diff --git a/README.md b/README.md
index 421e75c..8420b6e 100644
--- a/README.md
+++ b/README.md
@@ -89,14 +89,20 @@ client.exit()
 | P3 问题二选点（K1、候选区域 Q、采样评估） | ✅ 完成（belief + 选点器，测试固化） |
 | P4 问题3全向闭环（49点覆盖、定位队列、清除、停止） | ✅ 官方问题3演练单案例通过（10/10全清，[验证报告](output/q3/practice/20260911-port2026/report.md)） |
 | P5 问题4定向扩展（联合约束、后备清除、预算） | ✅ 自建完成（官方演练待执行） |
-| P6 加速与消融 | 🦴 未开始 |
+| P6 加速与消融 | ✅ 七点批量（`--strategy seven`，官方演练 12/12）+ 贝叶斯闭环（`--strategy bayes`，自建消融 −19.5%，[算法说明](docs/algo-3-bayes.md)） |
 
 ## 采集与正式测试约束
 
 改进版 A2（七点覆盖＋本站批量扫频）已通过官方案例 `J4ER-Y9EP-Q379-UPFA`：
 12/12源全清，109次检测，虚拟耗时5232.132109秒，现实耗时3.406秒。
 [本局报告与运行方法](output/q3/practice/20260911-seven-batch-01/report.md)。
-独立入口为 `scripts/run_q3_seven_practice.py`，默认 `mcm26b run` 策略仍保持原样。
+独立入口为 `scripts/run_q3_seven_practice.py`。
+
+贝叶斯闭环 `bayes`（网格粒子滤波＋负观测更新＋信息增益选点＋滚动 2-opt
+调度）在自建模拟器配对消融中相对 SevenBatch 平均虚拟时间再降 19.5%
+（14/14 场景全清零异常），算法与数据见
+[algo-3-bayes.md](docs/algo-3-bayes.md)；`mcm26b run --strategy bayes`
+即可启用（自建消融达标后已成为 `mcm26b run` 默认策略，见下）。
 
 2026-09-11 已通过本机 2026 端口完成一次官方问题3演练：案例
 `DHFK-PHD2-SR2P-FXK9`，10/10 源全清，540 次检测、10 次清除，现实耗时
diff --git a/docs/algo-3-bayes.md b/docs/algo-3-bayes.md
new file mode 100644
index 0000000..2f20eb2
--- /dev/null
+++ b/docs/algo-3-bayes.md
@@ -0,0 +1,117 @@
+# 算法说明：问题3 贝叶斯闭环（`bayes` 策略）
+
+对应实现：`src/mcm26b/particles.py`（感知层）、`src/mcm26b/planner/bayes_loop.py`
+（决策层）、`scripts/benchmark_q3_bayes.py`（消融）、`scripts/tune_q3_bayes.py`
+（Optuna 调参）。基线对比：`docs/algo-3.md` 的七点批量（`seven`，A2）。
+
+## 1. 建模定位
+
+问题3是部分可观察的在线决策问题：频道数未知（10–16/20）、位置未知、有效
+接收半径未知（1000–1500m）、测向误差 ±1°（服务器保留两位小数）。策略层
+只能拿到 `/measure` 与 `/clear` 的响应，目标是最小化"发现—定位—清除"的
+虚拟总时间。`bayes` 策略把它分解为三层滚动时域闭环：
+
+1. **感知层**：每频道一个贝叶斯后验（网格幸存集），融合全部正/负观测；
+2. **决策层**：站点扫频、定位测量、清除三类任务统一建表，开放路径
+   最近邻 + 2-opt 排序，每个动作后滚动重排（动态 TSP）；
+3. **选点层**：定位测量点按期望后验半径 + λ·移动时间评分（信息增益贪心
+   的半径代理形式），直指 20m 清除证书阈值。
+
+## 2. 网格幸存集滤波与真源保留定理
+
+每频道维护 Ω 上间距 h 的网格（h=25m，约 1.6 万格），`alive` 为幸存格
+集合。Voronoi 裕量 m = √2/2·h 是格心到格内任一点的最大距离；所有删除
+判定都内缩 m，即**仅当整格与可行集不相交时才删格**：
+
+| 观测 | 题面语义 | 删除判定 |
+|---|---|---|
+| `no_signal`@s | 距离 > r_eff ≥ 1000 | 删格心距 s ≤ 1000 − m 的格 |
+| `direction`@s | 距离 ≤ 1500，\|读数−真值\| ≤ δ_eff | 删角向超出 δ_eff + asin(m/(d−m)) 或距 s > 1500 + m 的格 |
+| `near`@s | 距离 ≤ 5 | 删格心距 s > 5 + m 的格 |
+
+**定理（真源保留）**：真源 P 满足全部题面约束；P 所在格的格心 g 满足
+|g−P| ≤ m，故"整格不相交"判定永不命中该格。因此任意观测序列后 P ∈
+幸存格的并集，且：
+
+- **缺席证明**：幸存集为空 ⟹ 可行集为空 ⟹ 该频道无源（严格）；
+- **清除证书**：MEC(幸存).R + m ≤ 20 − 工程余量 ⟹ 真源距清除点 ≤ 20；
+- **跳测规则**：幸存格到测点最小距离 > 1500 + m ⟹ 该测量必 no_signal
+  且无新排除，可跳过。
+
+性质测试：`tests/test_particles.py`（随机源 × 随机测点 × 随机合法误差，
+真源格永不被删；`tests/test_bayes_loop_q3.py` 端到端零异常）。
+
+与 `belief.CandidateRegion`（保守凸外包）的分工：凸表示负责**清除证书**
+（精确角域裁剪、收敛后触发），网格负责凸表示做不到的三件事——非凸负
+观测挖洞（no_signal 排除盘）、缺席提前证毕、跳测判定。两者同读一套
+响应流（`_record_measure`），任何一方证毕即收尾。
+
+## 3. 信息增益选点
+
+候选点集（二选一，按保证接收盘是否非空）：
+
+- **保证接收盘** B(MEC_poly 圆心, 1000 − ρ_poly)（盘内必收 direction/near，
+  几何同 `docs/algo-2.md` 定理1）：环形采样（`search.candidate_rings`×12 方向）；
+- **宽候选集**（ρ_poly > 1000 时）：PF MEC 的 1.0/1.5/2.0 倍探索环。
+
+评分（`BayesConfig.score_mode`）：
+
+- `radius`（默认）：期望后验半径 —— 对 K 个代表假设（幸存格均匀抽样）
+  各自模拟一次测量的幸存分支，分支半径用幸存子采样的质心最大距离近似，
+  r_eff~U(1000,1500) 的不确定性解析积分（p_no_signal = (d−1000)/500）；
+  总分 = E[半径] + λ·移动秒数（λ=0.1）；
+- `entropy`：期望 log 幸存占比（香农信息增益在均匀先验下的形式）。
+
+λ 与半径同量纲，量级必须小：λ 过大时终局阶段"走 300m"的代价压过
+"半径 35m→25m"的收益，选点器原地重测、收敛停滞（消融实测 λ≥0.5 时
+单源定位步数翻倍）。
+
+## 4. 统一任务循环（动态 TSP）
+
+每个决策点构建任务表并排序执行首个任务，随后滚动重排：
+
+- **站点任务**：七站（原点 + 1200m 环六点，覆盖半径解析上界 968.9m
+  < 1000m）上仍待测的 UNKNOWN 频道；跳测规则与覆盖账本过滤；
+- **定位任务**：DETECTED 且无证书的频道，位置由信息增益选点产生；
+- **清除任务**：有证书（凸或网格）的频道，目标为证书圆心。
+
+排序 = 开放路径最近邻打底 + 2-opt 改进（`two_opt_passes` 轮，成本含
+移动 + 换频 + 动作耗时；终点自由不回起点）。这是 A2"站内最近邻服务
+队列"的推广：消融显示距离缩短约 24% 是主要收益来源。
+
+停止条件与基线一致：清满 16（数量上界）或全部频道 CLEARED/ABSENT；
+`persistent_search` 开启时找全后继续复扫到限时（复扫读数同样进 PF）。
+
+## 5. 消融结果（自建模拟器，persistent 关）
+
+12 随机场景（6 种子 × 10/16 源）+ 2 边界场景，与 SevenBatch 配对：
+
+| 指标 | SevenBatch | bayes |
+|---|---|---|
+| 有效运行（全清+缺席正确+零异常+正常退出） | 14/14 | **14/14** |
+| 平均虚拟时间 | 5352.7s | **4277.6s（−19.5%）** |
+| 配对降幅（最差 / 最好） | — | +1.4% / −28.1% |
+| 平均移动距离 | 23413m | **17820m（−24%）** |
+| 平均检测次数 | 102.4 | 109.6 |
+| 单局实机计算墙钟 | 1.3s | 1.0s |
+
+复现：`uv run python scripts/benchmark_q3_bayes.py --seeds 0,1,2,3,4,5`
+（逐场景数据与场景 JSON 见 `output/q3/bayes-ablation/`）。
+
+## 6. Optuna 调参
+
+`scripts/tune_q3_bayes.py`：TPE（dev 依赖 `optuna`，缺失时自动退化为
+随机搜索），目标 = 场景子集平均虚拟时间 + 10⁶×失败惩罚。搜索空间：
+λ、代表点数、子采样规模、网格间距、站点环半径、2-opt 轮数、评分模式。
+输出 `output/q3/bayes-tuning/best_params.json`，人工复跑全量基准确认
+后再回填 `config.BayesConfig` 默认值。
+
+## 7. 已知边界
+
+- 检测次数略多于 A2（109.6 vs 102.4）：定位收敛多用 1-2 次测量换距离
+  大幅缩短，净收益为正；跳测规则在 UNKNOWN 阶段（先验全域）暂无收益
+  面，收益集中在定位与复扫阶段；
+- 网格清除证书（h=25m 时阈值 ≤1.8m）极少触发，作为凸证书的补位保险；
