tp4_mns16", "tp2_mns16", "tp2_mns8", "tp2_mns32", "tp2_mns64", "tp1_mns64", "tp1_mns16", "tp1_mns32", "tp1_mns8"], "winner": "tp4_mns32", "winner_value_ms": 604.4058500071964}, "e2e_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp2_mns64", "tp1_mns64", "tp1_mns16", "tp1_mns32", "tp1_mns8"], "winner": "tp4_mns8", "winner_value_ms": 610.0081680342555}, "tpot_ms:pooled_mean_ms": {"ranking": ["tp4_mns32", "tp4_mns8", "tp4_mns64", "tp4_mns16", "tp2_mns16", "tp2_mns32", "tp2_mns8", "tp2_mns64", "tp1_mns64", "tp1_mns32", "tp1_mns16", "tp1_mns8"], "winner": "tp4_mns32", "winner_value_ms": 4.254808547439789}, "tpot_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns32", "tp2_mns16", "tp2_mns8", "tp2_mns64", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "winner": "tp4_mns8", "winner_value_ms": 4.268226101921182}, "ttft_ms:pooled_mean_ms": {"ranking": ["tp4_mns16", "tp4_mns64", "tp4_mns32", "tp4_mns8", "tp2_mns8", "tp2_mns64", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "winner": "tp4_mns16", "winner_value_ms": 63.03574686938565}, "ttft_ms:pooled_p90_ms": {"ranking": ["tp4_mns16", "tp4_mns64", "tp4_mns8", "tp4_mns32", "tp2_mns8", "tp2_mns64", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64", "tp1_mns16"], "winner": "tp4_mns16", "winner_value_ms": 66.4233659626916}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.json
new file mode 100644
index 0000000..40f961a
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.json
@@ -0,0 +1,326 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "cells": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp1_mns16/tp1/result.json"
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp1_mns32/tp1/result.json"
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp1_mns64/tp1/result.json"
+    },
+    "tp1_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        },
+        "ttft_ms": {
+          "mean": 166.66991554923203,
+          "p90": 166.6699155492779
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp1_mns8/tp1/result.json"
+    },
+    "tp2_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        },
+        "ttft_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp2_mns16/tp2/result.json"
+    },
+    "tp2_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        },
+        "ttft_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp2_mns32/tp2/result.json"
+    },
+    "tp2_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        },
+        "ttft_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp2_mns64/tp2/result.json"
+    },
+    "tp2_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        },
+        "ttft_ms": {
+          "mean": 118.55592059231998,
+          "p90": 118.55592059232833
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp2_mns8/tp2/result.json"
+    },
+    "tp4_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        },
+        "ttft_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp4_mns16/tp4/result.json"
+    },
+    "tp4_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        },
+        "ttft_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp4_mns32/tp4/result.json"
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        },
+        "ttft_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp4_mns64/tp4/result.json"
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        },
+        "ttft_ms": {
+          "mean": 86.52545838364681,
+          "p90": 86.52545838364745
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po/runs/tp4_mns8/tp4/result.json"
+    }
+  },
+  "prefill_only": true,
+  "real_audit": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/analysis-r6/fixed-po-real-audit.json",
+  "schema": "qwen30-latency-case-frontier-real-comparison-v1",
+  "selection": {
+    "e2e_ms:mean": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.014895639803871355,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "e2e_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.03590282591969048,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:mean": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.014940997472395743,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.035908453871728634,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/fixed-po"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.md
new file mode 100644
index 0000000..5237196
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.md
@@ -0,0 +1,8 @@
+# Qwen30 Frontier vs real latency selection
+
+| Objective | Frontier | Real | Match | Regret | Pairwise |
+|---|---|---|---:|---:|---:|
+| ttft_ms:mean | tp4_mns16 | tp4_mns8 | no | 1.5% | 100.0% |
+| ttft_ms:p90 | tp4_mns16 | tp4_mns8 | no | 3.6% | 100.0% |
+| e2e_ms:mean | tp4_mns16 | tp4_mns8 | no | 1.5% | 100.0% |
+| e2e_ms:p90 | tp4_mns16 | tp4_mns8 | no | 3.6% | 100.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.stdout.json
new file mode 100644
index 0000000..0a76756
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-comparison.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:mean": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns16", "tp1_mns8", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.014895639803871355, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}, "e2e_ms:p90": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.03590282591969048, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}, "ttft_ms:mean": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns16", "tp1_mns8", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.014940997472395743, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}, "ttft_ms:p90": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.035908453871728634, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.json
new file mode 100644
index 0000000..a4fcbba
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.json
@@ -0,0 +1,997 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "case_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po",
+  "configs": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "pooled_mean_ms": 151.54830888467202,
+          "pooled_p90_ms": 152.33826905023307,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 151.54830888467202,
+          "trial_stddev_of_means_ms": 0.33839071804993504
+        },
+        "ttft_ms": {
+          "pooled_mean_ms": 151.50490087229585,
+          "pooled_p90_ms": 152.29528304189444,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 151.50490087229585,
+          "trial_stddev_of_means_ms": 0.3392777547312034
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 151.25221894176806,
+              "p90_ms": 152.03110210131854,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 151.20715750724278,
+              "p90_ms": 151.9814640050754,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns16/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 151.4755454836702,
+              "p90_ms": 152.21454401034862,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 151.4332707151915,
+              "p90_ms": 152.16313605196774,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns16/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 151.9171622285778,
+              "p90_ms": 152.64088998083025,
+              "samples": 129
+            },
+            "ttft_ms": {
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+              "p90_ms": 152.5908849434927,
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+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns16/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "pooled_mean_ms": 151.4782552960514,
+          "pooled_p90_ms": 152.49883604701608,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 151.4782552960514,
+          "trial_stddev_of_means_ms": 0.5555788512092701
+        },
+        "ttft_ms": {
+          "pooled_mean_ms": 151.43368434935846,
+          "pooled_p90_ms": 152.45853806845844,
+          "pooled_samples": 387,
+          "trial_mean_of_means_ms": 151.43368434935846,
+          "trial_stddev_of_means_ms": 0.5560791927635007
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 151.00544339222762,
+              "p90_ms": 151.96295792702585,
+              "samples": 129
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+            "ttft_ms": {
+              "mean_ms": 150.96285229624618,
+              "p90_ms": 151.92402398679405,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns32/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 151.33915553880178,
+              "p90_ms": 152.3007940268144,
+              "samples": 129
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+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns32/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
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+              "p90_ms": 152.93943404685706,
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+            "ttft_ms": {
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+              "p90_ms": 152.89701998699456,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns32/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
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+          "pooled_p90_ms": 153.7184970220551,
+          "pooled_samples": 387,
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+          "trial_stddev_of_means_ms": 0.5522776932799126
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+        "ttft_ms": {
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+          "pooled_p90_ms": 153.6727879429236,
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+          "trial_mean_of_means_ms": 152.58183204256076,
+          "trial_stddev_of_means_ms": 0.552880728503269
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 152.98813100463835,
+              "p90_ms": 153.7133390083909,
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+            },
+            "ttft_ms": {
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+              "p90_ms": 153.67183403577656,
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+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns64/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 152.89909483832415,
+              "p90_ms": 154.20521004125476,
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+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp1_mns64/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
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+          "trial_mean_of_means_ms": 64.2842707174255,
+          "trial_stddev_of_means_ms": 1.80289690665978
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 62.84650166739183,
+              "p90_ms": 63.89774801209569,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 62.80200301792271,
+              "p90_ms": 63.856702065095305,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp4_mns8/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 66.3395124548945,
+              "p90_ms": 70.76063798740506,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 66.29134260132447,
+              "p90_ms": 70.7101090811193,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp4_mns8/trial2/results/result.json",
+          "trial": 2
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 63.801664533274064,
+              "p90_ms": 67.48319591861218,
+              "samples": 129
+            },
+            "ttft_ms": {
+              "mean_ms": 63.759466533029325,
+              "p90_ms": 67.4400629941374,
+              "samples": 129
+            }
+          },
+          "requests": 129,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/fixed-po/real/tp4_mns8/trial3/results/result.json",
+          "trial": 3
+        }
+      ]
+    }
+  },
+  "prefill_only": true,
+  "schema": "qwen30-latency-case-real-audit-v1",
+  "trace_manifests": {
+    "tp1": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.215,
+      "last_arrival_s": 595.3488372093024,
+      "output_tokens": [
+        1
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp1/private/real_requests.jsonl",
+      "private_jsonl_sha256": "ce7582fc13050078a243d7f6adfc2b2e071dbe87b5f760c7bf111af57718ccfb",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp1/public/frontier.csv",
+      "public_csv_sha256": "e6f1ca0354e9d93c60ff18261ae6e08e2e54dbc888e30e244776f9cc8695a8cf",
+      "requests": 129,
+      "row_vector_sha256": "7c8dc7cccd2bd874768c1b06ca40d2327452390577b9907bacb76270b46998fa",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 1
+    },
+    "tp2": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.43,
+      "last_arrival_s": 297.6744186046512,
+      "output_tokens": [
+        1
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp2/private/real_requests.jsonl",
+      "private_jsonl_sha256": "3fe3c01ac31cd776b2458cafb818d889b20c5e14948154bbd716cce7200c8d5b",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp2/public/frontier.csv",
+      "public_csv_sha256": "78b900d8f47fec3a1c83b748f82cb9623ce3f0cf08265aa20c3ef1511a4a97e0",
+      "requests": 129,
+      "row_vector_sha256": "c9382d9007ea1dc572898836f2d0efb8e2244c4febc1ed59d5aeacfcc5475c0a",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 2
+    },
+    "tp4": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 0.86,
+      "last_arrival_s": 148.8372093023256,
+      "output_tokens": [
+        1
+      ],
+      "per_gpu_offered_request_rate": 0.215,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp4/private/real_requests.jsonl",
+      "private_jsonl_sha256": "af3ba5a7888ea5f283bb360dd36f1f455906f69f5ad82cef84e82018545710db",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po/tp4/public/frontier.csv",
+      "public_csv_sha256": "8b1100ccab34d9dac62b7ff1508d36bdf75aa3c3135e6f6642a0d3ac77af2505",
+      "requests": 129,
+      "row_vector_sha256": "a5e4959f28790eaa99a59a1b86c449a4e484967f1e35e47900d1a27fa061607f",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 4
+    }
+  },
+  "traces_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/traces/fixed-po",
+  "winners": {
+    "e2e_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 64.32922621852013
+    },
+    "e2e_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 67.98768497537822
+    },
+    "ttft_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 64.2842707174255
+    },
+    "ttft_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 67.94753996655345
+    }
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.md
new file mode 100644
index 0000000..2ffe8bf
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.md
@@ -0,0 +1,10 @@
+# Qwen30 real latency case audit
+
+Prefill-only: `True`.
+
+| Objective | Real winner | Value (ms) |
+|---|---|---:|
+| ttft_ms:pooled_mean_ms | tp4_mns8 | 64.28 |
+| ttft_ms:pooled_p90_ms | tp4_mns8 | 67.95 |
+| e2e_ms:pooled_mean_ms | tp4_mns8 | 64.33 |
+| e2e_ms:pooled_p90_ms | tp4_mns8 | 67.99 |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.stdout.json
new file mode 100644
index 0000000..282995c
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/fixed-po-real-audit.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:pooled_mean_ms": {"ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns16", "tp1_mns8", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 64.32922621852013}, "e2e_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 67.98768497537822}, "ttft_ms:pooled_mean_ms": {"ranking": ["tp4_mns8", "tp4_mns32", "tp4_mns64", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns32", "tp1_mns16", "tp1_mns8", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 64.2842707174255}, "ttft_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns32", "tp1_mns8", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 67.94753996655345}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.json
new file mode 100644
index 0000000..2d8bdff
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.json
@@ -0,0 +1,326 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "cells": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 340.75522510609915,
+          "p90": 832.752247743656
+        },
+        "ttft_ms": {
+          "mean": 340.75522510609915,
+          "p90": 832.752247743656
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp1_mns16/tp1/result.json"
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 340.75598360435777,
+          "p90": 832.752247743656
+        },
+        "ttft_ms": {
+          "mean": 340.75598360435777,
+          "p90": 832.752247743656
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp1_mns32/tp1/result.json"
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 340.7569941487134,
+          "p90": 832.752247743656
+        },
+        "ttft_ms": {
+          "mean": 340.7569941487134,
+          "p90": 832.752247743656
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp1_mns64/tp1/result.json"
+    },
+    "tp1_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 340.75522510609915,
+          "p90": 832.752247743656
+        },
+        "ttft_ms": {
+          "mean": 340.75522510609915,
+          "p90": 832.752247743656
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp1_mns8/tp1/result.json"
+    },
+    "tp2_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 222.73961839402438,
+          "p90": 513.3421414172687
+        },
+        "ttft_ms": {
+          "mean": 222.73961839402438,
+          "p90": 513.3421414172687
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp2_mns16/tp2/result.json"
+    },
+    "tp2_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 222.7393083124536,
+          "p90": 513.3421414172687
+        },
+        "ttft_ms": {
+          "mean": 222.7393083124536,
+          "p90": 513.3421414172687
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp2_mns32/tp2/result.json"
+    },
+    "tp2_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 222.73932355314494,
+          "p90": 513.3421414172687
+        },
+        "ttft_ms": {
+          "mean": 222.73932355314494,
+          "p90": 513.3421414172687
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp2_mns64/tp2/result.json"
+    },
+    "tp2_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 222.73961839402438,
+          "p90": 513.3421414172687
+        },
+        "ttft_ms": {
+          "mean": 222.73961839402438,
+          "p90": 513.3421414172687
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp2_mns8/tp2/result.json"
+    },
+    "tp4_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 164.583607484367,
+          "p90": 355.93888195481327
+        },
+        "ttft_ms": {
+          "mean": 164.583607484367,
+          "p90": 355.93888195481327
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp4_mns16/tp4/result.json"
+    },
+    "tp4_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 164.58396574139448,
+          "p90": 355.93888195481327
+        },
+        "ttft_ms": {
+          "mean": 164.58396574139448,
+          "p90": 355.93888195481327
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp4_mns32/tp4/result.json"
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 164.58471606968033,
+          "p90": 355.93888195481327
+        },
+        "ttft_ms": {
+          "mean": 164.58471606968033,
+          "p90": 355.93888195481327
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp4_mns64/tp4/result.json"
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 164.583607484367,
+          "p90": 355.93888195481327
+        },
+        "ttft_ms": {
+          "mean": 164.583607484367,
+          "p90": 355.93888195481327
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po/runs/tp4_mns8/tp4/result.json"
+    }
+  },
+  "prefill_only": true,
+  "real_audit": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/analysis-r6/trace-po-real-audit.json",
+  "schema": "qwen30-latency-case-frontier-real-comparison-v1",
+  "selection": {
+    "e2e_ms:mean": {
+      "agreement": 0.8412698412698413,
+      "concordant_pairs": 53,
+      "discordant_pairs": 10,
+      "informative_pairs": 63,
+      "real_ranking": [
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns64",
+      "selected_config_real_regret": 0.0318784105178655,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 3,
+      "winner_match": false
+    },
+    "e2e_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.0033158177113489728,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:mean": {
+      "agreement": 0.8412698412698413,
+      "concordant_pairs": 53,
+      "discordant_pairs": 10,
+      "informative_pairs": 63,
+      "real_ranking": [
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns64",
+      "selected_config_real_regret": 0.03187213306057872,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 3,
+      "winner_match": false
+    },
+    "ttft_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.0037779133092611917,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/sim/trace-po"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.md
new file mode 100644
index 0000000..12ecc66
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.md
@@ -0,0 +1,8 @@
+# Qwen30 Frontier vs real latency selection
+
+| Objective | Frontier | Real | Match | Regret | Pairwise |
+|---|---|---|---:|---:|---:|
+| ttft_ms:mean | tp4_mns16 | tp4_mns64 | no | 3.2% | 84.1% |
+| ttft_ms:p90 | tp4_mns16 | tp4_mns8 | no | 0.4% | 100.0% |
+| e2e_ms:mean | tp4_mns16 | tp4_mns64 | no | 3.2% | 84.1% |
+| e2e_ms:p90 | tp4_mns16 | tp4_mns8 | no | 0.3% | 100.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.stdout.json
new file mode 100644
index 0000000..c28456a
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-comparison.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:mean": {"agreement": 0.8412698412698413, "concordant_pairs": 53, "discordant_pairs": 10, "informative_pairs": 63, "real_ranking": ["tp4_mns64", "tp4_mns32", "tp4_mns8", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "real_winner": "tp4_mns64", "selected_config_real_regret": 0.0318784105178655, "sim_ranking": ["tp4_mns16", "tp4_mns8", "tp4_mns32", "tp4_mns64", "tp2_mns32", "tp2_mns64", "tp2_mns16", "tp2_mns8", "tp1_mns16", "tp1_mns8", "tp1_mns32", "tp1_mns64"], "sim_winner": "tp4_mns16", "tied_pairs": 3, "winner_match": false}, "e2e_ms:p90": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.0033158177113489728, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}, "ttft_ms:mean": {"agreement": 0.8412698412698413, "concordant_pairs": 53, "discordant_pairs": 10, "informative_pairs": 63, "real_ranking": ["tp4_mns64", "tp4_mns32", "tp4_mns8", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "real_winner": "tp4_mns64", "selected_config_real_regret": 0.03187213306057872, "sim_ranking": ["tp4_mns16", "tp4_mns8", "tp4_mns32", "tp4_mns64", "tp2_mns32", "tp2_mns64", "tp2_mns16", "tp2_mns8", "tp1_mns16", "tp1_mns8", "tp1_mns32", "tp1_mns64"], "sim_winner": "tp4_mns16", "tied_pairs": 3, "winner_match": false}, "ttft_ms:p90": {"agreement": 1.0, "concordant_pairs": 48, "discordant_pairs": 0, "informative_pairs": 48, "real_ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64"], "real_winner": "tp4_mns8", "selected_config_real_regret": 0.0037779133092611917, "sim_ranking": ["tp4_mns16", "tp4_mns32", "tp4_mns64", "tp4_mns8", "tp2_mns16", "tp2_mns32", "tp2_mns64", "tp2_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64", "tp1_mns8"], "sim_winner": "tp4_mns16", "tied_pairs": 18, "winner_match": false}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.json
new file mode 100644
index 0000000..9421973
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.json
@@ -0,0 +1,997 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "case_root": "/home/admin/cpfs/wjh/aituner/qwen30-latency-expansion-20260718-r2/real-r6/trace-po",
+  "configs": {
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+        }
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+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns64",
+      "winner_value_ms": 223.12445959072676
+    },
+    "ttft_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 666.7667380534112
+    }
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.md
new file mode 100644
index 0000000..fee21bb
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.md
@@ -0,0 +1,10 @@
+# Qwen30 real latency case audit
+
+Prefill-only: `True`.
