E-tier wave-1 ledger (RESULT 14 + HW map rows) + cost model v2 recalibrated on measured H200 datapoint

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn

1 files changed, 24 insertions, 0 deletions

diff --git a/docs/campaign/CASCADE_ABLATION_PLAN.md b/docs/campaign/CASCADE_ABLATION_PLAN.md
index 61860f6..8b52369 100644
--- a/docs/campaign/CASCADE_ABLATION_PLAN.md
+++ b/docs/campaign/CASCADE_ABLATION_PLAN.md
@@ -538,3 +538,27 @@ s1 alone beat the BP mean). Ledger of the residual-0.05 epoch gap after three pr
 Carry `--bsign_rand` and a future centered mode as Stage-2 A/B flags; the gap question re-opens at
 300M/real-corpus where it means something. Effort pivots to: (1) Stage-2 data pipeline (FineWeb-Edu +
 32k tokenizer), (2) E-tier tolerance suite on the idle farm (hardware track / UIUC outreach feed).
+
+### RESULT 14 (2026-07-12): E-TIER WAVE-1 — full analog-fault tolerance ledger at stage1b s55000.
+`etier_probe.py`, farm GPUs 2/3/7 (shards A/B/C), stage1b_ep_muon_s55000.pt (clean valCE 1.2678),
+B=8 eval batches; metrics = faulted valCE (Δ vs clean), cos(EP_faulted, BP_faulted) [self-consistency
+of the learning signal under fault], cos(EP_faulted, BP_clean) [direction vs the ideal update].
+
+| fault (component) | mild | medium | severe | verdict |
+|---|---|---|---|---|
+| wq — weight quant (crossbar #3) | 8b: +0.004 / 0.956 | 6b: +0.051 / 0.812 | 4b: +2.23 / 0.05 | **8b FREE, 6b marginal, 4b dead → ≥7b effective is the binding spec** |
+| fnoise — fwd additive state noise (softmax/relax #5) | 1e-3: 0.000 / 0.975 | 3e-3: 0.000 / 0.974 | 1e-2: +0.001 / 0.970 | **FREE at 1% — looped-era 1e-3 cliff does NOT transfer to cascade** |
+| divmis — divisive-norm mismatch (#4/#7) | 1%: 0.000 / 0.971 | 3%: +0.003 / 0.948 | 10%: +0.042 / 0.785 | 3% (routine matching) FREE; 10% marginal |
+| rope — phase error rad (#2) | 0.01: 0.000 / 0.973 | 0.03: +0.001 / 0.967 | 0.1: +0.012 / 0.923 | 0.03 rad FREE; ~2° I/Q accuracy suffices |
+| gilbert — gate gain error (#6) | 1%: 0.000 / 0.974 | 3%: 0.000 / 0.971 | 10%: +0.006 / 0.945 | **FREE at 10%** — translinear practice is comfortably inside |
+| fbnoise — nudge/error-channel noise | 1e-2: 0.969 / 0.975 | **1e-1: 0.951 / 0.957** | 3e-1: 0.764 / 0.768 | **10% relative noise on the ERROR CHANNEL is FREE** (cos 0.95) — the r-indifference/large-nudge gift, now measured on cascade |
+
+Reading: (a) the only hard constraint is crossbar weight precision (≥7b effective — inside standard
+SRAM-CIM capability; 6b rescue = wave-2 quant-aware co-training); (b) everything dynamic — forward
+noise 1%, error-channel noise 10%, gate/divider/phase mismatch at routine device tolerances — is
+FREE at this scale. cos(EP,BP_faulted) stays ~0.97 under every non-fatal fault: the EP estimator
+tracks whatever network the faults define, i.e. learning co-adapts to the fault (the analog-training
+thesis in one number). CAVEAT: static probes at a trained checkpoint (eval CE + one-step gradient
+direction), not training-under-fault; wave-2 = co-training with faults injected from step 0
+(expectation from the literature and from (c): tolerances IMPROVE). Feeds COMPONENT_HW_MAP.md
+(per-row status updated) + UIUC outreach dossier.