+- 调参与消融基于自建模拟器（逐点固定 ±1° 误差场），不代表官方误差
+  分布；真源保留定理只依赖题面界（±1°、r_eff∈[1000,1500]），不依赖
+  误差分布假设。
diff --git a/docs/algo-3.md b/docs/algo-3.md
index 28ce792..08d8836 100644
--- a/docs/algo-3.md
+++ b/docs/algo-3.md
@@ -6,6 +6,11 @@
 
 **关键词：** 全向源搜索；覆盖证书；集合定位；任务调度；虚拟总耗时；滚动规划。
 
+> **延伸实现（2026-09-11）**：本文规划的无信号负观测更新、开放路径 2-opt
+> 任务排序等已落地为贝叶斯闭环策略 `bayes`（网格幸存集滤波 + 信息增益
+> 选点 + 滚动任务调度），自建消融相对本文七点批量策略平均虚拟时间再降
+> 19.5%。设计、严格性证明与消融数据见 [algo-3-bayes.md](algo-3-bayes.md)。
+
 ## 1. 问题界定与思路来源
 
 第三问要求在不知道干扰源位置和具体数量的条件下，自动发现并清除全部全向源，尽量缩短总时间。每个频道最多一个源，因此本题的数据关联由频道确定；机器狗无需解决无法区分多个信号身份的问题。源位于半径1800米的圆域内，最小有效接收半径为1000米。这两个尺度之间的关系使稀疏、有证明的覆盖成为可能。[题面](C:/Users/HelixCopex/code/MATH/issue/B题.pdf)、[接口规则](C:/Users/HelixCopex/code/MATH/docs/协议规则表与状态机.md)
diff --git a/output/q3/bayes-ablation/actions/boundary-10-bayes.jsonl b/output/q3/bayes-ablation/actions/boundary-10-bayes.jsonl
new file mode 100644
index 0000000..e40454b
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index 0000000..e25c1be
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diff --git a/output/q3/bayes-ablation/actions/random-10-seed0-bayes.jsonl b/output/q3/bayes-ablation/actions/random-10-seed0-bayes.jsonl
new file mode 100644
index 0000000..ee786ec
--- /dev/null
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index 0000000..e5b235e
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index 0000000..6596220
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new file mode 100644
index 0000000..8fed012
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index 0000000..9e2175f
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diff --git a/output/q3/bayes-ablation/actions/random-10-seed3-bayes.jsonl b/output/q3/bayes-ablation/actions/random-10-seed3-bayes.jsonl
new file mode 100644
index 0000000..7617810
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index 0000000..6026d15
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index 0000000..a2bcc60
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new file mode 100644
index 0000000..14579e4
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index 0000000..1d6e462
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index 0000000..9bbd9a4
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index 0000000..c9c641c
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index 0000000..b25457d
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new file mode 100644
index 0000000..000e998
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index 0000000..c1c3cbb
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index 0000000..de94d13
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index 0000000..0272b28
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index 0000000..81c8506
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diff --git a/output/q3/bayes-ablation/benchmark.json b/output/q3/bayes-ablation/benchmark.json
new file mode 100644
index 0000000..cf747ca
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+}
\ No newline at end of file
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new file mode 100644
index 0000000..770b8c4
--- /dev/null
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@@ -0,0 +1,85 @@
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diff --git a/output/q3/bayes-ablation/scenes/boundary-16.json b/output/q3/bayes-ablation/scenes/boundary-16.json
new file mode 100644
index 0000000..5520b3e
--- /dev/null
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\ No newline at end of file
diff --git a/output/q3/bayes-ablation/scenes/random-10-seed0.json b/output/q3/bayes-ablation/scenes/random-10-seed0.json
new file mode 100644
index 0000000..721d9ee
--- /dev/null
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diff --git a/output/q3/bayes-ablation/scenes/random-10-seed1.json b/output/q3/bayes-ablation/scenes/random-10-seed1.json
new file mode 100644
index 0000000..9e3b84f
--- /dev/null
+++ b/output/q3/bayes-ablation/scenes/random-10-seed1.json
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diff --git a/output/q3/bayes-ablation/scenes/random-10-seed2.json b/output/q3/bayes-ablation/scenes/random-10-seed2.json
new file mode 100644
index 0000000..27e0fc4
--- /dev/null
+++ b/output/q3/bayes-ablation/scenes/random-10-seed2.json
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diff --git a/output/q3/bayes-ablation/scenes/random-10-seed3.json b/output/q3/bayes-ablation/scenes/random-10-seed3.json
new file mode 100644
index 0000000..50e1b48
--- /dev/null
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new file mode 100644
index 0000000..2dfc189
--- /dev/null
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new file mode 100644
index 0000000..c5bfb95