+
+| Objective | Real winner | Value (ms) |
+|---|---|---:|
+| ttft_ms:pooled_mean_ms | tp4_mns64 | 223.12 |
+| ttft_ms:pooled_p90_ms | tp4_mns8 | 666.77 |
+| e2e_ms:pooled_mean_ms | tp4_mns64 | 223.19 |
+| e2e_ms:pooled_p90_ms | tp4_mns8 | 667.10 |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.stdout.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.stdout.json
new file mode 100644
index 0000000..a5cdce0
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-expansion-lo/trace-po-real-audit.stdout.json
@@ -0,0 +1 @@
+{"e2e_ms:pooled_mean_ms": {"ranking": ["tp4_mns64", "tp4_mns32", "tp4_mns8", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "winner": "tp4_mns64", "winner_value_ms": 223.1923911500318}, "e2e_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 667.0993800507858}, "ttft_ms:pooled_mean_ms": {"ranking": ["tp4_mns64", "tp4_mns32", "tp4_mns8", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns16", "tp1_mns64", "tp1_mns32", "tp1_mns8"], "winner": "tp4_mns64", "winner_value_ms": 223.12445959072676}, "ttft_ms:pooled_p90_ms": {"ranking": ["tp4_mns8", "tp4_mns64", "tp4_mns32", "tp4_mns16", "tp2_mns64", "tp2_mns8", "tp2_mns32", "tp2_mns16", "tp1_mns8", "tp1_mns16", "tp1_mns32", "tp1_mns64"], "winner": "tp4_mns8", "winner_value_ms": 666.7667380534112}}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.json
new file mode 100644
index 0000000..c370177
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.json
@@ -0,0 +1,453 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "tpot_ms",
+    "e2e_ms"
+  ],
+  "cells": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 128201.44370110576,
+          "p90": 216221.8716312423
+        },
+        "tpot_ms": {
+          "mean": 106.74127671151493,
+          "p90": 107.53204073371177
+        },
+        "ttft_ms": {
+          "mean": 100982.41813966946,
+          "p90": 188801.20124415262
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp1_mns16/tp1/result.json"
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 54134.6392206195,
+          "p90": 70757.16788718625
+        },
+        "tpot_ms": {
+          "mean": 131.73148052557949,
+          "p90": 134.09269340154515
+        },
+        "ttft_ms": {
+          "mean": 20543.111686596734,
+          "p90": 40978.20939546926
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp1_mns32/tp1/result.json"
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 36992.839178769755,
+          "p90": 38253.17393690583
+        },
+        "tpot_ms": {
+          "mean": 143.73592141724885,
+          "p90": 148.50084455017992
+        },
+        "ttft_ms": {
+          "mean": 340.1792173712992,
+          "p90": 390.1667904730175
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp1_mns64/tp1/result.json"
+    },
+    "tp1_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 231355.5665072295,
+          "p90": 401099.3133242681
+        },
+        "tpot_ms": {
+          "mean": 79.72075104221494,
+          "p90": 80.05841803805441
+        },
+        "ttft_ms": {
+          "mean": 211026.77499146466,
+          "p90": 380684.4167245642
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp1_mns8/tp1/result.json"
+    },
+    "tp2_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 99415.72204671855,
+          "p90": 170023.18522015438
+        },
+        "tpot_ms": {
+          "mean": 69.3294093088488,
+          "p90": 69.78173796567563
+        },
+        "ttft_ms": {
+          "mean": 81736.72267296212,
+          "p90": 152228.84203890432
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp2_mns16/tp2/result.json"
+    },
+    "tp2_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 47656.99443299207,
+          "p90": 71358.22494490076
+        },
+        "tpot_ms": {
+          "mean": 83.38213205445625,
+          "p90": 84.68169232450846
+        },
+        "ttft_ms": {
+          "mean": 26394.55075910572,
+          "p90": 52520.58767404907
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp2_mns32/tp2/result.json"
+    },
+    "tp2_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 25800.137969948584,
+          "p90": 26994.699921135867
+        },
+        "tpot_ms": {
+          "mean": 100.27798158873513,
+          "p90": 104.85288258852235
+        },
+        "ttft_ms": {
+          "mean": 229.2526648211283,
+          "p90": 261.37367146904467
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp2_mns64/tp2/result.json"
+    },
+    "tp2_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 173225.23923299377,
+          "p90": 301133.20586389
+        },
+        "tpot_ms": {
+          "mean": 53.275061700270285,
+          "p90": 53.466591976089035
+        },
+        "ttft_ms": {
+          "mean": 159640.09849942484,
+          "p90": 287499.22490998777
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp2_mns8/tp2/result.json"
+    },
+    "tp4_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 77014.8840236653,
+          "p90": 132893.6304418779
+        },
+        "tpot_ms": {
+          "mean": 46.95641974752248,
+          "p90": 47.23194326182317
+        },
+        "ttft_ms": {
+          "mean": 65040.99698804708,
+          "p90": 120849.48491011641
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp4_mns16/tp4/result.json"
+    },
+    "tp4_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 41823.75653856865,
+          "p90": 66900.19803040712
+        },
+        "tpot_ms": {
+          "mean": 56.89199563649036,
+          "p90": 57.75799749592927
+        },
+        "ttft_ms": {
+          "mean": 27316.2976512636,
+          "p90": 54230.649753904916
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp4_mns32/tp4/result.json"
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 24104.231142330624,
+          "p90": 29174.179941975835
+        },
+        "tpot_ms": {
+          "mean": 69.02049776725552,
+          "p90": 72.06184134879742
+        },
+        "ttft_ms": {
+          "mean": 6504.004211680465,
+          "p90": 13004.945097644395
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp4_mns64/tp4/result.json"
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 133968.39678804282,
+          "p90": 233355.7233519645
+        },
+        "tpot_ms": {
+          "mean": 37.645089303294014,
+          "p90": 37.75522144488961
+        },
+        "ttft_ms": {
+          "mean": 124368.89901570287,
+          "p90": 223728.14188352478
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd/runs/tp4_mns8/tp4/result.json"
+    }
+  },
+  "prefill_only": false,
+  "real_audit": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/analysis/fixed-pd/real-audit.json",
+  "schema": "qwen30-latency-case-frontier-real-comparison-v1",
+  "selection": {
+    "e2e_ms:mean": {
+      "agreement": 0.5151515151515151,
+      "concordant_pairs": 34,
+      "discordant_pairs": 32,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp1_mns32",
+        "tp4_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp1_mns64",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp1_mns32",
+      "selected_config_real_regret": 0.017005214686575575,
+      "sim_ranking": [
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp2_mns32",
+        "tp1_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns64",
+      "tied_pairs": 0,
+      "winner_match": false
+    },
+    "e2e_ms:p90": {
+      "agreement": 0.5151515151515151,
+      "concordant_pairs": 34,
+      "discordant_pairs": 32,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp1_mns32",
+      "selected_config_real_regret": 0.054933980018932745,
+      "sim_ranking": [
+        "tp2_mns64",
+        "tp4_mns64",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp1_mns32",
+        "tp2_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp2_mns64",
+      "tied_pairs": 0,
+      "winner_match": false
+    },
+    "tpot_ms:mean": {
+      "agreement": 0.48484848484848486,
+      "concordant_pairs": 32,
+      "discordant_pairs": 34,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns32"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.0,
+      "sim_ranking": [
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns8",
+      "tied_pairs": 0,
+      "winner_match": true
+    },
+    "tpot_ms:p90": {
+      "agreement": 0.42424242424242425,
+      "concordant_pairs": 28,
+      "discordant_pairs": 38,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp2_mns8",
+        "tp4_mns32",
+        "tp2_mns64",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns32",
+        "tp2_mns16"
+      ],
+      "real_winner": "tp4_mns8",
+      "selected_config_real_regret": 0.0,
+      "sim_ranking": [
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp4_mns32",
+        "tp2_mns16",
+        "tp4_mns64",
+        "tp1_mns8",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns8",
+      "tied_pairs": 0,
+      "winner_match": true
+    },
+    "ttft_ms:mean": {
+      "agreement": 0.5909090909090909,
+      "concordant_pairs": 39,
+      "discordant_pairs": 27,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.5797674051508896,
+      "sim_ranking": [
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp4_mns64",
+        "tp1_mns32",
+        "tp2_mns32",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp2_mns64",
+      "tied_pairs": 0,
+      "winner_match": false
+    },
+    "ttft_ms:p90": {
+      "agreement": 0.5909090909090909,
+      "concordant_pairs": 39,
+      "discordant_pairs": 27,
+      "informative_pairs": 66,
+      "real_ranking": [
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp4_mns64",
+      "selected_config_real_regret": 0.5620663582204116,
+      "sim_ranking": [
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp4_mns64",
+        "tp1_mns32",
+        "tp2_mns32",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp1_mns16",
+        "tp4_mns8",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp2_mns64",
+      "tied_pairs": 0,
+      "winner_match": false
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-pd"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.md
new file mode 100644
index 0000000..a53acbe
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/comparison.md
@@ -0,0 +1,10 @@
+# Qwen30 Frontier vs real latency selection
+
+| Objective | Frontier | Real | Match | Regret | Pairwise |
+|---|---|---|---:|---:|---:|
+| ttft_ms:mean | tp2_mns64 | tp4_mns32 | no | 58.0% | 59.1% |
+| ttft_ms:p90 | tp2_mns64 | tp4_mns64 | no | 56.2% | 59.1% |
+| tpot_ms:mean | tp4_mns8 | tp4_mns8 | yes | 0.0% | 48.5% |
+| tpot_ms:p90 | tp4_mns8 | tp4_mns8 | yes | 0.0% | 42.4% |
+| e2e_ms:mean | tp4_mns64 | tp1_mns32 | no | 1.7% | 51.5% |
+| e2e_ms:p90 | tp2_mns64 | tp1_mns32 | no | 5.5% | 51.5% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.json
new file mode 100644
index 0000000..035bf0b
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.json
@@ -0,0 +1,1298 @@
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+      "row_vector_sha256": "1c92d235e3f7006367e2e0ad1a70ef4a8cf472b1fecc8aebae7f95218c20205d",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 2
+    },
+    "tp4": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 4.5,
+      "last_arrival_s": 56.888888888888886,
+      "output_tokens": [
+        256
+      ],
+      "per_gpu_offered_request_rate": 1.125,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-pd/tp4/private/real_requests.jsonl",
+      "private_jsonl_sha256": "aa08175b73187df17f69ef13946e947929ddf40cc0b5caf53e8209b9c342e174",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-pd/tp4/public/frontier.csv",
+      "public_csv_sha256": "5fbb14f2d04287096d9e5902db94041167cf6926d8c155dfc7d4b831fa94048c",
+      "requests": 257,
+      "row_vector_sha256": "2b6ecbd4c729db310300082f8362826c0ec407ae2451751c340dcf81c7a11859",
+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 4
+    }
+  },
+  "traces_root": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-pd",
+  "winners": {
+    "e2e_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp1_mns32",
+        "tp4_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp1_mns64",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp4_mns8"
+      ],
+      "winner": "tp1_mns32",
+      "winner_value_ms": 3203.7226679738205
+    },
+    "e2e_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp1_mns32",
+        "tp1_mns8",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp4_mns8"
+      ],
+      "winner": "tp1_mns32",
+      "winner_value_ms": 3389.1853449167684
+    },
+    "tpot_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp2_mns8",
+        "tp4_mns16",
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp2_mns16",
+        "tp2_mns32"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 8.417185619746073
+    },
+    "tpot_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns8",
+        "tp1_mns64",
+        "tp2_mns8",
+        "tp4_mns32",
+        "tp2_mns64",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns32",
+        "tp2_mns16"
+      ],
+      "winner": "tp4_mns8",
+      "winner_value_ms": 8.771115207734207
+    },
+    "ttft_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 123.15859724408143
+    },
+    "ttft_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns64",
+        "tp4_mns32",
+        "tp4_mns16",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp1_mns8",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp4_mns8"
+      ],
+      "winner": "tp4_mns64",
+      "winner_value_ms": 126.84211903251708
+    }
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.md
new file mode 100644
index 0000000..cd51259
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-pd/real-audit.md
@@ -0,0 +1,12 @@
+# Qwen30 real latency case audit
+
+Prefill-only: `False`.
