Add new experiment scripts, figures, and paper assets; untrack pyc/build artifactsHEADmaster

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

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+# Training Inventory
+
+Generated: 2026-04-25. Source: `results/` directory scan.
+
+## Summary
+
+| Dimension | Count |
+|---|---|
+| **Total training runs** | **125** |
+| **Unique models** (method × arch × seed × setting) | **125** |
+| **Total training epochs** | **9,410** |
+| **Estimated total GPU time** | **~10.5 hours** |
+| **Training methods** | **10** (6 primary + 4 frozen-baseline variants) |
+| **Architectures** | **5 base + 5 depth variants** |
+| **Experiment settings** | **~20 distinct** |
+| **Method × architecture combinations** | **31** |
+
+## By Method (10 types)
+
+| Method | Runs | Description |
+|---|---|---|
+| DFA | 45 | Direct Feedback Alignment (Nokland 2016). Output error projected directly to each layer via fixed random d×C matrix. |
+| **FA** (NEW) | **21** | Vanilla Feedback Alignment (Lillicrap 2016). Sequential backward credit propagation with fixed random d×d matrices. |
+| EP | 13 | Equilibrium Propagation. Contrastive energy-based, nudged-vs-free phase. Internal control (trustworthy). |
+| BP | 12 | Backpropagation. End-to-end exact gradients. Gold standard control. |
+| State Bridge (SB) | 11 | Diagnostic probe: learns to predict h_L from (h_l, t_l, s), derives credit via target-prop-style gradient. |
+| Credit Bridge (CB) | 11 | Diagnostic probe: learns a value network V(h_l, t_l, s), derives credit via synthetic-gradient-style input gradient. |
+| BP-shallow | 3 | BP training only embedding + head, blocks frozen. Frozen baseline variant. |
+| BP-frozen | 3 | BP training only embedding + head, blocks frozen at random init. |
+| DFA-shallow | 3 | DFA training only embedding + head, blocks frozen. Architecture-matched baseline for diagnostic (d). |
+| DFA-frozen | 3 | DFA training only embedding + head, blocks frozen at random init. |
+
+## By Architecture (5 base + depth variants)
+
+| Architecture | Runs | Role in paper |
+|---|---|---|
+| **ResMLP d=256 L=4 + terminal LN** | 89 | Primary audit architecture. 4-block pre-LayerNorm residual MLP, CIFAR-10. |
+| **SmallCNN BatchNorm** | 15 | Cross-architecture control. No terminal LN → Mode 1(b) does not fire. |
+| **ResMLP d=256 L=4 no-terminal-LN** | 3 | Same-backbone causal control for terminal LN. Preserves Mode 1(a), eliminates 1(b). |
+| **ResMLP d=256 L=4 no-residual-skip** | 3 | Falsification control. Shows residual skip is NOT necessary for Mode 1. |
+| **ViT-Mini d=128 L=4 (cls token + LN)** | 3 | Cross-architecture: transformer with terminal LN. Both Mode 1 diagnostics fire by epochs 2-3. |
+| **ResMLP d=512 L=2** | 2 | Depth sweep (DFA + FA). |
+| **ResMLP d=512 L=4** | 4 | Depth sweep (DFA 3-seed + FA). |
+| **ResMLP d=512 L=6** | 2 | Depth sweep (DFA + FA). |
+| **ResMLP d=512 L=8** | 2 | Depth sweep (DFA + FA). |
+| **ResMLP d=512 L=12** | 2 | Depth sweep (DFA + FA). |
+
+## By Experiment Setting (~20 types)
+
+| Setting | Runs | Epochs | Description |
+|---|---|---|---|
+| Main audit | 18 | 100 | 6 methods × 3 seeds on d=256 ResMLP. Table 1. |
+| Cross-architecture | 18 | 100 | DFA/BP/EP/SB/CB on CNN + DFA on ViT-Mini. §5.2. |
+| Depth sweep | 12 | 100 | DFA + FA at d=512, L∈{2,4,6,8,12}. Appendix H. |
+| Frozen blocks baseline | 12 | 100 | BP/DFA × shallow/frozen × 3 seeds. Diagnostic (d). |
+| Penalty rescue λ=1e-2 | ~12 | 30 | DFA/FA/SB/CB + penalty. §5.1 + §4.2. |
+| Penalty sweep λ=1e-4 | 6 | 30 | DFA + FA at weaker penalty. §5.1 λ sweep. |
+| Penalty λ=1e-1 | 1 | 30 | DFA at stronger penalty. |
+| BP+penalty control | 3 | 30 | Capacity-cost control. §5.2. |
+| Matched 30ep no-pen | 9 | 30 | BP/DFA/FA without penalty at 30 epochs. §5.2 matched controls. |
+| SB/CB vanilla baseline | 2 | 30 | Appendix J. |
+| No-terminal-LN ablation | 3 | 100 | DFA on same backbone minus terminal LN. §3.2. |
+| No-residual ablation | 3 | 100 | DFA on same backbone minus skip path. §3.1 falsification. |
+| Random-target ablation | 4 | 100 | DFA/FA/SB+CB/EP with i.i.d. random labels. §3.1. |
+| Early checkpoints | 6 | 5 | DFA + FA at 5 epochs for Mode 2 identification. §4.1. |
+| Snapshot evolution | 3 | 100 | DFA per-epoch trajectory (h_L, g_L logged). §3.1. |
+| DFA+pen 100ep | 3 | 100 | Long-horizon penalty rescue. |
+| EP baseline (6 seeds) | 6 | 100 | Extended EP replication. |
+
+## FA vs DFA Comparison (the key new finding)
+
+Same local loss ⟨f_l, a_l⟩, same architecture, same optimizer. Only difference: how a_l is computed.