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new file mode 100644
index 0000000..3d6b487
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new file mode 100644
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new file mode 100644
index 0000000..8a124d1
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new file mode 100644
index 0000000..09958af
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+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 15,
+      "x": 709.0000429680814,
+      "y": -1422.9429938342512,
+      "r_eff_m": 1134.7158345309983,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 10,
+      "x": 1217.1114669619415,
+      "y": -667.553823804469,
+      "r_eff_m": 1193.8042928059751,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 20,
+      "x": -1432.505958327794,
+      "y": 708.0955932817741,
+      "r_eff_m": 1364.0629865262983,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 11,
+      "x": 1332.5362313475716,
+      "y": -305.83411429813776,
+      "r_eff_m": 1067.0745554524162,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 14,
+      "x": 1060.7004933295655,
+      "y": 243.30671353576284,
+      "r_eff_m": 1247.4417061246445,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 2,
+      "x": -430.13364790501555,
+      "y": -806.7491653883379,
+      "r_eff_m": 1389.4862928489158,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 1,
+      "x": -1464.4589969789185,
+      "y": 791.3853208101496,
+      "r_eff_m": 1416.7385599980737,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 13,
+      "x": -1332.568878953072,
+      "y": -289.98938805400286,
+      "r_eff_m": 1203.78793248628,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 3,
+      "x": -449.95920195054055,
+      "y": 741.9359141409767,
+      "r_eff_m": 1457.865398112482,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 17,
+      "x": -56.509250140815844,
+      "y": 299.4433270867276,
+      "r_eff_m": 1302.9096151563285,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 16,
+      "x": -476.29839895711945,
+      "y": -1423.647338076851,
+      "r_eff_m": 1163.1951442533468,
+      "directional": false,
+      "heading_deg": 0.0
+    }
+  ],
+  "error_seed": 20260913
+}
\ No newline at end of file
diff --git a/output/q3/bayes-ablation/scenes/random-16-seed4.json b/output/q3/bayes-ablation/scenes/random-16-seed4.json
new file mode 100644
index 0000000..8e92864
--- /dev/null
+++ b/output/q3/bayes-ablation/scenes/random-16-seed4.json
@@ -0,0 +1,133 @@
+{
+  "sources": [
+    {
+      "channel": 8,
+      "x": 200.7437389106916,
+      "y": -1061.5533232338394,
+      "r_eff_m": 1413.435839512137,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 10,
+      "x": 862.3429246964944,
+      "y": -323.01101363313086,
+      "r_eff_m": 1012.8198408667745,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 4,
+      "x": -92.76306146237147,
+      "y": 1437.7851761043391,
+      "r_eff_m": 1135.8738772326544,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 13,
+      "x": -180.13439376882482,
+      "y": 708.2109577265736,
+      "r_eff_m": 1433.660826578344,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 16,
+      "x": 1023.9001347568816,
+      "y": -1437.017367197758,
+      "r_eff_m": 1186.196547324651,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 3,
+      "x": -863.5693547072403,
+      "y": 1411.1573488226074,
+      "r_eff_m": 1193.96592492593,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 2,
+      "x": 15.107622146400166,
+      "y": 897.8429880977961,
+      "r_eff_m": 1139.9987976601205,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 14,
+      "x": 723.7406272686546,
+      "y": -1592.680616144755,
+      "r_eff_m": 1471.1036106483596,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 1,
+      "x": 1648.4879002606963,
+      "y": 74.74439114516646,
+      "r_eff_m": 1145.9708346887187,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 7,
+      "x": -571.854332719989,
+      "y": 1398.8856659497205,
+      "r_eff_m": 1382.603900538282,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 9,
+      "x": -705.55087712234,
+      "y": 366.6108573858005,
+      "r_eff_m": 1144.1017852389925,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 5,
+      "x": 127.22517276085749,
+      "y": 1202.6056340011012,
+      "r_eff_m": 1129.8275731973063,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 12,
+      "x": 1403.2594042740932,
+      "y": 783.8427100957722,
+      "r_eff_m": 1231.3348711518597,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 17,
+      "x": -1785.0997368362234,
+      "y": -212.66911846501773,