+
+| Objective | Real winner | Value (ms) |
+|---|---|---:|
+| ttft_ms:pooled_mean_ms | tp4_mns32 | 123.16 |
+| ttft_ms:pooled_p90_ms | tp4_mns64 | 126.84 |
+| tpot_ms:pooled_mean_ms | tp4_mns8 | 8.42 |
+| tpot_ms:pooled_p90_ms | tp4_mns8 | 8.77 |
+| e2e_ms:pooled_mean_ms | tp1_mns32 | 3203.72 |
+| e2e_ms:pooled_p90_ms | tp1_mns32 | 3389.19 |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.json
new file mode 100644
index 0000000..9074b19
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.json
@@ -0,0 +1,326 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "cells": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        },
+        "ttft_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp1_mns16/tp1/result.json"
+    },
+    "tp1_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        },
+        "ttft_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp1_mns32/tp1/result.json"
+    },
+    "tp1_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        },
+        "ttft_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp1_mns64/tp1/result.json"
+    },
+    "tp1_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        },
+        "ttft_ms": {
+          "mean": 267.46878507222704,
+          "p90": 267.46878507223215
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp1_mns8/tp1/result.json"
+    },
+    "tp2_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        },
+        "ttft_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp2_mns16/tp2/result.json"
+    },
+    "tp2_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        },
+        "ttft_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp2_mns32/tp2/result.json"
+    },
+    "tp2_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        },
+        "ttft_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp2_mns64/tp2/result.json"
+    },
+    "tp2_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        },
+        "ttft_ms": {
+          "mean": 175.26431810890125,
+          "p90": 175.2643181089013
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp2_mns8/tp2/result.json"
+    },
+    "tp4_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        },
+        "ttft_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp4_mns16/tp4/result.json"
+    },
+    "tp4_mns32": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        },
+        "ttft_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp4_mns32/tp4/result.json"
+    },
+    "tp4_mns64": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        },
+        "ttft_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp4_mns64/tp4/result.json"
+    },
+    "tp4_mns8": {
+      "metrics": {
+        "e2e_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        },
+        "ttft_ms": {
+          "mean": 127.7919646347385,
+          "p90": 127.79196463473852
+        }
+      },
+      "path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po/runs/tp4_mns8/tp4/result.json"
+    }
+  },
+  "prefill_only": true,
+  "real_audit": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/analysis/fixed-po/real-audit.json",
+  "schema": "qwen30-latency-case-frontier-real-comparison-v1",
+  "selection": {
+    "e2e_ms:mean": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.0034531419781375313,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "e2e_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.005277055274057908,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:mean": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.003463041945107654,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    },
+    "ttft_ms:p90": {
+      "agreement": 1.0,
+      "concordant_pairs": 48,
+      "discordant_pairs": 0,
+      "informative_pairs": 48,
+      "real_ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "real_winner": "tp4_mns32",
+      "selected_config_real_regret": 0.005266030780421245,
+      "sim_ranking": [
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp2_mns8",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns16",
+      "tied_pairs": 18,
+      "winner_match": false
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/sim/fixed-po"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.md
new file mode 100644
index 0000000..d38638c
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/comparison.md
@@ -0,0 +1,8 @@
+# Qwen30 Frontier vs real latency selection
+
+| Objective | Frontier | Real | Match | Regret | Pairwise |
+|---|---|---|---:|---:|---:|
+| ttft_ms:mean | tp4_mns16 | tp4_mns32 | no | 0.3% | 100.0% |
+| ttft_ms:p90 | tp4_mns16 | tp4_mns32 | no | 0.5% | 100.0% |
+| e2e_ms:mean | tp4_mns16 | tp4_mns32 | no | 0.3% | 100.0% |
+| e2e_ms:p90 | tp4_mns16 | tp4_mns32 | no | 0.5% | 100.0% |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.json
new file mode 100644
index 0000000..74c5c48
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.json
@@ -0,0 +1,997 @@
+{
+  "applicable_metrics": [
+    "ttft_ms",
+    "e2e_ms"
+  ],
+  "case_root": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/real/fixed-po",
+  "configs": {
+    "tp1_mns16": {
+      "metrics": {
+        "e2e_ms": {
+          "pooled_mean_ms": 311.5405924270961,
+          "pooled_p90_ms": 313.7628498952836,
+          "pooled_samples": 771,
+          "trial_mean_of_means_ms": 311.5405924270961,
+          "trial_stddev_of_means_ms": 1.3039412575877052
+        },
+        "ttft_ms": {
+          "pooled_mean_ms": 311.49589566449873,
+          "pooled_p90_ms": 313.7203580699861,
+          "pooled_samples": 771,
+          "trial_mean_of_means_ms": 311.49589566449873,
+          "trial_stddev_of_means_ms": 1.3039649961427384
+        }
+      },
+      "trials": [
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 310.6955070939125,
+              "p90_ms": 311.31368898786604,
+              "samples": 257
+            },
+            "ttft_ms": {
+              "mean_ms": 310.65253322356983,
+              "p90_ms": 311.2668279791251,
+              "samples": 257
+            }
+          },
+          "requests": 257,
+          "result_path": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/real/fixed-po/real/tp1_mns16/trial1/results/result.json",
+          "trial": 1
+        },
+        {
+          "metrics": {
+            "e2e_ms": {
+              "mean_ms": 310.8839521212648,
+              "p90_ms": 311.4629740593955,
+              "samples": 257
+            },
+            "ttft_ms": {
+              "mean_ms": 310.837354891071,
+              "p90_ms": 311.4192739594728,
+              "samples": 257
+            }
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+          "trial": 3
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+      ]
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+      "trials": [
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+        {
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+          "trial": 2
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+        {
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+          "trial": 3
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+      ]
+    },
+    "tp4_mns8": {
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+          "trial": 1
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+          "trial": 2
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+          "trial": 3
+        }
+      ]
+    }
+  },
+  "prefill_only": true,
+  "schema": "qwen30-latency-case-real-audit-v1",
+  "trace_manifests": {
+    "tp1": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 1.125,
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+      "private_jsonl_sha256": "eb048c65428f2530bdea135e6607405fd7ebaefb103267daaec29839462aa3ab",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-po/tp1/public/frontier.csv",
+      "public_csv_sha256": "82c186222779c4a176f18e425d371966012ca7c1c6560f13d2c7036ac4f38d86",
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+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 1
+    },
+    "tp2": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 2.25,
+      "last_arrival_s": 113.77777777777777,
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+      "private_jsonl_sha256": "aa61aed87875ed792c37efdd62bfeee4753bd3de110a1de92fa32273be13ca12",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-po/tp2/public/frontier.csv",
+      "public_csv_sha256": "b32676281c8f5651f47ee3d88a88d433a01a0863d8794751d2d638b988e1b8b2",
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+      "schema": "qwen30-latency-case-v1",
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+    },
+    "tp4": {
+      "description": "fixed-shape: deterministic token IDs, uniform TP-normalized QPS, no prefix reuse",
+      "first_arrival_s": 0.0,
+      "global_offered_request_rate": 4.5,
+      "last_arrival_s": 56.888888888888886,
+      "output_tokens": [
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+      "per_gpu_offered_request_rate": 1.125,
+      "prefix_caching": false,
+      "private_jsonl": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-po/tp4/private/real_requests.jsonl",
+      "private_jsonl_sha256": "b82a17cd707c3c54069298b764031a1c18775571aa6e54c55be0746dd1fe94ca",
+      "public_csv": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-po/tp4/public/frontier.csv",
+      "public_csv_sha256": "67429bf430436a23979a0007707a03f4c67af962b9466cd230294a3c62696931",
+      "requests": 257,
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+      "schema": "qwen30-latency-case-v1",
+      "tensor_parallel_size": 4
+    }
+  },
+  "traces_root": "/home/admin/cpfs/wjh/aituner/qwen30-fixed-pressure-surface-20260719-r1/traces/fixed-po",
+  "winners": {
+    "e2e_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 113.43910740842456
+    },
+    "e2e_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 114.73881592974067
+    },
+    "ttft_ms:pooled_mean_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 113.39516492515813
+    },
+    "ttft_ms:pooled_p90_ms": {
+      "ranking": [
+        "tp4_mns32",
+        "tp4_mns8",
+        "tp4_mns64",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp2_mns64",
+        "tp2_mns32",
+        "tp2_mns16",
+        "tp1_mns32",
+        "tp1_mns16",
+        "tp1_mns64",
+        "tp1_mns8"
+      ],
+      "winner": "tp4_mns32",
+      "winner_value_ms": 114.69435307662934
+    }
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.md
new file mode 100644
index 0000000..44d6ecb
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-fixed-hi/fixed-po/real-audit.md
@@ -0,0 +1,10 @@
+# Qwen30 real latency case audit
+
+Prefill-only: `True`.
+
+| Objective | Real winner | Value (ms) |
+|---|---|---:|
+| ttft_ms:pooled_mean_ms | tp4_mns32 | 113.40 |
+| ttft_ms:pooled_p90_ms | tp4_mns32 | 114.69 |
+| e2e_ms:pooled_mean_ms | tp4_mns32 | 113.44 |
+| e2e_ms:pooled_p90_ms | tp4_mns32 | 114.74 |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.json
new file mode 100644
index 0000000..f07a37a
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.json
@@ -0,0 +1,726 @@
+{
+  "cells": {
+    "tp1_mns16": {
+      "config": "tp1_mns16",
+      "elapsed_seconds": 351.88990092277527,
+      "metrics": {
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+          "p90_ratio_sim_over_real": 13.072241203568879,
+          "real_mean_ms": 87355.16047904849,
+          "real_p90_ms": 156177.17167094816,
+          "sim_mean_ms": 1209178.7470715286,
+          "sim_p90_ms": 2041585.6585738186
+        },
+        "tpot_ms": {
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+          "real_mean_ms": 20.58492915882586,
+          "real_p90_ms": 25.316827059621797,
+          "sim_mean_ms": 99.14789585006503,
+          "sim_p90_ms": 102.85568630062728
+        },
+        "ttft_ms": {
+          "mean_ratio_sim_over_real": 50.0951473194418,
+          "p90_ratio_sim_over_real": 40.15634837465801,
+          "real_mean_ms": 17378.17525871318,
+          "real_p90_ms": 42739.809082006104,
+          "sim_mean_ms": 870562.2497283154,
+          "sim_p90_ms": 1716274.6629634094
+        }
+      },
+      "mns": 16,
+      "offered_request_rate": 0.215,
+      "offered_request_rate_per_gpu": 0.215,
+      "request_count": 129,
+      "result_path": "/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2/runs/tp1_mns16/tp1/result.json",
+      "result_sha256": "d892cbc79c7ac3a2158310d346aea87fdd4a4515ada6465d02087066e412fe89",
+      "tp": 1,
+      "trace_label": "tp1",
+      "trace_sha256": "0014176c946a4c838f2ba127915fda8f2728e8cbfed070a001800b2f02f02d2a"
+    },
+    "tp1_mns32": {
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+      "elapsed_seconds": 342.20933651924133,
+      "metrics": {
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+          "sim_mean_ms": 722298.9236327951,
+          "sim_p90_ms": 1272056.614352521
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+          "real_p90_ms": 29.99736783063116,
+          "sim_mean_ms": 119.5865393985106,
+          "sim_p90_ms": 125.1721669939102
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+        "ttft_ms": {
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+          "real_p90_ms": 1931.474626995623,
+          "sim_mean_ms": 316980.6268626798,
+          "sim_p90_ms": 743175.4797517607
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+      "offered_request_rate": 0.215,
+      "offered_request_rate_per_gpu": 0.215,
+      "request_count": 129,
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+      "tp": 1,
+      "trace_label": "tp1",
+      "trace_sha256": "0014176c946a4c838f2ba127915fda8f2728e8cbfed070a001800b2f02f02d2a"
+    },
+    "tp1_mns64": {
+      "config": "tp1_mns64",
+      "elapsed_seconds": 347.8728907108307,
+      "metrics": {
+        "e2e_ms": {
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+          "p90_ratio_sim_over_real": 5.889817911531751,
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+          "real_p90_ms": 165355.2623600699,
+          "sim_mean_ms": 549486.0041057414,
+          "sim_p90_ms": 973912.3860143718
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+        "tpot_ms": {
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+          "p90_ratio_sim_over_real": 4.93808404053013,
+          "real_mean_ms": 24.114592194742286,
+          "real_p90_ms": 30.355145227612027,
+          "sim_mean_ms": 137.83117802373562,
+          "sim_p90_ms": 149.8962581964453
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+        "ttft_ms": {
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+          "p90_ratio_sim_over_real": 153.2295314740789,
+          "real_mean_ms": 619.7960944975623,
+          "real_p90_ms": 1956.7296199966222,
+          "sim_mean_ms": 105003.31385062331,
+          "sim_p90_ms": 299828.76289353485
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+      "request_count": 129,
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+      "result_sha256": "a870a95f9f088e0c098025d3d7d4001409b28ab26f8633ff27ea878d2bbd50d2",
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+      "trace_label": "tp1",
+      "trace_sha256": "0014176c946a4c838f2ba127915fda8f2728e8cbfed070a001800b2f02f02d2a"
+    },
+    "tp1_mns8": {
+      "config": "tp1_mns8",
+      "elapsed_seconds": 369.526850938797,
+      "metrics": {
+        "e2e_ms": {
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+        "tp4_mns64",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp1_mns8",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns8",
+      "tied_pairs": 0,
+      "winner_match": true
+    },
+    "tpot_ms:p90": {
+      "concordant_pairs": 64,
+      "discordant_pairs": 2,
+      "informative_pairs": 66,
+      "pairwise_agreement_fraction": 0.9696969696969697,
+      "real_ranking": [
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp2_mns8",
+        "tp4_mns32",
+        "tp4_mns64",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp2_mns32",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "real_winner": "tp4_mns8",
+      "sim_ranking": [
+        "tp4_mns8",
+        "tp4_mns16",
+        "tp4_mns32",
+        "tp2_mns8",
+        "tp4_mns64",
+        "tp2_mns16",
+        "tp2_mns32",
+        "tp1_mns8",
+        "tp2_mns64",
+        "tp1_mns16",
+        "tp1_mns32",
+        "tp1_mns64"
+      ],
+      "sim_winner": "tp4_mns8",
+      "tied_pairs": 0,
+      "winner_match": true
+    },
+    "ttft_ms:mean": {
+      "concordant_pairs": 56,
+      "discordant_pairs": 10,
+      "informative_pairs": 66,
+      "pairwise_agreement_fraction": 0.8484848484848485,
+      "real_ranking": [
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp1_mns32",
+        "tp2_mns32",
+        "tp4_mns32",
+        "tp1_mns16",
+        "tp2_mns16",
+        "tp4_mns16",
+        "tp1_mns8",
+        "tp2_mns8",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp4_mns64",
+      "sim_ranking": [
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp2_mns32",
+        "tp1_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp4_mns8",
+        "tp1_mns16",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns64",
+      "tied_pairs": 0,
+      "winner_match": true
+    },
+    "ttft_ms:p90": {
+      "concordant_pairs": 56,
+      "discordant_pairs": 10,
+      "informative_pairs": 66,
+      "pairwise_agreement_fraction": 0.8484848484848485,
+      "real_ranking": [
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp1_mns32",
+        "tp1_mns64",
+        "tp2_mns32",
+        "tp4_mns32",
+        "tp1_mns16",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp1_mns8",
+        "tp2_mns8",
+        "tp4_mns8"
+      ],
+      "real_winner": "tp4_mns64",
+      "sim_ranking": [
+        "tp4_mns64",
+        "tp2_mns64",
+        "tp1_mns64",
+        "tp4_mns32",
+        "tp2_mns32",
+        "tp1_mns32",
+        "tp4_mns16",
+        "tp2_mns16",
+        "tp4_mns8",
+        "tp1_mns16",
+        "tp2_mns8",
+        "tp1_mns8"
+      ],
+      "sim_winner": "tp4_mns64",
+      "tied_pairs": 0,
+      "winner_match": true
+    }
+  },
+  "sim_root": "/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2"
+}
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.md b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.md
new file mode 100644
index 0000000..83f66a7
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/comparison.md
@@ -0,0 +1,29 @@
+# Frontier piecewise graph-profile vs. real vLLM
+
+Each cell uses its TP-normalized, 129-request trace. Frontier values are one deterministic simulation; real values pool three fresh-server trials (387 requests/cell).