+
+| | FA (21 runs) | DFA (45 runs) |
+|---|---|---|
+| Credit signal | Sequential backward: a_l = B_l @ a_{l+1} (d×d random) | Direct projection: a_l = B_l^T @ e_T (d×C random) |
+| Test acc (d=256, 100ep, 3-seed) | **0.401 ± 0.009** | 0.306 ± 0.008 |
+| vs frozen baseline 0.349 | **+5.2 pp above** | -4.3 pp below |
+| Deep cos | **+0.33** (genuine) | ~0 (degenerate) |
+| ‖h_L‖ | ~10⁵ | ~5×10⁸ |
+| ‖g_L‖ | ~10⁻⁶ (meaningful) | ~10⁻¹⁰ (floor) |
+| Mode 1(b) fires? | **NO** | YES |
+
+## Cross-Method Functional Triangulation (under penalty rescue)
+
+| Metric | SB+pen | CB+pen | DFA+pen | Ordering |
+|---|---|---|---|---|
+| Accuracy | **0.453** | 0.360 | 0.360 | SB ≫ CB ≈ DFA |
+| Nudging (loss Δ) | **-1.93e-3** | -4.26e-4 | -4.98e-5 | SB ≫ CB ≈ DFA |
+| Training loss decrease | **-0.447** | -0.121 | -0.095 | SB ≫ CB ≈ DFA |
+| Deep cos | +0.322 | **+0.679** | +0.151 | CB > SB > DFA |
+
+3 functional metrics agree on SB ≫ CB ≈ DFA. Deep cosine is the only one that disagrees.
+
+## File Locations
+
+All training results are in `results/`. Key directories:
+- `results/protocol_audit/` — main 5-method audit + temporal evolution + CNN + d=512
+- `results/fa_main_audit/` — FA 100ep 3-seed
+- `results/fa_depth_scan_d512_L{2,4,6,8,12}/` — FA depth sweep
+- `results/fa_penalty_30ep/`, `results/fa_penalty_lam1e-4_30ep/` — FA + penalty
+- `results/fa_random_targets_s42/`, `results/fa_early_ckpts/` — FA ablations
+- `results/dfa_pen_short/` — DFA penalty sweep (lam=0.01, 0.0001, 0.1)
+- `results/round38_*_penalty_30ep*/` — SB+pen, CB+pen 3-seed
+- `results/round41_dfa_penalty_30ep*/` — DFA+pen 3-seed diagnostics
+- `results/bp_with_penalty/`, `results/bp_no_penalty_30ep/` — BP ± penalty
+- `results/dfa_no_penalty_30ep/`, `results/fa_no_penalty_30ep/` — matched 30ep
+- `results/snapshot_no_outln_v1/` — no-terminal-LN ablation
+- `results/h2_no_residual_full_s*/` — no-residual ablation
+- `results/snapshot_vit_v1/` — ViT-Mini
+- `results/ep_baseline/` — EP 6-seed
+- `results/resmlp_frozen_blocks_s*.log` — frozen baseline
+
+Reproducibility notebook: `reproduce_all.ipynb`
+All ± values use ddof=1 (sample std with Bessel correction).