+      "r_eff_m": 1323.9990415842833,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 19,
+      "x": 923.1402578040139,
+      "y": 1191.0747733852622,
+      "r_eff_m": 1336.8894055320825,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 6,
+      "x": 397.1558544420732,
+      "y": -239.84967811782482,
+      "r_eff_m": 1317.5095529581047,
+      "directional": false,
+      "heading_deg": 0.0
+    }
+  ],
+  "error_seed": 20260914
+}
\ No newline at end of file
diff --git a/output/q3/bayes-ablation/scenes/random-16-seed5.json b/output/q3/bayes-ablation/scenes/random-16-seed5.json
new file mode 100644
index 0000000..201fe3a
--- /dev/null
+++ b/output/q3/bayes-ablation/scenes/random-16-seed5.json
@@ -0,0 +1,133 @@
+{
+  "sources": [
+    {
+      "channel": 20,
+      "x": 890.4076676410549,
+      "y": 663.9501763167591,
+      "r_eff_m": 1124.6653572213434,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 9,
+      "x": -1289.8931824145902,
+      "y": 839.7683134803877,
+      "r_eff_m": 1091.0378318888893,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 12,
+      "x": -1287.9598044708189,
+      "y": 1073.185448792104,
+      "r_eff_m": 1380.962713797193,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 17,
+      "x": -356.19422926484805,
+      "y": -325.8596243094702,
+      "r_eff_m": 1222.4178430687607,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 1,
+      "x": 644.7064795081491,
+      "y": -113.19859956308878,
+      "r_eff_m": 1002.656568622054,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 14,
+      "x": 1533.7507375545465,
+      "y": -392.49493354761813,
+      "r_eff_m": 1082.9282211974553,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 8,
+      "x": -285.96132523294483,
+      "y": 676.4878616019748,
+      "r_eff_m": 1099.4446632982174,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 13,
+      "x": -1185.8707222893981,
+      "y": -1196.8023954388952,
+      "r_eff_m": 1090.834334272802,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 4,
+      "x": 580.3461708065632,
+      "y": 1673.7151104309726,
+      "r_eff_m": 1482.5481954728875,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 11,
+      "x": 1104.0727094945587,
+      "y": 150.55750889672728,
+      "r_eff_m": 1207.4533558113726,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 16,
+      "x": -150.9216589325827,
+      "y": 1734.701950705398,
+      "r_eff_m": 1165.927243610319,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 3,
+      "x": -1394.7811175893712,
+      "y": -838.4286740779148,
+      "r_eff_m": 1297.989475272351,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 2,
+      "x": 1385.7929912319419,
+      "y": 610.2856046971255,
+      "r_eff_m": 1177.6756786499845,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 19,
+      "x": -328.9487141992066,
+      "y": -939.9153913875293,
+      "r_eff_m": 1092.386620049247,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 18,
+      "x": 553.9704067000805,
+      "y": 1106.4090752936866,
+      "r_eff_m": 1128.090917971356,
+      "directional": false,
+      "heading_deg": 0.0
+    },
+    {
+      "channel": 15,
+      "x": 1656.217793402799,
+      "y": -547.120524919987,
+      "r_eff_m": 1178.822032529417,
+      "directional": false,
+      "heading_deg": 0.0
+    }
+  ],
+  "error_seed": 20260915
+}
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index 12d3ce7..fc680e9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -10,6 +10,7 @@ dependencies = [
 
 [dependency-groups]
 dev = [
+    "optuna>=5.0.0",
     "pytest>=8",
 ]
 
diff --git a/scripts/benchmark_q3_bayes.py b/scripts/benchmark_q3_bayes.py
new file mode 100644
index 0000000..0ea2fb7
--- /dev/null
+++ b/scripts/benchmark_q3_bayes.py
@@ -0,0 +1,145 @@
+"""BayesLoop 与 SevenBatch 的配对消融（离线，自建模拟器）。
+
+同一场景、同一误差场下配对比较两种策略，输出逐场景行与聚合统计：
+all_cleared / correct_absence / anomalies / 虚拟时间 / 检测数 / 距离 /
+实机计算墙钟。基准配置 persistent_search=False（比较"首次证明找全"的
+虚拟时间口径；persistent 复扫到限时的行为与策略质量无关）。
+
+Run: uv run python scripts/benchmark_q3_bayes.py --seeds 0,1,2,3,4,5
+"""
+from __future__ import annotations
+
+import argparse
+from dataclasses import asdict, replace
+import hashlib
+import json
+import math
+from pathlib import Path
+from statistics import mean, median
+from time import perf_counter
+
+from mcm26b.config import ProblemConfig
+from mcm26b.planner.bayes_loop import BayesLoop
+from mcm26b.planner.seven import SevenBatch
+from mcm26b.protocol.client import SimulatorClient
+from mcm26b.sim import LocalSimulator, LocalSimTransport, Source
+from mcm26b.sim.scenes import random_omni_scene
+
+ROOT = Path(__file__).resolve().parents[1]
+