+
+| Config | TTFT sim / real mean (ms) | TPOT sim / real mean (ms) | E2E sim / real mean (ms) |
+|---|---:|---:|---:|
+| tp1_mns8 | 1669003.8 / 88479.9 | 76.0 / 14.3 | 1930772.9 / 137996.4 |
+| tp1_mns16 | 870562.2 / 17378.2 | 99.1 / 20.6 | 1209178.7 / 87355.2 |
+| tp1_mns32 | 316980.6 / 620.5 | 119.6 / 23.8 | 722298.9 / 81051.2 |
+| tp1_mns64 | 105003.3 / 619.8 | 137.8 / 24.1 | 549486.0 / 82253.7 |
+| tp2_mns8 | 1171654.6 / 95920.1 | 51.1 / 9.2 | 1348614.2 / 128296.9 |
+| tp2_mns16 | 606885.2 / 34443.0 | 64.4 / 14.1 | 828082.5 / 82936.7 |
+| tp2_mns32 | 224495.4 / 1050.6 | 74.8 / 18.0 | 479340.1 / 62267.5 |
+| tp2_mns64 | 30524.5 / 375.8 | 82.6 / 18.2 | 311160.1 / 62353.6 |
+| tp4_mns8 | 834500.2 / 102605.9 | 35.4 / 6.8 | 957838.5 / 126405.4 |
+| tp4_mns16 | 429098.7 / 35042.6 | 43.2 / 8.8 | 578209.7 / 65779.1 |
+| tp4_mns32 | 166734.5 / 6296.2 | 49.4 / 12.2 | 336309.9 / 47944.5 |
+| tp4_mns64 | 26688.5 / 246.0 | 53.7 / 13.2 | 209788.3 / 44985.1 |
+
+## Selection agreement
+
+| Target | Frontier winner | Real winner | Match | Pairwise agreement |
+|---|---|---|---:|---:|
+| ttft_ms:mean | tp4_mns64 | tp4_mns64 | yes | 84.8% (56/66) |
+| ttft_ms:p90 | tp4_mns64 | tp4_mns64 | yes | 84.8% (56/66) |
+| tpot_ms:mean | tp4_mns8 | tp4_mns8 | yes | 97.0% (64/66) |
+| tpot_ms:p90 | tp4_mns8 | tp4_mns8 | yes | 97.0% (64/66) |
+| e2e_ms:mean | tp4_mns64 | tp4_mns64 | yes | 92.4% (61/66) |
+| e2e_ms:p90 | tp4_mns64 | tp4_mns64 | yes | 83.3% (55/66) |
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/launch.log b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/launch.log
new file mode 100644
index 0000000..4b641d8
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/launch.log
@@ -0,0 +1,2 @@
+ANALYSIS_LAUNCH_ECHO sim_root=/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2 real_audit=/home/admin/cpfs/wjh/aituner/simulator-tuning-latency-q30-tp-normalized-u0p01-20260717/qwen30-tracepd-u0p01-real-audit.json outputs=/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2/analysis expected=12 completed cells, rank+latency comparison
+ANALYSIS_RETRY_ECHO sim_root=/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2 real_audit_sha256=6e2c17bce5b0edb5f6f92aae4cc1b00f9390f692d31d059efe647158b386c8e9 output=/home/admin/cpfs/wjh/aituner/graph-piecewise-qwen30-20260717/simulator-piecewise-surface-v2/analysis
diff --git a/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/summary.json b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/summary.json
new file mode 100644
index 0000000..7ffaba6
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/frozen-inputs/q30-trace-pd/summary.json
@@ -0,0 +1,230 @@
+{
+  "e2e_ms:mean": {
+    "concordant_pairs": 61,
+    "discordant_pairs": 5,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.9242424242424242,
+    "real_ranking": [
+      "tp4_mns64",
+      "tp4_mns32",
+      "tp2_mns32",
+      "tp2_mns64",
+      "tp4_mns16",
+      "tp1_mns32",
+      "tp1_mns64",
+      "tp2_mns16",
+      "tp1_mns16",
+      "tp4_mns8",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "real_winner": "tp4_mns64",
+    "sim_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp4_mns32",
+      "tp2_mns32",
+      "tp1_mns64",
+      "tp4_mns16",
+      "tp1_mns32",
+      "tp2_mns16",
+      "tp4_mns8",
+      "tp1_mns16",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "sim_winner": "tp4_mns64",
+    "tied_pairs": 0,
+    "winner_match": true
+  },
+  "e2e_ms:p90": {
+    "concordant_pairs": 55,
+    "discordant_pairs": 11,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.8333333333333334,
+    "real_ranking": [
+      "tp4_mns64",
+      "tp4_mns32",
+      "tp4_mns16",
+      "tp2_mns32",
+      "tp2_mns64",
+      "tp2_mns16",
+      "tp1_mns16",
+      "tp1_mns32",
+      "tp1_mns64",
+      "tp4_mns8",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "real_winner": "tp4_mns64",
+    "sim_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp4_mns32",
+      "tp2_mns32",
+      "tp1_mns64",
+      "tp4_mns16",
+      "tp1_mns32",
+      "tp2_mns16",
+      "tp4_mns8",
+      "tp1_mns16",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "sim_winner": "tp4_mns64",
+    "tied_pairs": 0,
+    "winner_match": true
+  },
+  "tpot_ms:mean": {
+    "concordant_pairs": 64,
+    "discordant_pairs": 2,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.9696969696969697,
+    "real_ranking": [
+      "tp4_mns8",
+      "tp4_mns16",
+      "tp2_mns8",
+      "tp4_mns32",
+      "tp4_mns64",
+      "tp2_mns16",
+      "tp1_mns8",
+      "tp2_mns32",
+      "tp2_mns64",
+      "tp1_mns16",
+      "tp1_mns32",
+      "tp1_mns64"
+    ],
+    "real_winner": "tp4_mns8",
+    "sim_ranking": [
+      "tp4_mns8",
+      "tp4_mns16",
+      "tp4_mns32",
+      "tp2_mns8",
+      "tp4_mns64",
+      "tp2_mns16",
+      "tp2_mns32",
+      "tp1_mns8",
+      "tp2_mns64",
+      "tp1_mns16",
+      "tp1_mns32",
+      "tp1_mns64"
+    ],
+    "sim_winner": "tp4_mns8",
+    "tied_pairs": 0,
+    "winner_match": true
+  },
+  "tpot_ms:p90": {
+    "concordant_pairs": 64,
+    "discordant_pairs": 2,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.9696969696969697,
+    "real_ranking": [
+      "tp4_mns8",
+      "tp4_mns16",
+      "tp2_mns8",
+      "tp4_mns32",
+      "tp4_mns64",
+      "tp2_mns16",
+      "tp1_mns8",
+      "tp2_mns32",
+      "tp2_mns64",
+      "tp1_mns16",
+      "tp1_mns32",
+      "tp1_mns64"
+    ],
+    "real_winner": "tp4_mns8",
+    "sim_ranking": [
+      "tp4_mns8",
+      "tp4_mns16",
+      "tp4_mns32",
+      "tp2_mns8",
+      "tp4_mns64",
+      "tp2_mns16",
+      "tp2_mns32",
+      "tp1_mns8",
+      "tp2_mns64",
+      "tp1_mns16",
+      "tp1_mns32",
+      "tp1_mns64"
+    ],
+    "sim_winner": "tp4_mns8",
+    "tied_pairs": 0,
+    "winner_match": true
+  },
+  "ttft_ms:mean": {
+    "concordant_pairs": 56,
+    "discordant_pairs": 10,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.8484848484848485,
+    "real_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp1_mns64",
+      "tp1_mns32",
+      "tp2_mns32",
+      "tp4_mns32",
+      "tp1_mns16",
+      "tp2_mns16",
+      "tp4_mns16",
+      "tp1_mns8",
+      "tp2_mns8",
+      "tp4_mns8"
+    ],
+    "real_winner": "tp4_mns64",
+    "sim_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp1_mns64",
+      "tp4_mns32",
+      "tp2_mns32",
+      "tp1_mns32",
+      "tp4_mns16",
+      "tp2_mns16",
+      "tp4_mns8",
+      "tp1_mns16",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "sim_winner": "tp4_mns64",
+    "tied_pairs": 0,
+    "winner_match": true
+  },
+  "ttft_ms:p90": {
+    "concordant_pairs": 56,
+    "discordant_pairs": 10,
+    "informative_pairs": 66,
+    "pairwise_agreement_fraction": 0.8484848484848485,
+    "real_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp1_mns32",
+      "tp1_mns64",
+      "tp2_mns32",
+      "tp4_mns32",
+      "tp1_mns16",
+      "tp4_mns16",
+      "tp2_mns16",
+      "tp1_mns8",
+      "tp2_mns8",
+      "tp4_mns8"
+    ],
+    "real_winner": "tp4_mns64",
+    "sim_ranking": [
+      "tp4_mns64",
+      "tp2_mns64",
+      "tp1_mns64",
+      "tp4_mns32",
+      "tp2_mns32",
+      "tp1_mns32",
+      "tp4_mns16",
+      "tp2_mns16",
+      "tp4_mns8",
+      "tp1_mns16",
+      "tp2_mns8",
+      "tp1_mns8"
+    ],
+    "sim_winner": "tp4_mns64",
+    "tied_pairs": 0,
+    "winner_match": true
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/results/decision-pair-axis.png b/runs/frontier-split-rootcause-v0/results/decision-pair-axis.png
new file mode 100644
index 0000000..6d0bc0b
Binary files /dev/null and b/runs/frontier-split-rootcause-v0/results/decision-pair-axis.png differ
diff --git a/runs/frontier-split-rootcause-v0/results/decomposition.json b/runs/frontier-split-rootcause-v0/results/decomposition.json
new file mode 100644
index 0000000..d96b226
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/results/decomposition.json
@@ -0,0 +1,7410 @@
+{
+  "anomalies": [],
+  "cross_checks": [
+    {
+      "expected_percent": 58.0,
+      "name": "q30 high-pressure fixed-pd TTFT mean regret",
+      "observed_percent": 57.97674051508896,
+      "passed": true
+    },
+    {
+      "expected_percent": 33.0,
+      "name": "q235 A0 fixed-pd TPOT mean regret",
+      "observed_percent": 33.025510615656906,
+      "passed": true
+    },
+    {
+      "expected_percent": 33.0,
+      "name": "q235 A1 fixed-pd TPOT mean regret",
+      "observed_percent": 33.025510615656906,
+      "passed": true
+    },
+    {
+      "expected_percent": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "name": "q30 trace-pd all-objective regret",
+      "observed_percent": [
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0,
+        0.0
+      ],
+      "passed": true
+    },
+    {
+      "expected_percent": [
+        21.2,
+        0.3
+      ],
+      "name": "q235 Trace-PO TTFT p90 A0 to A1 regret",
+      "observed_percent": [
+        21.17895828808376,
+        0.2607797240047338
+      ],
+      "passed": true
+    },
+    {
+      "expected_percent": [
+        33.0,
+        37.2,
+        30.7,
+        34.6,
+        33.0,
+        37.2,
+        30.7,
+        34.6
+      ],
+      "name": "q235 Fixed-PD TPOT/E2E regrets unchanged from A0 to A1",
+      "observed_percent": [
+        33.025510615656906,
+        37.228890038064755,
+        30.67524317507717,
+        34.56375801249614,
+        33.025510615656906,
+        37.228890038064755,
+        30.67524317507717,
+        34.56375801249614
+      ],
+      "passed": true
+    }
+  ],
+  "data_gaps": [],
+  "definitions": {
+    "config_uniform_scale": "geomean_c(sim_c / real_c) over paired configs",
+    "failure": "regret > 0.05",
+    "fragile_success": "winner match and real best-vs-second relative margin < 0.01",
+    "h_scale_verdict": "HOLDS iff failure equals (top-3 log-ratio spread > log1p(real relative margin))",
+    "log_ratio_spread_all": "max_c(log(sim_c / real_c)) - min_c(log(sim_c / real_c))",
+    "log_ratio_spread_real_top3": "log-ratio spread over the three configs with lowest real objective values",
+    "objective_direction": "all objectives are minimized",
+    "pair_inversion": "real_c > real_w and sim_c < sim_w, equivalently delta_c < -m_c",
+    "real_pair_margin_percent": "100 * log(real_c / real_w)",
+    "real_relative_margin_best_vs_second": "real_second / real_best - 1",
+    "regret": "real_sim_winner / real_best - 1, recomputed from per-config values",
+    "signed_pairwise_delta_percent": "100 * (log(sim_c / sim_w) - log(real_c / real_w)); negative favors c relative to real",
+    "winner_deciding_axis": "axis difference between real winner w and sim winner s; none for a winner match",
+    "winner_pair_tie": "sim_s == sim_w with real_s > real_w; a decision-boundary winner-label mismatch, not a strict inversion"
+  },
+  "directional_summary": {
+    "axis_inversions_by_case": [
+      {
+        "case": "q30 trace-pd",
+        "n_inv_mixed": 0,
+        "n_inv_mns": 0,
+        "n_inv_tp": 0,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 0,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q30 fixed-pd high",
+        "n_inv_mixed": 6,
+        "n_inv_mns": 3,
+        "n_inv_tp": 7,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 0,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q30 fixed-po high",
+        "n_inv_mixed": 0,
+        "n_inv_mns": 0,
+        "n_inv_tp": 0,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 4,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q30 fixed-pd low",
+        "n_inv_mixed": 24,
+        "n_inv_mns": 0,
+        "n_inv_tp": 8,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 0,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q30 fixed-po low",
+        "n_inv_mixed": 0,
+        "n_inv_mns": 0,
+        "n_inv_tp": 0,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 4,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q30 trace-po low",
+        "n_inv_mixed": 0,
+        "n_inv_mns": 6,
+        "n_inv_tp": 0,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 2,
+        "n_tie_tp": 0
+      },
+      {
+        "case": "q235 A0 fixed-pd",
+        "n_inv_mixed": 5,
+        "n_inv_mns": 0,
+        "n_inv_tp": 5,
+        "n_tie_mixed": 0,
+        "n_tie_mns": 1,
+        "n_tie_tp": 0
+      },
+      {
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+      {
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+        "winner_pair_delta_s_percent": -60.056263771346096,
+        "winner_pair_m_s_percent": 28.537073298091865
+      },
+      {
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+      {
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+      {
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+        "winner_pair_m_s_percent": 6.030894994380943
