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<title>ept.git/docs/hardware/EQOLION_DESIGN.md, branch master</title>
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<title>筛选正式闭卷(11优化器33臂): AdamW收口≈5.01; 增益钳位测试设计入档(逐元件vs逐模式饱和=唯一的坎, 预注册两结局)</title>
<updated>2026-08-05T15:35:27+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>yurenh2@illinois.edu</email>
</author>
<published>2026-08-05T15:35:27+00:00</published>
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Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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</entry>
<entry>
<title>偏置放大公理(用户08-06指出): 逐坐标归一化把持久小偏置放大成满幅漂移, sign全家同罪(否决只挡</title>
<updated>2026-08-05T13:18:11+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>yurenh2@illinois.edu</email>
</author>
<published>2026-08-05T13:18:11+00:00</published>
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方差不挡偏置); 曲率通道=偏置磁铁(E[s·ĝ]=βc+δ/β, 污染被1/β放大333×), 存活=两档|β|锁相分离;
评分表增第三轴=偏置放大系数, 器件电池预注册排序重排预测(per-matrix优雅退化/sign满幅/Dither翻身)。
附: --dump_grad探针+cautlion已实装。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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方差不挡偏置); 曲率通道=偏置磁铁(E[s·ĝ]=βc+δ/β, 污染被1/β放大333×), 存活=两档|β|锁相分离;
评分表增第三轴=偏置放大系数, 器件电池预注册排序重排预测(per-matrix优雅退化/sign满幅/Dither翻身)。
附: --dump_grad探针+cautlion已实装。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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</entry>
<entry>
<title>第二代原语优化器: SignLine/ConsensusLion/DitherLion 实装+本地筛选电池发射</title>
<updated>2026-08-05T11:48:06+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>yurenh2@illinois.edu</email>
</author>
<published>2026-08-05T11:48:06+00:00</published>
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R4后设计原则=只追不翻腾的目标。SignLine核心洞察: 正行/列缩放在sign内是无操作, 作为脉冲幅度
在sign外才有效=因子化自适应的模拟原生形态; ConsensusLion=双漏率电容+符合门的噪声否决;
DitherLion=免费噪声做期望软sign。KFAC-lite(追平稳的活动协方差)列为下一轮。
9臂与stage A同协议本地筛选中; 发射纪律教训追加: 发射与等待必须分Bash调用(超时杀树会扫掉setsid)。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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R4后设计原则=只追不翻腾的目标。SignLine核心洞察: 正行/列缩放在sign内是无操作, 作为脉冲幅度
在sign外才有效=因子化自适应的模拟原生形态; ConsensusLion=双漏率电容+符合门的噪声否决;
DitherLion=免费噪声做期望软sign。KFAC-lite(追平稳的活动协方差)列为下一轮。
9臂与stage A同协议本地筛选中; 发射纪律教训追加: 发射与等待必须分Bash调用(超时杀树会扫掉setsid)。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
</pre>
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</entry>
<entry>
<title>EqOLion R4(真实轨迹判决): 冻结极因子几十步退相关至~0.53=慢漂移前提对符号模式不成立(极均衡</title>
<updated>2026-08-05T11:40:24+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>yurenh2@illinois.edu</email>
</author>
<published>2026-08-05T11:40:24+00:00</published>
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放大病态尾部,小σ奇异向量高速旋转); 子满秩探针NaN, 满秩单迭代仅平基线; 存活空间收窄到温启动
全NS(3-5×)或Occam臂(行/列AGC)升主候选; 限定=最早期轨迹为最难工况, 晚期重dump后再判。
附: --dump_mom探针实装(601步×3矩阵/276MB)。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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放大病态尾部,小σ奇异向量高速旋转); 子满秩探针NaN, 满秩单迭代仅平基线; 存活空间收窄到温启动
全NS(3-5×)或Occam臂(行/列AGC)升主候选; 限定=最早期轨迹为最难工况, 晚期重dump后再判。
附: --dump_mom探针实装(601步×3矩阵/276MB)。

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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</entry>
<entry>
<title>EqOLion设计+当天三轮证伪: O(1)秩一探针死(两轮), 真实动量矩阵判决性救活(sign(M) vs sign(polar)</title>
<updated>2026-08-05T09:47:35+00:00</updated>
<author>
<name>Yuren Hao</name>
<email>yurenh2@illinois.edu</email>
</author>
<published>2026-08-05T09:47:35+00:00</published>
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<id>98e145cda386167ce6d9d20120b4e265b3a6471a</id>
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中位仅0.70, 偏斜55-156x, 正交化改写~30%符号=实在载荷); 成本算术修正(O(d)探针/漂移时标≈C次
通过/步, 非1-2%童话); 主分支改为搭车探针(nudged相位数千免费活动向量/步, 代价=数据度量白化
无理论); 下一轮=真实动量逐步轨迹上的追踪测试

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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中位仅0.70, 偏斜55-156x, 正交化改写~30%符号=实在载荷); 成本算术修正(O(d)探针/漂移时标≈C次
通过/步, 非1-2%童话); 主分支改为搭车探针(nudged相位数千免费活动向量/步, 代价=数据度量白化
无理论); 下一轮=真实动量逐步轨迹上的追踪测试

Co-Authored-By: Claude Fable 5 &lt;noreply@anthropic.com&gt;
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn
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