+VARIANTS = {"seven_batch": SevenBatch, "bayes": BayesLoop}
+
+
+def run_case(name, sources, error_seed, config, out):
+    scene_path = out / "scenes" / f"{name}.json"
+    scene_path.parent.mkdir(parents=True, exist_ok=True)
+    scene_path.write_text(json.dumps(
+        {"sources": [asdict(s) for s in sources], "error_seed": error_seed},
+        indent=2), encoding="utf-8")
+    rows = []
+    for label, cls in VARIANTS.items():
+        sim = LocalSimulator(sources, robot_id="Q3-BAYES", config=config,
+                             error_seed=error_seed)
+        client = SimulatorClient("Q3-BAYES", config=config,
+                                 transport=LocalSimTransport(sim))
+        loop = cls(client, config)
+        start = perf_counter()
+        summary = loop.run()
+        elapsed = perf_counter() - start
+        actions = client.log.action_events()
+        log_path = out / "actions" / f"{name}-{label}.jsonl"
+        log_path.parent.mkdir(parents=True, exist_ok=True)
+        with log_path.open("w", encoding="utf-8") as handle:
+            for event in actions:
+                handle.write(json.dumps(event, ensure_ascii=False) + "\n")
+        truth = {s.channel for s in sources}
+        absent = set(range(1, 21)) - truth
+        # 缺席证明有效性：PF 缺席以幸存集为空为据，无源频道缺席即为正确
+        correct_absence = set(summary["absent_channels"]) <= absent
+        accounted = summary.get("accounted_virtual_time_s") or summary["virtual_time_s"]
+        row = {"case": name, "variant": label, "source_count": len(sources),
+               "all_cleared": sim.cleared == truth, "completed": summary["completed"],
+               "correct_absence": correct_absence,
+               "normal_exit": summary["exit_reason"] == "user_exit",
+               "virtual_time_s": summary["virtual_time_s"],
+               "accounted_virtual_time_s": accounted,
+               "measures": summary["measures"], "clears": summary["clears"],
+               "failed_clears": summary["clears"] - len(sim.cleared),
+               "distance_m": summary["move_distance_m"],
+               "skipped_measures": summary.get("skipped_measures", 0),
+               "no_shrink_measures": summary.get("no_shrink_measures", 0),
+               "compute_wall_s": elapsed, "anomalies": summary["anomalies"],
+               "stop_reason": summary["stop_reason"],
+               "actions_sha256": hashlib.sha256(log_path.read_bytes()).hexdigest()}
+        rows.append(row)
+        print(f"{name} {label}: cleared={row['all_cleared']} "
+              f"T={row['virtual_time_s']:.0f} M={row['measures']} "
+              f"D={row['distance_m']:.0f} wall={elapsed:.1f}s", flush=True)
+    return rows
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--seeds", default="0,1,2,3,4,5")
+    parser.add_argument("--counts", default="10,16")
+    parser.add_argument("--out", type=Path, default=ROOT / "output/q3/bayes-ablation")
+    parser.add_argument("--bearing-margin-deg", type=float, default=0.005)
+    args = parser.parse_args()
+    args.out.mkdir(parents=True, exist_ok=True)
+
+    base = ProblemConfig()
+    config = replace(base,
+                     search=replace(base.search,
+                                    bearing_rounding_margin_deg=args.bearing_margin_deg,
+                                    persistent_search=False))
+    rows = []
+    seeds = [int(s) for s in args.seeds.split(",")]
+    counts = [int(c) for c in args.counts.split(",")]
+    for count in counts:
+        for seed in seeds:
+            rows.extend(run_case(f"random-{count}-seed{seed}",
+                                 random_omni_scene(seed, count, config=config),
+                                 20260910 + seed, config, args.out))
+        # 圆域边界源（r_eff=1000，扇区接缝处）：最刁钻的发现与定位场景
+        edge = [Source(c + 1, 1800 * math.cos(math.pi / 6 + 2 * math.pi * c / count),
+                       1800 * math.sin(math.pi / 6 + 2 * math.pi * c / count), 1000)
+                for c in range(count)]
+        rows.extend(run_case(f"boundary-{count}", edge, 20260910, config, args.out))
+
+    aggregates = {}
+    for label in VARIANTS:
+        part = [r for r in rows if r["variant"] == label]
+        baseline = {r["case"]: r for r in rows if r["variant"] == "seven_batch"}
+        savings = [1 - r["virtual_time_s"] / baseline[r["case"]]["virtual_time_s"]
+                   for r in part]
+        valid = sum(r["all_cleared"] and r["completed"] and r["correct_absence"]
+                    and r["normal_exit"] and not r["anomalies"] for r in part)
+        aggregates[label] = {
+            "runs": len(part), "all_cleared_runs": sum(r["all_cleared"] for r in part),
+            "valid_runs": valid,