+      }
+    ],
+    "sim_tie_winner_mismatch_count": 14,
+    "strict_winner_reversal_count": 33
+  },
+  "known_attribution": {
+    "q235_state": {
+      "components": [
+        {
+          "component": "total",
+          "exact_state_tp8_minus_tp4_ms": 10.902788634037428,
+          "own_composition_tp8_minus_tp4_ms": -20.06625468177714
+        },
+        {
+          "component": "moe_compute",
+          "exact_state_tp8_minus_tp4_ms": -1.9774463255033616,
+          "own_composition_tp8_minus_tp4_ms": -32.45444243169211
+        },
+        {
+          "component": "attention",
+          "exact_state_tp8_minus_tp4_ms": -2.130420408899373,
+          "own_composition_tp8_minus_tp4_ms": -7.461942625219683
+        },
+        {
+          "component": "tp_dp_communication",
+          "exact_state_tp8_minus_tp4_ms": -6.471757614086094,
+          "own_composition_tp8_minus_tp4_ms": -6.571107062807271
+        },
+        {
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+          "exact_state_tp8_minus_tp4_ms": 6.535508227248577,
+          "own_composition_tp8_minus_tp4_ms": 6.235402017662346
+        },
+        {
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+          "exact_state_tp8_minus_tp4_ms": 0.13840596821076812,
+          "own_composition_tp8_minus_tp4_ms": -0.2861742505642797
+        },
+        {
+          "component": "dense_mlp_compute",
+          "exact_state_tp8_minus_tp4_ms": -0.030752152939768296,
+          "own_composition_tp8_minus_tp4_ms": -0.12314137296116046
+        },
+        {
+          "component": "pipeline_communication",
+          "exact_state_tp8_minus_tp4_ms": 0.0,
+          "own_composition_tp8_minus_tp4_ms": 0.0
+        },
+        {
+          "component": "runtime_overhead",
+          "exact_state_tp8_minus_tp4_ms": 0.0,
+          "own_composition_tp8_minus_tp4_ms": 0.0
+        }
+      ],
+      "configs": [
+        {
+          "config": "tp4_ep1_mns64",
+          "exact_state_coverage": 1.0,
+          "exact_state_matched_sim_ms": 34.25746674314369,
+          "real_exact_decode_batch_mean": 3.8896771904930825,
+          "real_token_weighted_iteration_ms": 18.47097461620307,
+          "sim_own_decode_batch_mean": 13.537037037037036
+        },
+        {
+          "config": "tp8_ep8_mns64",
+          "exact_state_coverage": 1.0,
+          "exact_state_matched_sim_ms": 45.160255377181116,
+          "real_exact_decode_batch_mean": 10.921314741035857,
+          "real_token_weighted_iteration_ms": 27.588699194406445,
+          "sim_own_decode_batch_mean": 18.93782383419689
+        }
+      ],
+      "contrast_decomposition": {
+        "exact_state_matched_tp8_minus_tp4_ms": 10.902788634037428,
+        "residual_vs_exact_iteration_ms": 1.7850640558340523,
+        "residual_vs_frozen_real_tpot_ms": 3.9527886340374287,
+        "simulator_internal_tp8_minus_tp4_ms": -20.06625468177714,
+        "state_composition_shift_ms": 30.969043315814567
+      },
+      "reference": {
+        "exact_iteration_tp8_minus_tp4_ms": 9.117724578203376,
+        "observed_real_tp8_minus_tp4_ms": 6.949999999999999,
+        "real_tpot_ms": {
+          "tp4_ep1_mns64": 21.0442,
+          "tp8_ep8_mns64": 27.9942
+        }
+      },
+      "source": "q235-state-diag/state-diagnosis-exact.json",
+      "verdict": "Exact real state composition flips Frontier to the correct TP4 winner; the ranking error is caused by closed-loop state/composition mismatch, not a conditional stage reversal."
+    },
+    "q30_admission": {
+      "cells": [
+        {
+          "config": "tp2_mns64",
+          "mns": 64,
+          "real_required_slots_upper_bound": 7.548483722821714,
+          "real_ttft_ms": 194.56193759030603,
+          "real_waiting_max": 0,
+          "sim_first_scheduling_wait_ms": 38.22329108338011,
+          "sim_queue_free_ttft_ms": 191.02937373774816,
+          "sim_required_slots": 57.96430802744742,
+          "sim_tpot_over_real": 8.091316956395687,
+          "sim_ttft_ms": 229.2526648211283
+        },
+        {
+          "config": "tp4_mns16",
+          "mns": 16,
+          "real_required_slots_upper_bound": 14.637597063342735,
+          "real_ttft_ms": 124.49453797538061,
+          "real_waiting_max": 0,
+          "sim_first_scheduling_wait_ms": 64906.25631809643,
+          "sim_queue_free_ttft_ms": 134.74066995065758,
+          "sim_required_slots": 54.488824675063235,
+          "sim_tpot_over_real": 3.8276349505907024,
+          "sim_ttft_ms": 65040.99698804708
+        },
+        {
+          "config": "tp4_mns32",
+          "mns": 32,
+          "real_required_slots_upper_bound": 14.521569587596273,
+          "real_ttft_ms": 123.15859724408143,
+          "real_waiting_max": 0,
+          "sim_first_scheduling_wait_ms": 27180.676177927482,
+          "sim_queue_free_ttft_ms": 135.62147333612225,
+          "sim_required_slots": 65.89386162288272,
+          "sim_tpot_over_real": 4.6740581573385525,
+          "sim_ttft_ms": 27316.2976512636
+        },
+        {
+          "config": "tp4_mns64",
+          "mns": 64,
+          "real_required_slots_upper_bound": 14.661911968825338,
+          "real_ttft_ms": 123.17715882596677,
+          "real_waiting_max": 0,
+          "sim_first_scheduling_wait_ms": 6367.273779218055,
+          "sim_queue_free_ttft_ms": 136.7304324624105,
+          "sim_required_slots": 79.81630813400574,
+          "sim_tpot_over_real": 5.614117914776633,
+          "sim_ttft_ms": 6504.004211680465
+        }
+      ],
+      "contrasts": {
+        "observed_sim_ttft_tp4_minus_tp2_ms": 27087.044986442474,
+        "queue_free_sim_ttft_tp4_minus_tp2_ms": -55.40790040162591,
+        "real_ttft_tp4_minus_tp2_ms": -71.4033403462246
+      },
+      "source": "q30-admission-diag/result.json",
+      "verdict": "Frontier overpredicts decode service time, so TP4's higher global arrival rate crosses the MNS admission cap only in simulation. The resulting first-scheduling queue reverses the TP topology ranking; without that queue Frontier itself predicts TP4 faster than TP2, matching real hardware."
+    }
+  },
+  "rows": [
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+      "missing_configs": [],
+      "n_inv_mixed": 0,
+      "n_inv_mns": 1,
+      "n_inv_tp": 0,
+      "n_tie_mixed": 0,
+      "n_tie_mns": 0,
+      "n_tie_tp": 0,
+      "objective": "e2e_p90_ms",
+      "paired_config_count": 4,
+      "pairwise_vs_real_winner": [
+        {
+          "axis_vs_real_winner": "mixed",
+          "config": "tp4_ep1_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 13.943039926940672,
+          "signed_pairwise_delta_percent": 29.838662224128264
+        },
+        {
+          "axis_vs_real_winner": "tp-axis",
+          "config": "tp4_ep1_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 10.455222177040667,
+          "signed_pairwise_delta_percent": 32.30699826893181
+        },
+        {
+          "axis_vs_real_winner": "mns-axis",
+          "config": "tp8_ep8_mns128",
+          "inversion": true,
+          "real_pair_margin_percent": 6.030894994380943,
+          "signed_pairwise_delta_percent": -17.372678635438426
+        },
+        {
+          "axis_vs_real_winner": "none",
+          "config": "tp8_ep8_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 0.0,
+          "signed_pairwise_delta_percent": 0.0
+        }
+      ],
+      "real_relative_margin_best_vs_second": 0.062164651568153984,
+      "real_top3_configs": [
+        "tp8_ep8_mns64",
+        "tp8_ep8_mns128",
+        "tp4_ep1_mns64"
+      ],
+      "real_winner": "tp8_ep8_mns64",
+      "regret": 0.062164651568153984,
+      "sim_winner": "tp8_ep8_mns128",
+      "sim_winner_real_relative_loss": 0.062164651568153984,
+      "sources": [
+        "q235-ablation-a1/comparison.json"
+      ],
+      "winner_deciding_axis": "mns-axis",
+      "winner_match": false,
+      "winner_pair_delta_s_percent": -17.372678635438426,
+      "winner_pair_m_s_percent": 6.030894994380943,
+      "winner_pair_relation": "reversal",
+      "winner_pair_strict_reversal": true
+    },
+    {
+      "case": "q235 A1 trace-po",
+      "config_uniform_scale": 0.5481032351618105,
+      "expected_config_count": 4,
+      "failure": false,
+      "fragile_success": false,
+      "h_scale_condition_spread_gt_log_margin": true,
+      "h_scale_verdict": "COUNTEREXAMPLE",
+      "log_ratio_spread_all": 0.3220111524478986,
+      "log_ratio_spread_real_top3": 0.3220111524478986,
+      "missing_configs": [],
+      "n_inv_mixed": 0,
+      "n_inv_mns": 1,
+      "n_inv_tp": 0,
+      "n_tie_mixed": 0,
+      "n_tie_mns": 0,
+      "n_tie_tp": 0,
+      "objective": "ttft_mean_ms",
+      "paired_config_count": 4,
+      "pairwise_vs_real_winner": [
+        {
+          "axis_vs_real_winner": "tp-axis",
+          "config": "tp4_ep1_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 5.119345640134235,
+          "signed_pairwise_delta_percent": 30.823724522814285
+        },
+        {
+          "axis_vs_real_winner": "mixed",
+          "config": "tp4_ep1_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 6.802653056521642,
+          "signed_pairwise_delta_percent": 29.107141724120687
+        },
+        {
+          "axis_vs_real_winner": "none",
+          "config": "tp8_ep8_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 0.0,
+          "signed_pairwise_delta_percent": 0.0
+        },
+        {
+          "axis_vs_real_winner": "mns-axis",
+          "config": "tp8_ep8_mns64",
+          "inversion": true,
+          "real_pair_margin_percent": 1.3657297298272386,
+          "signed_pairwise_delta_percent": -1.3773907219755823
+        }
+      ],
+      "real_relative_margin_best_vs_second": 0.013750984200462835,
+      "real_top3_configs": [
+        "tp8_ep8_mns128",
+        "tp8_ep8_mns64",
+        "tp4_ep1_mns128"
+      ],
+      "real_winner": "tp8_ep8_mns128",
+      "regret": 0.013750984200462835,
+      "sim_winner": "tp8_ep8_mns64",
+      "sim_winner_real_relative_loss": 0.013750984200462835,
+      "sources": [
+        "q235-ablation-a1/comparison.json"
+      ],
+      "winner_deciding_axis": "mns-axis",
+      "winner_match": false,
+      "winner_pair_delta_s_percent": -1.3773907219755823,
+      "winner_pair_m_s_percent": 1.3657297298272386,
+      "winner_pair_relation": "reversal",
+      "winner_pair_strict_reversal": true
+    },
+    {
+      "case": "q235 A1 trace-po",
+      "config_uniform_scale": 0.5678289728094312,
+      "expected_config_count": 4,
+      "failure": false,
+      "fragile_success": false,
+      "h_scale_condition_spread_gt_log_margin": true,
+      "h_scale_verdict": "COUNTEREXAMPLE",
+      "log_ratio_spread_all": 0.31919899251598766,
+      "log_ratio_spread_real_top3": 0.31919899251598766,
+      "missing_configs": [],
+      "n_inv_mixed": 0,
+      "n_inv_mns": 0,
+      "n_inv_tp": 0,
+      "n_tie_mixed": 0,
+      "n_tie_mns": 1,
+      "n_tie_tp": 0,
+      "objective": "ttft_p90_ms",
+      "paired_config_count": 4,
+      "pairwise_vs_real_winner": [
+        {
+          "axis_vs_real_winner": "mixed",
+          "config": "tp4_ep1_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 19.209826109044702,
+          "signed_pairwise_delta_percent": 31.659458967916663
+        },
+        {
+          "axis_vs_real_winner": "tp-axis",
+          "config": "tp4_ep1_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 19.400420037632387,
+          "signed_pairwise_delta_percent": 31.468865039328982
+        },
+        {
+          "axis_vs_real_winner": "mns-axis",
+          "config": "tp8_ep8_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 0.26044028368209854,
+          "signed_pairwise_delta_percent": -0.26044028368209854
+        },
+        {
+          "axis_vs_real_winner": "none",
+          "config": "tp8_ep8_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 0.0,
+          "signed_pairwise_delta_percent": 0.0
+        }
+      ],
+      "real_relative_margin_best_vs_second": 0.002607797240047338,
+      "real_top3_configs": [
+        "tp8_ep8_mns64",
+        "tp8_ep8_mns128",
+        "tp4_ep1_mns128"
+      ],
+      "real_winner": "tp8_ep8_mns64",
+      "regret": 0.002607797240047338,
+      "sim_winner": "tp8_ep8_mns128",
+      "sim_winner_real_relative_loss": 0.002607797240047338,
+      "sources": [
+        "q235-ablation-a1/comparison.json"
+      ],
+      "winner_deciding_axis": "mns-axis",
+      "winner_match": false,
+      "winner_pair_delta_s_percent": -0.26044028368209854,
+      "winner_pair_m_s_percent": 0.26044028368209854,
+      "winner_pair_relation": "sim-tie",
+      "winner_pair_strict_reversal": false
+    },
+    {
+      "case": "q235 A1 trace-po",
+      "config_uniform_scale": 0.548058912389237,