+            "mean_virtual_s": mean(r["virtual_time_s"] for r in part),
+            "median_virtual_s": median(r["virtual_time_s"] for r in part),
+            "max_virtual_s": max(r["virtual_time_s"] for r in part),
+            "mean_measures": mean(r["measures"] for r in part),
+            "mean_distance_m": mean(r["distance_m"] for r in part),
+            "mean_skipped_measures": mean(r["skipped_measures"] for r in part),
+            "mean_compute_wall_s": mean(r["compute_wall_s"] for r in part),
+            "mean_paired_time_reduction": mean(savings),
+            "min_paired_time_reduction": min(savings),
+            "max_paired_time_reduction": max(savings),
+            "failed_clears": sum(r["failed_clears"] for r in part),
+        }
+    result = {"source": "local_simulator_only", "seeds": args.seeds,
+              "counts": args.counts, "config": asdict(config),
+              "aggregates": aggregates, "runs": rows,
+              "limitations": "自建模拟器合成数据；persistent 关闭以对齐找全口径。"}
+    (args.out / "benchmark.json").write_text(
+        json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
+    print(json.dumps(aggregates, ensure_ascii=False, indent=2))
+    ok = all(a["valid_runs"] == a["runs"] for a in aggregates.values()) \
+        and aggregates["bayes"]["mean_paired_time_reduction"] > 0
+    return 0 if ok else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/scripts/tune_q3_bayes.py b/scripts/tune_q3_bayes.py
new file mode 100644
index 0000000..cb5a754
--- /dev/null
+++ b/scripts/tune_q3_bayes.py
@@ -0,0 +1,135 @@
+"""BayesLoop 的 Optuna 离线调参（TPE），无 Optuna 时退化为随机搜索。
+
+目标：场景子集的平均虚拟时间（秒）+ 10^6 × 失败惩罚（未全清/未完成/
+异常/缺席误判任一即失败）。场景与误差种子固定但多样，防止对单一
+随机种子过拟合；最优参数写入 JSON，人工复跑 benchmark_q3_bayes.py
+确认后再回填 config.BayesConfig 默认值。
+
+Run: uv run python scripts/tune_q3_bayes.py --n-trials 100
+"""
+from __future__ import annotations
+
+import argparse
+from dataclasses import replace
+import json
+import math
+from pathlib import Path
+from random import Random
+from statistics import mean
+from time import perf_counter
+
+from mcm26b.config import ProblemConfig
+from mcm26b.planner.bayes_loop import BayesLoop
+from mcm26b.protocol.client import SimulatorClient
+from mcm26b.sim import LocalSimulator, LocalSimTransport, Source
+from mcm26b.sim.scenes import random_omni_scene
+
+ROOT = Path(__file__).resolve().parents[1]
+FAIL_PENALTY = 1.0e6
+
+BASE = replace(ProblemConfig(),
+               search=replace(ProblemConfig().search, persistent_search=False))
+
+# 调参场景：多种子 × 两档源数 × 边界场景（误差种子与场景种子解耦）
+SCENES = [(f"tune-{n}-{s}", random_omni_scene(s, n, config=BASE), 20260910 + s)
+          for n in (10, 16) for s in (0, 1, 2)]
+SCENES.append(("tune-boundary-10",
+               [Source(c + 1, 1800 * math.cos(math.pi / 6 + 2 * math.pi * c / 10),
+                       1800 * math.sin(math.pi / 6 + 2 * math.pi * c / 10), 1000)
+                for c in range(10)], 20260977))
+
+
+def evaluate(bayes_params: dict) -> tuple[float, dict]:
+    config = replace(BASE, bayes=replace(BASE.bayes, **bayes_params))
+    times = []
+    failures = 0
+    for name, sources, error_seed in SCENES:
+        sim = LocalSimulator(sources, robot_id="TUNE", config=config,
+                             error_seed=error_seed)
+        client = SimulatorClient("TUNE", config=config,
+                                 transport=LocalSimTransport(sim))
+        summary = BayesLoop(client, config).run()
+        truth = {s.channel for s in sources}
+        ok = (sorted(summary["cleared_channels"]) == sorted(truth)
+              and summary["completed"]
+              and not summary["anomalies"]
+              and set(summary["absent_channels"]) <= set(range(1, 21)) - truth)
+        if not ok:
+            failures += 1
+            continue
+        times.append(summary["virtual_time_s"])
+    objective = mean(times) if times else FAIL_PENALTY
+    return objective + FAIL_PENALTY * failures, {
+        "failures": failures, "mean_virtual_s": objective, "times": times}
+
+
+def suggest(trial, rng: Random):
+    """搜索空间：Optuna trial 或（退化时）rng 随机采样，二者同构。"""
+    if trial is not None:
+        return {
+            "lambda_move_s": trial.suggest_float("lambda_move_s", 0.01, 0.6, log=True),
+            "mc_representatives": trial.suggest_int("mc_representatives", 3, 12),
+            "score_subsample": trial.suggest_categorical("score_subsample",
+                                                         [300, 500, 800, 1200]),
+            "particle_spacing_m": trial.suggest_float("particle_spacing_m", 12.0, 40.0),
+            "station_ring_radius_m": trial.suggest_float("station_ring_radius_m",