+      "expected_config_count": 4,
+      "failure": false,
+      "fragile_success": false,
+      "h_scale_condition_spread_gt_log_margin": true,
+      "h_scale_verdict": "COUNTEREXAMPLE",
+      "log_ratio_spread_all": 0.32202928326406854,
+      "log_ratio_spread_real_top3": 0.32202928326406854,
+      "missing_configs": [],
+      "n_inv_mixed": 0,
+      "n_inv_mns": 1,
+      "n_inv_tp": 0,
+      "n_tie_mixed": 0,
+      "n_tie_mns": 0,
+      "n_tie_tp": 0,
+      "objective": "e2e_mean_ms",
+      "paired_config_count": 4,
+      "pairwise_vs_real_winner": [
+        {
+          "axis_vs_real_winner": "tp-axis",
+          "config": "tp4_ep1_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 5.1172644115479695,
+          "signed_pairwise_delta_percent": 30.825805751400548
+        },
+        {
+          "axis_vs_real_winner": "mixed",
+          "config": "tp4_ep1_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 6.800551883155552,
+          "signed_pairwise_delta_percent": 29.109242897486777
+        },
+        {
+          "axis_vs_real_winner": "none",
+          "config": "tp8_ep8_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 0.0,
+          "signed_pairwise_delta_percent": 0.0
+        },
+        {
+          "axis_vs_real_winner": "mns-axis",
+          "config": "tp8_ep8_mns64",
+          "inversion": true,
+          "real_pair_margin_percent": 1.3654615828579657,
+          "signed_pairwise_delta_percent": -1.3771225750063092
+        }
+      ],
+      "real_relative_margin_best_vs_second": 0.0137482658615673,
+      "real_top3_configs": [
+        "tp8_ep8_mns128",
+        "tp8_ep8_mns64",
+        "tp4_ep1_mns128"
+      ],
+      "real_winner": "tp8_ep8_mns128",
+      "regret": 0.0137482658615673,
+      "sim_winner": "tp8_ep8_mns64",
+      "sim_winner_real_relative_loss": 0.0137482658615673,
+      "sources": [
+        "q235-ablation-a1/comparison.json"
+      ],
+      "winner_deciding_axis": "mns-axis",
+      "winner_match": false,
+      "winner_pair_delta_s_percent": -1.3771225750063092,
+      "winner_pair_m_s_percent": 1.3654615828579657,
+      "winner_pair_relation": "reversal",
+      "winner_pair_strict_reversal": true
+    },
+    {
+      "case": "q235 A1 trace-po",
+      "config_uniform_scale": 0.5678075555479308,
+      "expected_config_count": 4,
+      "failure": false,
+      "fragile_success": false,
+      "h_scale_condition_spread_gt_log_margin": true,
+      "h_scale_verdict": "COUNTEREXAMPLE",
+      "log_ratio_spread_all": 0.3192076739943569,
+      "log_ratio_spread_real_top3": 0.3192076739943569,
+      "missing_configs": [],
+      "n_inv_mixed": 0,
+      "n_inv_mns": 0,
+      "n_inv_tp": 0,
+      "n_tie_mixed": 0,
+      "n_tie_mns": 1,
+      "n_tie_tp": 0,
+      "objective": "e2e_p90_ms",
+      "paired_config_count": 4,
+      "pairwise_vs_real_winner": [
+        {
+          "axis_vs_real_winner": "mixed",
+          "config": "tp4_ep1_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 19.20014493069586,
+          "signed_pairwise_delta_percent": 31.669140146265505
+        },
+        {
+          "axis_vs_real_winner": "tp-axis",
+          "config": "tp4_ep1_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 19.390739890554553,
+          "signed_pairwise_delta_percent": 31.478545186406816
+        },
+        {
+          "axis_vs_real_winner": "mns-axis",
+          "config": "tp8_ep8_mns128",
+          "inversion": false,
+          "real_pair_margin_percent": 0.2516272531701875,
+          "signed_pairwise_delta_percent": -0.2516272531701875
+        },
+        {
+          "axis_vs_real_winner": "none",
+          "config": "tp8_ep8_mns64",
+          "inversion": false,
+          "real_pair_margin_percent": 0.0,
+          "signed_pairwise_delta_percent": 0.0
+        }
+      ],
+      "real_relative_margin_best_vs_second": 0.0025194410024500513,
+      "real_top3_configs": [
+        "tp8_ep8_mns64",
+        "tp8_ep8_mns128",
+        "tp4_ep1_mns128"
+      ],
+      "real_winner": "tp8_ep8_mns64",
+      "regret": 0.0025194410024500513,
+      "sim_winner": "tp8_ep8_mns128",
+      "sim_winner_real_relative_loss": 0.0025194410024500513,
+      "sources": [
+        "q235-ablation-a1/comparison.json"
+      ],
+      "winner_deciding_axis": "mns-axis",
+      "winner_match": false,
+      "winner_pair_delta_s_percent": -0.2516272531701875,
+      "winner_pair_m_s_percent": 0.2516272531701875,
+      "winner_pair_relation": "sim-tie",
+      "winner_pair_strict_reversal": false
+    }
+  ],
+  "schema": "frontier-split-rootcause-decomposition-v2",
+  "summary": {
+    "case_count": 14,
+    "data_gap_count": 0,
+    "failure_count": 23,
+    "h_scale_counterexample_count": 40,
+    "h_scale_counterexamples": [
+      {
+        "case": "q30 trace-pd",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q30 trace-pd",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q30 trace-pd",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q30 trace-pd",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q30 fixed-pd high",
+        "objective": "tpot_mean_ms"
+      },
+      {
+        "case": "q30 fixed-pd high",
+        "objective": "tpot_p90_ms"
+      },
+      {
+        "case": "q30 fixed-pd high",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q30 fixed-po high",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q30 fixed-po high",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q30 fixed-po high",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q30 fixed-po high",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q30 fixed-pd low",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q30 fixed-pd low",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q30 fixed-po low",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q30 fixed-po low",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q30 fixed-po low",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q30 fixed-po low",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q30 trace-po low",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q30 trace-po low",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q30 trace-po low",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q30 trace-po low",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q235 A0 fixed-pd",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q235 A0 fixed-pd",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q235 A0 fixed-po",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q235 A0 fixed-po",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q235 A0 trace-pd",
+        "objective": "tpot_mean_ms"
+      },
+      {
+        "case": "q235 A0 trace-pd",
+        "objective": "tpot_p90_ms"
+      },
+      {
+        "case": "q235 A0 trace-pd",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q235 A1 fixed-pd",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q235 A1 fixed-pd",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q235 A1 fixed-po",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q235 A1 fixed-po",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q235 A1 fixed-po",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q235 A1 fixed-po",
+        "objective": "e2e_p90_ms"
+      },
+      {
+        "case": "q235 A1 trace-pd",
+        "objective": "tpot_mean_ms"
+      },
+      {
+        "case": "q235 A1 trace-pd",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q235 A1 trace-po",
+        "objective": "ttft_mean_ms"
+      },
+      {
+        "case": "q235 A1 trace-po",
+        "objective": "ttft_p90_ms"
+      },
+      {
+        "case": "q235 A1 trace-po",
+        "objective": "e2e_mean_ms"
+      },
+      {
+        "case": "q235 A1 trace-po",
+        "objective": "e2e_p90_ms"
+      }
+    ],
+    "row_count": 70,
+    "winner_mismatch_count": 47
+  }
+}
diff --git a/runs/frontier-split-rootcause-v0/results/decomposition.md b/runs/frontier-split-rootcause-v0/results/decomposition.md
new file mode 100644
index 0000000..bac3454
--- /dev/null
+++ b/runs/frontier-split-rootcause-v0/results/decomposition.md
@@ -0,0 +1,301 @@
+# Frontier good/bad split decomposition
+
+All 70 rows are recomputed from frozen per-config JSON values. Lower is better for every objective. `scale` is the geometric mean of `sim/real`; spreads are shown as `100 ×` log-space width, while `real margin` is the ordinary relative difference `100 × (real_second / real_best - 1)`. H-SCALE compares the log-space spread with `log1p(real margin)`, not directly with the ordinary relative margin. The real top-3 neighborhood is selected independently for every row. Directional `m_s` and `delta_s` are already expressed in log-percentage points.
+
+- Rows / case surfaces: 70 / 14.
+- Failures (`regret > 5%`): 23.
+- Exact winner mismatches: 47.
+- H-SCALE counterexamples: 40.
+
+## Unified decomposition
+
+| case | objective | sim winner | real winner | regret | scale | spread all | spread real top-3 | real margin (relative) | sim-winner real loss | failure | H-SCALE | deciding axis | m_s | delta_s | n_inv_tp | n_inv_mns | n_inv_mixed | fragile success |
+|---|---|---|---|---:|---:|---:|---:|---:|---:|---|---|---|---:|---:|---:|---:|---:|---|
+| q30 trace-pd | ttft_mean_ms | tp4_mns64 | tp4_mns64 | 0.0% | 45.900x | 414.0% | 73.5% | 52.8% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 trace-pd | ttft_p90_ms | tp4_mns64 | tp4_mns64 | 0.0% | 43.384x | 386.3% | 136.8% | 67.6% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 trace-pd | tpot_mean_ms | tp4_mns8 | tp4_mns8 | 0.0% | 4.799x | 34.2% | 11.9% | 30.3% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 trace-pd | tpot_p90_ms | tp4_mns8 | tp4_mns8 | 0.0% | 4.291x | 34.9% | 10.9% | 32.9% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 trace-pd | e2e_mean_ms | tp4_mns64 | tp4_mns64 | 0.0% | 8.263x | 109.9% | 50.1% | 6.6% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 trace-pd | e2e_p90_ms | tp4_mns64 | tp4_mns64 | 0.0% | 8.066x | 123.0% | 70.3% | 0.1% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q30 fixed-pd high | ttft_mean_ms | tp2_mns64 | tp4_mns32 | 58.0% | 80.274x | 664.7% | 229.2% | 0.0% | 58.0% | yes | HOLDS | mixed | 45.7% | -523.8% | 2 | 1 | 2 | no |
+| q30 fixed-pd high | ttft_p90_ms | tp2_mns64 | tp4_mns64 | 56.2% | 130.663x | 709.3% | 222.7% | 0.1% | 56.2% | yes | HOLDS | tp-axis | 44.6% | -435.3% | 2 | 0 | 0 | no |
+| q30 fixed-pd high | tpot_mean_ms | tp4_mns8 | tp4_mns8 | 0.0% | 6.313x | 118.1% | 95.7% | 34.4% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 fixed-pd high | tpot_p90_ms | tp4_mns8 | tp4_mns8 | 0.0% | 5.885x | 122.3% | 95.1% | 37.2% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 fixed-pd high | e2e_mean_ms | tp4_mns64 | tp1_mns32 | 1.7% | 18.867x | 226.5% | 111.5% | 0.7% | 1.7% | no | COUNTEREXAMPLE | mixed | 1.7% | -82.6% | 2 | 1 | 2 | no |
+| q30 fixed-pd high | e2e_p90_ms | tp2_mns64 | tp1_mns32 | 5.5% | 24.706x | 274.2% | 172.5% | 1.0% | 5.5% | yes | HOLDS | mixed | 5.3% | -101.7% | 1 | 1 | 2 | no |
+| q30 fixed-po high | ttft_mean_ms | tp4_mns16 | tp4_mns32 | 0.3% | 0.964x | 27.5% | 0.3% | 0.1% | 0.3% | no | COUNTEREXAMPLE | mns-axis | 0.3% | -0.3% | 0 | 0 | 0 | no |
+| q30 fixed-po high | ttft_p90_ms | tp4_mns16 | tp4_mns32 | 0.5% | 0.956x | 26.9% | 0.3% | 0.0% | 0.5% | no | COUNTEREXAMPLE | mns-axis | 0.5% | -0.5% | 0 | 0 | 0 | no |
+| q30 fixed-po high | e2e_mean_ms | tp4_mns16 | tp4_mns32 | 0.3% | 0.964x | 27.5% | 0.3% | 0.1% | 0.3% | no | COUNTEREXAMPLE | mns-axis | 0.3% | -0.3% | 0 | 0 | 0 | no |
+| q30 fixed-po high | e2e_p90_ms | tp4_mns16 | tp4_mns32 | 0.5% | 0.956x | 26.9% | 0.3% | 0.0% | 0.5% | no | COUNTEREXAMPLE | mns-axis | 0.5% | -0.5% | 0 | 0 | 0 | no |
+| q30 fixed-pd low | ttft_mean_ms | tp4_mns16 | tp4_mns16 | 0.0% | 1.368x | 43.8% | 1.5% | 1.3% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 fixed-pd low | ttft_p90_ms | tp4_mns16 | tp4_mns16 | 0.0% | 1.402x | 48.7% | 2.9% | 1.8% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q30 fixed-pd low | tpot_mean_ms | tp1_mns16 | tp4_mns32 | 14.0% | 4.952x | 52.7% | 0.2% | 0.0% | 14.0% | yes | HOLDS | mixed | 13.1% | -52.5% | 2 | 0 | 6 | no |
+| q30 fixed-pd low | tpot_p90_ms | tp1_mns16 | tp4_mns8 | 13.4% | 4.950x | 53.2% | 0.3% | 0.2% | 13.4% | yes | HOLDS | mixed | 12.5% | -52.8% | 2 | 0 | 6 | no |
+| q30 fixed-pd low | e2e_mean_ms | tp1_mns16 | tp4_mns32 | 26.9% | 4.423x | 59.8% | 0.2% | 0.1% | 26.9% | yes | HOLDS | mixed | 23.8% | -59.6% | 2 | 0 | 6 | no |
+| q30 fixed-pd low | e2e_p90_ms | tp1_mns16 | tp4_mns8 | 25.7% | 4.421x | 60.0% | 0.2% | 0.1% | 25.7% | yes | HOLDS | mixed | 22.9% | -59.8% | 2 | 0 | 6 | no |
+| q30 fixed-po low | ttft_mean_ms | tp4_mns16 | tp4_mns8 | 1.5% | 1.218x | 20.9% | 1.1% | 0.3% | 1.5% | no | COUNTEREXAMPLE | mns-axis | 1.5% | -1.5% | 0 | 0 | 0 | no |
+| q30 fixed-po low | ttft_p90_ms | tp4_mns16 | tp4_mns8 | 3.6% | 1.184x | 16.1% | 2.3% | 0.6% | 3.6% | no | COUNTEREXAMPLE | mns-axis | 3.5% | -3.5% | 0 | 0 | 0 | no |
+| q30 fixed-po low | e2e_mean_ms | tp4_mns16 | tp4_mns8 | 1.5% | 1.217x | 20.8% | 1.1% | 0.3% | 1.5% | no | COUNTEREXAMPLE | mns-axis | 1.5% | -1.5% | 0 | 0 | 0 | no |
+| q30 fixed-po low | e2e_p90_ms | tp4_mns16 | tp4_mns8 | 3.6% | 1.183x | 16.0% | 2.4% | 0.7% | 3.6% | no | COUNTEREXAMPLE | mns-axis | 3.5% | -3.5% | 0 | 0 | 0 | no |
+| q30 trace-po low | ttft_mean_ms | tp4_mns16 | tp4_mns64 | 3.2% | 0.657x | 18.2% | 2.6% | 1.7% | 3.2% | no | COUNTEREXAMPLE | mns-axis | 3.1% | -3.1% | 0 | 3 | 0 | no |
+| q30 trace-po low | ttft_p90_ms | tp4_mns16 | tp4_mns8 | 0.4% | 0.478x | 17.7% | 0.2% | 0.2% | 0.4% | no | COUNTEREXAMPLE | mns-axis | 0.4% | -0.4% | 0 | 0 | 0 | no |
+| q30 trace-po low | e2e_mean_ms | tp4_mns16 | tp4_mns64 | 3.2% | 0.657x | 18.2% | 2.6% | 1.7% | 3.2% | no | COUNTEREXAMPLE | mns-axis | 3.1% | -3.1% | 0 | 3 | 0 | no |
+| q30 trace-po low | e2e_p90_ms | tp4_mns16 | tp4_mns8 | 0.3% | 0.478x | 17.7% | 0.2% | 0.1% | 0.3% | no | COUNTEREXAMPLE | mns-axis | 0.3% | -0.3% | 0 | 0 | 0 | no |
+| q235 A0 fixed-pd | ttft_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | 4.2% | 0.991x | 6.1% | 5.0% | 0.4% | 4.2% | no | COUNTEREXAMPLE | tp-axis | 4.1% | -5.0% | 1 | 0 | 1 | no |
+| q235 A0 fixed-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.2% | 1.020x | 2.4% | 2.4% | 0.2% | 0.2% | no | COUNTEREXAMPLE | mns-axis | 0.2% | -0.2% | 0 | 0 | 0 | no |
+| q235 A0 fixed-pd | tpot_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 33.0% | 3.025x | 64.0% | 63.9% | 0.7% | 33.0% | yes | HOLDS | tp-axis | 28.5% | -64.0% | 1 | 0 | 1 | no |
+| q235 A0 fixed-pd | tpot_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 37.2% | 3.062x | 62.9% | 62.8% | 0.3% | 37.2% | yes | HOLDS | tp-axis | 31.6% | -62.8% | 1 | 0 | 1 | no |
+| q235 A0 fixed-pd | e2e_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 30.7% | 2.913x | 61.5% | 61.5% | 0.7% | 30.7% | yes | HOLDS | tp-axis | 26.8% | -61.5% | 1 | 0 | 1 | no |
+| q235 A0 fixed-pd | e2e_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 34.6% | 2.955x | 60.5% | 60.4% | 0.3% | 34.6% | yes | HOLDS | tp-axis | 29.7% | -60.4% | 1 | 0 | 1 | no |
+| q235 A0 fixed-po | ttft_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | 5.9% | 0.964x | 12.1% | 12.0% | 0.2% | 5.9% | yes | HOLDS | tp-axis | 5.7% | -12.0% | 1 | 0 | 1 | no |
+| q235 A0 fixed-po | ttft_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | 1.7% | 0.941x | 8.3% | 8.0% | 0.3% | 1.7% | no | COUNTEREXAMPLE | tp-axis | 1.7% | -8.0% | 1 | 0 | 1 | no |
+| q235 A0 fixed-po | e2e_mean_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | 5.9% | 0.964x | 12.1% | 12.0% | 0.2% | 5.9% | yes | HOLDS | tp-axis | 5.7% | -12.0% | 1 | 0 | 1 | no |
+| q235 A0 fixed-po | e2e_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns128 | 1.7% | 0.941x | 8.3% | 8.0% | 0.3% | 1.7% | no | COUNTEREXAMPLE | tp-axis | 1.7% | -8.0% | 1 | 0 | 1 | no |
+| q235 A0 trace-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 1.493x | 101.6% | 101.6% | 2220.3% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A0 trace-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 1.511x | 96.5% | 96.5% | 3455.8% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A0 trace-pd | tpot_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | 0.0% | 1.340x | 61.5% | 43.1% | 16.8% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A0 trace-pd | tpot_p90_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | 0.0% | 1.281x | 49.4% | 29.8% | 26.3% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A0 trace-pd | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.6% | 1.415x | 69.3% | 69.3% | 0.6% | 0.6% | no | COUNTEREXAMPLE | mns-axis | 0.6% | -18.1% | 0 | 1 | 0 | no |
+| q235 A0 trace-pd | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 6.2% | 1.473x | 71.5% | 71.5% | 6.2% | 6.2% | yes | HOLDS | mns-axis | 6.0% | -16.7% | 0 | 1 | 0 | no |
+| q235 A0 trace-po | ttft_mean_ms | tp4_ep1_mns64 | tp8_ep8_mns128 | 7.0% | 0.753x | 36.3% | 34.6% | 1.4% | 7.0% | yes | HOLDS | mixed | 6.8% | -36.3% | 1 | 1 | 1 | no |
+| q235 A0 trace-po | ttft_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns64 | 21.2% | 0.767x | 31.8% | 31.6% | 0.3% | 21.2% | yes | HOLDS | mixed | 19.2% | -31.6% | 1 | 0 | 1 | no |
+| q235 A0 trace-po | e2e_mean_ms | tp4_ep1_mns64 | tp8_ep8_mns128 | 7.0% | 0.753x | 36.3% | 34.6% | 1.4% | 7.0% | yes | HOLDS | mixed | 6.8% | -36.3% | 1 | 1 | 1 | no |
+| q235 A0 trace-po | e2e_p90_ms | tp4_ep1_mns128 | tp8_ep8_mns64 | 21.2% | 0.766x | 31.8% | 31.6% | 0.3% | 21.2% | yes | HOLDS | mixed | 19.2% | -31.6% | 1 | 0 | 1 | no |
+| q235 A1 fixed-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 0.805x | 26.8% | 26.8% | 0.4% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q235 A1 fixed-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.2% | 0.837x | 30.5% | 30.5% | 0.2% | 0.2% | no | COUNTEREXAMPLE | mns-axis | 0.2% | -0.2% | 0 | 0 | 0 | no |
+| q235 A1 fixed-pd | tpot_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 33.0% | 2.608x | 60.1% | 60.0% | 0.7% | 33.0% | yes | HOLDS | tp-axis | 28.5% | -60.1% | 1 | 0 | 1 | no |
+| q235 A1 fixed-pd | tpot_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 37.2% | 2.587x | 61.2% | 61.1% | 0.3% | 37.2% | yes | HOLDS | tp-axis | 31.6% | -61.1% | 1 | 0 | 1 | no |
+| q235 A1 fixed-pd | e2e_mean_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 30.7% | 2.508x | 58.3% | 58.2% | 0.7% | 30.7% | yes | HOLDS | tp-axis | 26.8% | -58.3% | 1 | 0 | 1 | no |
+| q235 A1 fixed-pd | e2e_p90_ms | tp8_ep8_mns128 | tp4_ep1_mns128 | 34.6% | 2.495x | 59.3% | 59.2% | 0.3% | 34.6% | yes | HOLDS | tp-axis | 29.7% | -59.2% | 1 | 0 | 1 | no |
+| q235 A1 fixed-po | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 0.776x | 24.8% | 24.8% | 0.2% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q235 A1 fixed-po | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 0.757x | 28.9% | 28.9% | 0.3% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q235 A1 fixed-po | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 0.776x | 24.8% | 24.8% | 0.2% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q235 A1 fixed-po | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 0.757x | 28.9% | 28.9% | 0.3% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | yes |
+| q235 A1 trace-pd | ttft_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 1.217x | 154.4% | 154.4% | 2220.3% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A1 trace-pd | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns128 | 0.0% | 1.219x | 151.1% | 151.1% | 3455.8% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A1 trace-pd | tpot_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | 0.0% | 1.338x | 46.7% | 28.2% | 16.8% | 0.0% | no | COUNTEREXAMPLE | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A1 trace-pd | tpot_p90_ms | tp8_ep8_mns64 | tp8_ep8_mns64 | 0.0% | 1.221x | 45.3% | 22.3% | 26.3% | 0.0% | no | HOLDS | none | 0.0% | +0.0% | 0 | 0 | 0 | no |
+| q235 A1 trace-pd | e2e_mean_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.6% | 1.430x | 48.8% | 48.8% | 0.6% | 0.6% | no | COUNTEREXAMPLE | mns-axis | 0.6% | -15.9% | 0 | 1 | 0 | no |
+| q235 A1 trace-pd | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 6.2% | 1.492x | 49.7% | 49.7% | 6.2% | 6.2% | yes | HOLDS | mns-axis | 6.0% | -17.4% | 0 | 1 | 0 | no |
+| q235 A1 trace-po | ttft_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns128 | 1.4% | 0.548x | 32.2% | 32.2% | 1.4% | 1.4% | no | COUNTEREXAMPLE | mns-axis | 1.4% | -1.4% | 0 | 1 | 0 | no |
+| q235 A1 trace-po | ttft_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.3% | 0.568x | 31.9% | 31.9% | 0.3% | 0.3% | no | COUNTEREXAMPLE | mns-axis | 0.3% | -0.3% | 0 | 0 | 0 | no |
+| q235 A1 trace-po | e2e_mean_ms | tp8_ep8_mns64 | tp8_ep8_mns128 | 1.4% | 0.548x | 32.2% | 32.2% | 1.4% | 1.4% | no | COUNTEREXAMPLE | mns-axis | 1.4% | -1.4% | 0 | 1 | 0 | no |
+| q235 A1 trace-po | e2e_p90_ms | tp8_ep8_mns128 | tp8_ep8_mns64 | 0.3% | 0.568x | 31.9% | 31.9% | 0.3% | 0.3% | no | COUNTEREXAMPLE | mns-axis | 0.3% | -0.3% | 0 | 0 | 0 | no |
+
+## H-SCALE verdict
+
+H-SCALE is not sufficient as stated; the following rows are counterexamples to the biconditional:
+
+All 40 observed counterexamples are non-failures with spread > `log1p(margin)`; there are 0 failures with spread <= `log1p(margin)`. Thus the threshold is necessary for the observed failures but not sufficient to predict them.
+
+| case | objective | failure | spread real top-3 | real margin | counterexample type |
+|---|---|---|---:|---:|---|
+| q30 trace-pd | ttft_mean_ms | no | 73.5% | 52.8% | non-failure with spread > log1p(margin) |
+| q30 trace-pd | ttft_p90_ms | no | 136.8% | 67.6% | non-failure with spread > log1p(margin) |
+| q30 trace-pd | e2e_mean_ms | no | 50.1% | 6.6% | non-failure with spread > log1p(margin) |
+| q30 trace-pd | e2e_p90_ms | no | 70.3% | 0.1% | non-failure with spread > log1p(margin) |
+| q30 fixed-pd high | tpot_mean_ms | no | 95.7% | 34.4% | non-failure with spread > log1p(margin) |
+| q30 fixed-pd high | tpot_p90_ms | no | 95.1% | 37.2% | non-failure with spread > log1p(margin) |
+| q30 fixed-pd high | e2e_mean_ms | no | 111.5% | 0.7% | non-failure with spread > log1p(margin) |
+| q30 fixed-po high | ttft_mean_ms | no | 0.3% | 0.1% | non-failure with spread > log1p(margin) |
+| q30 fixed-po high | ttft_p90_ms | no | 0.3% | 0.0% | non-failure with spread > log1p(margin) |
+| q30 fixed-po high | e2e_mean_ms | no | 0.3% | 0.1% | non-failure with spread > log1p(margin) |
+| q30 fixed-po high | e2e_p90_ms | no | 0.3% | 0.0% | non-failure with spread > log1p(margin) |
+| q30 fixed-pd low | ttft_mean_ms | no | 1.5% | 1.3% | non-failure with spread > log1p(margin) |
+| q30 fixed-pd low | ttft_p90_ms | no | 2.9% | 1.8% | non-failure with spread > log1p(margin) |
+| q30 fixed-po low | ttft_mean_ms | no | 1.1% | 0.3% | non-failure with spread > log1p(margin) |
+| q30 fixed-po low | ttft_p90_ms | no | 2.3% | 0.6% | non-failure with spread > log1p(margin) |
+| q30 fixed-po low | e2e_mean_ms | no | 1.1% | 0.3% | non-failure with spread > log1p(margin) |
+| q30 fixed-po low | e2e_p90_ms | no | 2.4% | 0.7% | non-failure with spread > log1p(margin) |
+| q30 trace-po low | ttft_mean_ms | no | 2.6% | 1.7% | non-failure with spread > log1p(margin) |
+| q30 trace-po low | ttft_p90_ms | no | 0.2% | 0.2% | non-failure with spread > log1p(margin) |
+| q30 trace-po low | e2e_mean_ms | no | 2.6% | 1.7% | non-failure with spread > log1p(margin) |
+| q30 trace-po low | e2e_p90_ms | no | 0.2% | 0.1% | non-failure with spread > log1p(margin) |
+| q235 A0 fixed-pd | ttft_mean_ms | no | 5.0% | 0.4% | non-failure with spread > log1p(margin) |
+| q235 A0 fixed-pd | ttft_p90_ms | no | 2.4% | 0.2% | non-failure with spread > log1p(margin) |
+| q235 A0 fixed-po | ttft_p90_ms | no | 8.0% | 0.3% | non-failure with spread > log1p(margin) |
+| q235 A0 fixed-po | e2e_p90_ms | no | 8.0% | 0.3% | non-failure with spread > log1p(margin) |
+| q235 A0 trace-pd | tpot_mean_ms | no | 43.1% | 16.8% | non-failure with spread > log1p(margin) |
+| q235 A0 trace-pd | tpot_p90_ms | no | 29.8% | 26.3% | non-failure with spread > log1p(margin) |
+| q235 A0 trace-pd | e2e_mean_ms | no | 69.3% | 0.6% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-pd | ttft_mean_ms | no | 26.8% | 0.4% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-pd | ttft_p90_ms | no | 30.5% | 0.2% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-po | ttft_mean_ms | no | 24.8% | 0.2% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-po | ttft_p90_ms | no | 28.9% | 0.3% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-po | e2e_mean_ms | no | 24.8% | 0.2% | non-failure with spread > log1p(margin) |
+| q235 A1 fixed-po | e2e_p90_ms | no | 28.9% | 0.3% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-pd | tpot_mean_ms | no | 28.2% | 16.8% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-pd | e2e_mean_ms | no | 48.8% | 0.6% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-po | ttft_mean_ms | no | 32.2% | 1.4% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-po | ttft_p90_ms | no | 31.9% | 0.3% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-po | e2e_mean_ms | no | 32.2% | 1.4% | non-failure with spread > log1p(margin) |
+| q235 A1 trace-po | e2e_p90_ms | no | 31.9% | 0.3% | non-failure with spread > log1p(margin) |
+
+## S0b directional conclusions
+
+Directional pair statistics remove the S0 range statistic's ambiguity by measuring every config against the real winner. Strict inversions use the frozen-value test `real_c > real_w and sim_c < sim_w`; simulator ties are not counted as inversions.
+
+### (a) Which config axis decides each material failure?