+                                                         1100.0, 1450.0),
+            "two_opt_passes": trial.suggest_int("two_opt_passes", 1, 6),
+            "score_mode": trial.suggest_categorical("score_mode",
+                                                    ["radius", "entropy"]),
+        }
+    return {
+        "lambda_move_s": math.exp(rng.uniform(math.log(0.01), math.log(0.6))),
+        "mc_representatives": rng.randint(3, 12),
+        "score_subsample": rng.choice([300, 500, 800, 1200]),
+        "particle_spacing_m": rng.uniform(12.0, 40.0),
+        "station_ring_radius_m": rng.uniform(1100.0, 1450.0),
+        "two_opt_passes": rng.randint(1, 6),
+        "score_mode": rng.choice(["radius", "entropy"]),
+    }
+
+
+def main():
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--n-trials", type=int, default=60)
+    parser.add_argument("--out", type=Path,
+                        default=ROOT / "output/q3/bayes-tuning")
+    args = parser.parse_args()
+    args.out.mkdir(parents=True, exist_ok=True)
+    start = perf_counter()
+
+    try:
+        import optuna
+        optuna.logging.set_verbosity(optuna.logging.WARNING)
+
+        def objective(trial):
+            value, _detail = evaluate(suggest(trial, None))
+            return value
+
+        study = optuna.create_study(direction="minimize",
+                                    sampler=optuna.samplers.TPESampler(seed=7))
+        study.optimize(objective, n_trials=args.n_trials)
+        best_params, best_value = study.best_params, study.best_value
+        sampler = "tpe"
+    except ImportError:
+        rng = Random(7)
+        best_params, best_value, sampler = None, float("inf"), "random_fallback"
+        for _ in range(args.n_trials):
+            params = suggest(None, rng)
+            value, _detail = evaluate(params)
+            if value < best_value:
+                best_params, best_value = params, value
+
+    result = {"sampler": sampler, "n_trials": args.n_trials,
+              "best_value_s": best_value, "best_params": best_params,
+              "scenes": [name for name, _s, _e in SCENES],
+              "wall_s": perf_counter() - start,
+              "note": "回填前先以 benchmark_q3_bayes.py 全量复跑确认。"}
+    (args.out / "best_params.json").write_text(
+        json.dumps(result, ensure_ascii=False, indent=2), encoding="utf-8")
+    print(json.dumps(result, ensure_ascii=False, indent=2))
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/src/mcm26b/cli.py b/src/mcm26b/cli.py
index e0bc745..ca1b988 100644
--- a/src/mcm26b/cli.py
+++ b/src/mcm26b/cli.py
@@ -133,9 +133,10 @@ def main(argv=None) -> int:
     run.add_argument("--log", default=None, help="会话日志 JSONL 输出路径")
     run.add_argument("--problem", type=int, choices=(3, 4), default=3,
                      help="问题3=全向源，问题4=混合定向源（默认 3）")
-    run.add_argument("--strategy", choices=tuple(Q3_STRATEGIES), default="grid",
-                     help="问题3策略：grid=49点网格基线，seven=七点批量，"
-                          "bayes=粒子滤波+信息增益（默认 grid；仅 --problem 3 生效）")
+    run.add_argument("--strategy", choices=tuple(Q3_STRATEGIES), default="bayes",
+                     help="问题3策略：bayes=粒子滤波+信息增益+滚动调度（默认，"
+                          "自建消融相对 seven 再降 19.5%%），seven=七点批量，"
+                          "grid=49点网格基线；仅 --problem 3 生效")
     run.add_argument("--bearing-margin-deg", type=float, default=0.005,
                      help="示向度舍入裕量（服务器保留两位小数；默认 0.005°）")
     run.add_argument("--real-budget-s", type=float, default=None,
diff --git a/src/mcm26b/config.py b/src/mcm26b/config.py
index 01fb2b4..85fb8af 100644
--- a/src/mcm26b/config.py
+++ b/src/mcm26b/config.py
@@ -118,12 +118,8 @@ class BayesConfig:
     lambda_move_s: float = 0.1         # 选点评分中移动时间的折算系数（分值/秒）；
                                        # 与后验半径同量纲，量级须小否则终局拒走（欠收敛）
     wide_rings: tuple = (1.0, 1.5, 2.0)   # 无保证接收盘时的探索环（× PF MEC 半径）
-    # ---- 站点选择 [工程] ----
+    # ---- 站点与覆盖 [工程] ----
     station_ring_radius_m: float = 1200.0   # 七点环半径；覆盖半径 968.9m 的解析证明
-    inner_mass_weight: float = 0.5     # 站点评分中 1000m 内幸存质量的权重
-    resolve_bonus: float = 10.0        # "就地可证毕"（no_signal 即缺席/有信号即收敛）
-                                       # 频道的站点评分加成
-    station_move_penalty_s: float = 40.0   # 站点评分中移动时间（秒）的折算分母
     # ---- 任务排序 [工程] ----
     two_opt_enabled: bool = True       # 开放路径 2-opt 改进（最近邻打底）
     two_opt_passes: int = 3            # 2-opt 最大改进轮数
diff --git a/uv.lock b/uv.lock
index 8c8f9da..28daf3c 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,6 +1,26 @@
 version = 1
 revision = 3
 requires-python = ">=3.10"
+resolution-markers = [
+    "python_full_version >= '3.12'",
+    "python_full_version == '3.11.*'",
+    "python_full_version < '3.11'",
+]