+
+| case | objective | real winner → sim winner | deciding axis | m_s | delta_s | -delta_s | regret |
+|---|---|---|---|---:|---:|---:|---:|
+| q30 fixed-pd high | ttft_mean_ms | tp4_mns32 → tp2_mns64 | mixed | 45.7% | -523.8% | 523.8% | 58.0% |
+| q30 fixed-pd high | ttft_p90_ms | tp4_mns64 → tp2_mns64 | tp-axis | 44.6% | -435.3% | 435.3% | 56.2% |
+| q30 fixed-pd high | e2e_p90_ms | tp1_mns32 → tp2_mns64 | mixed | 5.3% | -101.7% | 101.7% | 5.5% |
+| q30 fixed-pd low | tpot_mean_ms | tp4_mns32 → tp1_mns16 | mixed | 13.1% | -52.5% | 52.5% | 14.0% |
+| q30 fixed-pd low | tpot_p90_ms | tp4_mns8 → tp1_mns16 | mixed | 12.5% | -52.8% | 52.8% | 13.4% |
+| q30 fixed-pd low | e2e_mean_ms | tp4_mns32 → tp1_mns16 | mixed | 23.8% | -59.6% | 59.6% | 26.9% |
+| q30 fixed-pd low | e2e_p90_ms | tp4_mns8 → tp1_mns16 | mixed | 22.9% | -59.8% | 59.8% | 25.7% |
+| q235 A0 fixed-pd | tpot_mean_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 28.5% | -64.0% | 64.0% | 33.0% |
+| q235 A0 fixed-pd | tpot_p90_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 31.6% | -62.8% | 62.8% | 37.2% |
+| q235 A0 fixed-pd | e2e_mean_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 26.8% | -61.5% | 61.5% | 30.7% |
+| q235 A0 fixed-pd | e2e_p90_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 29.7% | -60.4% | 60.4% | 34.6% |
+| q235 A0 fixed-po | ttft_mean_ms | tp8_ep8_mns128 → tp4_ep1_mns128 | tp-axis | 5.7% | -12.0% | 12.0% | 5.9% |
+| q235 A0 fixed-po | e2e_mean_ms | tp8_ep8_mns128 → tp4_ep1_mns128 | tp-axis | 5.7% | -12.0% | 12.0% | 5.9% |
+| q235 A0 trace-pd | e2e_p90_ms | tp8_ep8_mns64 → tp8_ep8_mns128 | mns-axis | 6.0% | -16.7% | 16.7% | 6.2% |
+| q235 A0 trace-po | ttft_mean_ms | tp8_ep8_mns128 → tp4_ep1_mns64 | mixed | 6.8% | -36.3% | 36.3% | 7.0% |
+| q235 A0 trace-po | ttft_p90_ms | tp8_ep8_mns64 → tp4_ep1_mns128 | mixed | 19.2% | -31.6% | 31.6% | 21.2% |
+| q235 A0 trace-po | e2e_mean_ms | tp8_ep8_mns128 → tp4_ep1_mns64 | mixed | 6.8% | -36.3% | 36.3% | 7.0% |
+| q235 A0 trace-po | e2e_p90_ms | tp8_ep8_mns64 → tp4_ep1_mns128 | mixed | 19.2% | -31.6% | 31.6% | 21.2% |
+| q235 A1 fixed-pd | tpot_mean_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 28.5% | -60.1% | 60.1% | 33.0% |
+| q235 A1 fixed-pd | tpot_p90_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 31.6% | -61.1% | 61.1% | 37.2% |
+| q235 A1 fixed-pd | e2e_mean_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 26.8% | -58.3% | 58.3% | 30.7% |
+| q235 A1 fixed-pd | e2e_p90_ms | tp4_ep1_mns128 → tp8_ep8_mns128 | tp-axis | 29.7% | -59.2% | 59.2% | 34.6% |
+| q235 A1 trace-pd | e2e_p90_ms | tp8_ep8_mns64 → tp8_ep8_mns128 | mns-axis | 6.0% | -17.4% | 17.4% | 6.2% |
+
+### (b) Where do TP-axis and MNS-axis inversions and boundary ties concentrate?
+
+`n_inv_*` counts sum strict `(real winner, c)` pair inversions across all objectives in each case; a row can contain more than one inverted pair. `n_tie_*` counts cover exact simulator ties only for the simulator-selected winner versus the real winner. Ties remain decision-boundary winner-label mismatches, not strict reversals.
+
+| case | n_inv_tp | n_inv_mns | n_inv_mixed | n_tie_tp | n_tie_mns | n_tie_mixed |
+|---|---:|---:|---:|---:|---:|---:|
+| q30 trace-pd | 0 | 0 | 0 | 0 | 0 | 0 |
+| q30 fixed-pd high | 7 | 3 | 6 | 0 | 0 | 0 |
+| q30 fixed-po high | 0 | 0 | 0 | 0 | 4 | 0 |
+| q30 fixed-pd low | 8 | 0 | 24 | 0 | 0 | 0 |
+| q30 fixed-po low | 0 | 0 | 0 | 0 | 4 | 0 |
+| q30 trace-po low | 0 | 6 | 0 | 0 | 2 | 0 |
+| q235 A0 fixed-pd | 5 | 0 | 5 | 0 | 1 | 0 |
+| q235 A0 fixed-po | 4 | 0 | 4 | 0 | 0 | 0 |
+| q235 A0 trace-pd | 0 | 2 | 0 | 0 | 0 | 0 |
+| q235 A0 trace-po | 4 | 2 | 4 | 0 | 0 | 0 |
+| q235 A1 fixed-pd | 4 | 0 | 4 | 0 | 1 | 0 |
+| q235 A1 fixed-po | 0 | 0 | 0 | 0 | 0 | 0 |
+| q235 A1 trace-pd | 0 | 2 | 0 | 0 | 0 | 0 |
+| q235 A1 trace-po | 0 | 2 | 0 | 0 | 2 | 0 |
+| **total** | **32** | **17** | **47** | **0** | **14** | **0** |
+
+- Among strict inversions, TP-axis cases are most concentrated in: q30 fixed-pd low (8), q30 fixed-pd high (7), q235 A0 fixed-pd (5), q235 A0 fixed-po (4), q235 A0 trace-po (4).
+- Among strict inversions, MNS-axis cases are most concentrated in: q30 trace-po low (6), q30 fixed-pd high (3), q235 A0 trace-pd (2), q235 A0 trace-po (2), q235 A1 trace-pd (2).
+- The eight Q235 A0/A1 Fixed-PD failures are all tp-axis. This does not conflict with the A0/MNS64 state-drift diagnosis, but does not constitute additional state-drift evidence for A1/MNS128.
+- Q30 admission evidence does not map one-to-one to an MNS-axis deciding pair: high-pressure Fixed-PD TTFT mean is **mixed** and p90 is **tp-axis**. This is an axis/mechanism mismatch, not a direct causal contradiction: changing TP changes offered arrival pressure, while the diagnosed nonlinear event is crossing the MNS admission cap. It rules out the simpler claim that an MNS-threshold mechanism must appear as an mns-axis winner pair.
+- All 14 exact simulator winner ties are mns-axis. Including these boundary errors gives MNS **17 + 14 = 31**, comparable to TP's **32** strict inversions.
+
+The exact ties below show that Frontier is completely insensitive to MNS changes within the corresponding case/objective cell:
+
+| case | objective | real winner ↔ simulator-selected tied winner (MNS pair) |
+|---|---|---|
+| q30 fixed-po high | ttft_mean_ms | tp4_mns32 ↔ tp4_mns16 |
+| q30 fixed-po high | ttft_p90_ms | tp4_mns32 ↔ tp4_mns16 |
+| q30 fixed-po high | e2e_mean_ms | tp4_mns32 ↔ tp4_mns16 |
+| q30 fixed-po high | e2e_p90_ms | tp4_mns32 ↔ tp4_mns16 |
+| q30 fixed-po low | ttft_mean_ms | tp4_mns8 ↔ tp4_mns16 |
+| q30 fixed-po low | ttft_p90_ms | tp4_mns8 ↔ tp4_mns16 |
+| q30 fixed-po low | e2e_mean_ms | tp4_mns8 ↔ tp4_mns16 |
+| q30 fixed-po low | e2e_p90_ms | tp4_mns8 ↔ tp4_mns16 |
+| q30 trace-po low | ttft_p90_ms | tp4_mns8 ↔ tp4_mns16 |
+| q30 trace-po low | e2e_p90_ms | tp4_mns8 ↔ tp4_mns16 |
+| q235 A0 fixed-pd | ttft_p90_ms | tp8_ep8_mns64 ↔ tp8_ep8_mns128 |
+| q235 A1 fixed-pd | ttft_p90_ms | tp8_ep8_mns64 ↔ tp8_ep8_mns128 |
+| q235 A1 trace-po | ttft_p90_ms | tp8_ep8_mns64 ↔ tp8_ep8_mns128 |
+| q235 A1 trace-po | e2e_p90_ms | tp8_ep8_mns64 ↔ tp8_ep8_mns128 |
+
+### (c) How many exact-winner successes are margin-robust?
+
+Among exact winner matches, **17** are margin-robust (`margin >= 1%`) and **6** are fragile (`margin < 1%`). Separately, 14 winner-label mismatches come from exact simulator ties and sit on the decision boundary rather than being strict inversions.
+
+| fragile-success case | objective | real margin |
+|---|---|---:|
+| q30 trace-pd | e2e_p90_ms | 0.1% |
+| q235 A1 fixed-pd | ttft_mean_ms | 0.4% |
+| q235 A1 fixed-po | ttft_mean_ms | 0.2% |
+| q235 A1 fixed-po | ttft_p90_ms | 0.3% |
+| q235 A1 fixed-po | e2e_mean_ms | 0.2% |
+| q235 A1 fixed-po | e2e_p90_ms | 0.3% |
+
+## Cross-checks
+
+| check | observed | frozen expectation | result |
+|---|---:|---:|---|
+| q30 high-pressure fixed-pd TTFT mean regret | 58.0% | 58.0% | PASS |
+| q235 A0 fixed-pd TPOT mean regret | 33.0% | 33.0% | PASS |
+| q235 A1 fixed-pd TPOT mean regret | 33.0% | 33.0% | PASS |
+| q30 trace-pd all-objective regret | 0.0%, 0.0%, 0.0%, 0.0%, 0.0%, 0.0% | 0.0%, 0.0%, 0.0%, 0.0%, 0.0%, 0.0% | PASS |
+| q235 Trace-PO TTFT p90 A0 to A1 regret | 21.2%, 0.3% | 21.2%, 0.3% | PASS |
+| q235 Fixed-PD TPOT/E2E regrets unchanged from A0 to A1 | 33.0%, 37.2%, 30.7%, 34.6%, 33.0%, 37.2%, 30.7%, 34.6% | 33.0%, 37.2%, 30.7%, 34.6%, 33.0%, 37.2%, 30.7%, 34.6% | PASS |
+
+## Data gaps
+
+No per-config sim/real pairing gaps were found in the requested surfaces.
+
+## 异常
+
+- 无。重算 winner/regret 与 frozen JSON 一致，硬性交叉核对均通过。
+
+## Figure
+
+`margin-vs-residual.png` uses x = `100 × log1p(real best-vs-second relative margin)` and y = `100 ×` real-top-3 log-ratio spread. Both axes are logarithmic because the real margins span six orders of magnitude. Green means exact winner match; red means winner mismatch. The diagonal is the H-SCALE threshold, while failure itself is defined by regret, not by exact winner match.
+
+`decision-pair-axis.png` is a mechanism census, not a hypothesis test: for a strict winner reversal, `-delta_s > m_s` is algebraically equivalent to the mismatch. The frozen surfaces also contain deterministic winner-label mismatches caused by exact simulator ties; those points lie on `-delta_s = m_s` and are not counted as strict inversions. Color identifies the winner-deciding config axis and marker area is proportional to regret.
+
+## A0 vs A1 对照
+
+A1 repairs the Q235 Trace-PO p90 ranking error but leaves the four large Fixed-PD TPOT/E2E regrets unchanged.
+
+| case / objective | A0 regret | A1 regret |
+|---|---:|---:|
+| trace-po / ttft_p90_ms | 21.2% | 0.3% |
+| fixed-pd / tpot_mean_ms | 33.0% | 33.0% |
+| fixed-pd / tpot_p90_ms | 37.2% | 37.2% |
+| fixed-pd / e2e_mean_ms | 30.7% | 30.7% |
+| fixed-pd / e2e_p90_ms | 34.6% | 34.6% |
+
+Thus Trace-PO TTFT p90 changes **21.2% → 0.3%**, whereas Fixed-PD remains **33.0% / 37.2% / 30.7% / 34.6%** in both A0 and A1.
+
+## 已知分量归因摘要
+
+### Q30 high-pressure Fixed-PD TTFT: first-scheduling wait vs execution-side TTFT
+
+`queue-free TTFT` is the execution-side TTFT after removing first-scheduling wait; in the frozen diagnostic, simulated TTFT is their sum (up to floating-point rounding).
+
+| config | sim TPOT / real | sim slots / MNS | real slots upper / MNS | first-scheduling wait | queue-free TTFT | sim TTFT | real TTFT | real waiting max |
+|---|---:|---:|---:|---:|---:|---:|---:|---:|
+| tp2_mns64 | 8.09x | 58.0/64 | 7.5/64 | 38.2 ms | 191.0 ms | 229.3 ms | 194.6 ms | 0 |
+| tp4_mns16 | 3.83x | 54.5/16 | 14.6/16 | 64906.3 ms | 134.7 ms | 65041.0 ms | 124.5 ms | 0 |
+| tp4_mns32 | 4.67x | 65.9/32 | 14.5/32 | 27180.7 ms | 135.6 ms | 27316.3 ms | 123.2 ms | 0 |
+| tp4_mns64 | 5.61x | 79.8/64 | 14.7/64 | 6367.3 ms | 136.7 ms | 6504.0 ms | 123.2 ms | 0 |
+
+For TP4/MNS32 minus TP2/MNS64, the observed simulator contrast is **+27087.0 ms**; removing first-scheduling wait changes it to **-55.4 ms**, aligned with the real contrast **-71.4 ms**. This localizes the Q30 high-pressure TTFT reversal to admission queueing, while the upstream service-time overprediction remains unattributed in the frozen data.
+
+### Q235 Fixed-PD: own-composition vs exact-state contrast
+
+Positive TP8−TP4 means TP8 is slower and therefore agrees with the real TP4 winner.
+
+| config | sim own decode batch mean | real exact decode batch mean | real token-weighted iteration | exact-state matched sim | coverage |
+|---|---:|---:|---:|---:|---:|
+| tp4_ep1_mns64 | 13.537 | 3.890 | 18.4710 ms | 34.2575 ms | 100.0% |
+| tp8_ep8_mns64 | 18.938 | 10.921 | 27.5887 ms | 45.1603 ms | 100.0% |
+
+| component | own-composition TP8−TP4 | exact-state TP8−TP4 |
+|---|---:|---:|
+| total | -20.0663 ms | +10.9028 ms |
+| moe_compute | -32.4544 ms | -1.9774 ms |
+| attention | -7.4619 ms | -2.1304 ms |
+| tp_dp_communication | -6.5711 ms | -6.4718 ms |
+| ep_communication | +6.2354 ms | +6.5355 ms |
+| moe_routing | -0.2862 ms | +0.1384 ms |
+| dense_mlp_compute | -0.1231 ms | -0.0308 ms |
+| pipeline_communication | +0.0000 ms | +0.0000 ms |
+| runtime_overhead | +0.0000 ms | +0.0000 ms |
+
+The total contrast flips from **-20.0663 ms** on Frontier's own composition to **+10.9028 ms** at exact real state, a **+30.9690 ms** state-composition shift. The exact real iteration contrast is **+9.1177 ms** and the frozen real TPOT contrast is **+6.9500 ms**. This supports closed-loop state/composition drift for Q235 Fixed-PD; it does not by itself attribute every remaining conditional execution residual.
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