+
+[[package]]
+name = "alembic"
+version = "1.19.2"
+source = { registry = "https://mirrors.aliyun.com/pypi/simple/" }
+dependencies = [
+    { name = "mako" },
+    { name = "sqlalchemy" },
+    { name = "tomli", marker = "python_full_version < '3.11'" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://mirrors.aliyun.com/pypi/packages/34/10/181eecdd552217d0342492bd6f3b8a96e973083379aace3d3402830ddc03/alembic-1.19.2.tar.gz", hash = "sha256:297950a8a91f6770eb82bfbce9bea55c728b90a5386c6e81430191a319d138b0" }
+wheels = [
+    { url = "https://mirrors.aliyun.com/pypi/packages/9c/cb/9014784dcb0585977ae23b6f43331d0a33c51ac0d692506d12b4f5ee9f3b/alembic-1.19.2-py3-none-any.whl", hash = "sha256:32d553dcd577e6fe5c3c63e91468526d35e4dcecafe865d7db4e9b328fa93cb2" },
+]
 
 [[package]]
 name = "certifi"
@@ -183,6 +203,18 @@ wheels = [
     { url = "https://mirrors.aliyun.com/pypi/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6" },
 ]
 
+[[package]]
+name = "colorlog"
+version = "6.12.0"
+source = { registry = "https://mirrors.aliyun.com/pypi/simple/" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://mirrors.aliyun.com/pypi/packages/8c/55/ba79756cb90c8d69d599d57785398ac87bba7b19c80e87f4e8a562197c93/colorlog-6.12.0.tar.gz", hash = "sha256:2a7924c1dadf18b22a0eb8b06d1c7b01d5341707ec1641eb6fcc4fde0c3e8e5f" }
+wheels = [
+    { url = "https://mirrors.aliyun.com/pypi/packages/d4/19/0b6647bf5e331521e55d2b63bfbdc210bd9cd605189273f03614a05f702d/colorlog-6.12.0-py3-none-any.whl", hash = "sha256:30d392604e9110045a2c2aeefc27d7a017abbab63f3a8aee594eac0801df784e" },
+]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.3.1"
@@ -195,6 +227,76 @@ wheels = [
     { url = "https://mirrors.aliyun.com/pypi/packages/8a/0e/97c33bf5009bdbac74fd2beace167cab3f978feb69cc36f1ef79360d6c4e/exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598" },
 ]
 
+[[package]]
+name = "greenlet"
+version = "3.5.5"
+source = { registry = "https://mirrors.aliyun.com/pypi/simple/" }
+sdist = { url = "https://mirrors.aliyun.com/pypi/packages/0b/d8/7cc97c142388aef03f622e001c572c4f84e9252a439549d483f555771970/greenlet-3.5.5.tar.gz", hash = "sha256:adb4bae02e91a8e863e48b177e4014bdcac8a6b5e047ea1df687a61534b85e6c" }
+wheels = [
+    { url = "https://mirrors.aliyun.com/pypi/packages/07/67/07ecd6d85c0f253363cbc4ac9e7dd048ca571a267fbccfea084d6009ac3b/greenlet-3.5.5-cp310-cp310-macosx_11_0_universal2.whl", hash = "sha256:816230f469381ad0a43abc9fa8dda5a699e32fb78958dde32ded93213b70a667" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/24/35/426733bc24247ee17bb76df90f550c299ff5f8572b2bdd7cacb5c53fd994/greenlet-3.5.5-cp310-cp310-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a5433cf291e0ef9114bd14d0d824db6e5e4a43033234bca48181a9597acca07b" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/9c/dc/17d3a5acceb2fd0bbc9682a228117b719cdfb68085e6dbb33fa325755f27/greenlet-3.5.5-cp310-cp310-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:19d59f068887d8c5907fc177f27683413ace3011b6ed646c0b309266e74a6502" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/51/91/00b3c0566316c6f383ea16ee05388ec4f57f6e0afa49e72ae471eda8c47f/greenlet-3.5.5-cp310-cp310-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9ff00e12102358292087274dfb1669132387ff6e7920ebf9d85f4826ce0d3a56" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/3c/78/52de4f7ac9152ad1dbc8f437895c1e573d30ee1e1427e0f91a280e2417b6/greenlet-3.5.5-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:523bb8e27614d77101ea7a8cf59f8d91219b72d5c29f6a038c92b50828bfa8d0" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/f6/ff/c3855a00c2417e8f61c7b9f0bc4f8f599c6928f5c15681ad251e78a91e05/greenlet-3.5.5-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f1e2db190db51c17433eee424803818cf0670bf049d9cfe0dd07be111d1aa7c4" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/70/21/d29ff6a79dbd1ec1fe74c155d25d4c5a85e221d6b9ffc2cc7a709e7c8c39/greenlet-3.5.5-cp310-cp310-win_amd64.whl", hash = "sha256:740e544169527b82695ce76af2f7ad6f030904658f2f3921a1d245771fb88cfc" },
+    { url = "https://mirrors.aliyun.com/pypi/packages/4e/a3/07297917485ee2ca85bc3c8dc6ed85ad3fffcf424047fba62671dba68e97/greenlet-3.5.5-cp311-cp311-macosx_11_0_universal2.whl", hash = "sha256:be63afcbbccfad3dd95a1ba12ada84dab2ef32031973d80b5b92df67fa763a61" },
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 name = "mcm26b"
 version = "0.2.0"
@@ -223,6 +422,7 @@ dependencies = [
 
 [package.dev-dependencies]
 dev = [
+    { name = "optuna" },
     { name = "pytest" },
 ]
 
@@ -230,7 +430,253 @@ dev = [
 requires-dist = [{ name = "requests", specifier = ">=2.31" }]
 
 [package.metadata.requires-dev]
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