From 646f890833e2d3ff159debe45c186988e7081b16 Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Sat, 29 Aug 2026 13:27:33 -0500 Subject: fig: summarize the full physical grid crossover --- visual-composer/physical-grid-p5-contract.md | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) (limited to 'visual-composer/physical-grid-p5-contract.md') diff --git a/visual-composer/physical-grid-p5-contract.md b/visual-composer/physical-grid-p5-contract.md index 1c7b448..f938f1c 100644 --- a/visual-composer/physical-grid-p5-contract.md +++ b/visual-composer/physical-grid-p5-contract.md @@ -5,11 +5,10 @@ - Core claim: local state-dependent residualization restores physical local learning and composes with overclamping. - Reviewer question: does SDIL improve downstream classification over raw learning, constant calibration, and overclamping under the same component imperfections? - Evidence layer: main result. -- Source data: `results/physical_bias/p5_grid_bias_crossover.json`. -- Statistics: eight trials per input diameter (two label rotations by four device draws); show every trial and the arithmetic mean, without inferred uncertainty intervals. +- Source data: `results/physical_bias/p5_full_grid_bias_crossover.json`. +- Statistics: 32 trials per input diameter (eight label rotations by four device draws); show every trial and the arithmetic mean, without inferred uncertainty intervals. - Panel map: (a) raw, per-edge constant calibration, and SDIL under standard clamping; (b) overclamping and overclamping plus SDIL. - Labels: classification error (%), input diameter (mV), method names, eight trials per diameter. - Caption role: state the physical-grid setting, trial count, component-error model, and perfect-result counts without extending the evidence to hardware measurements. -- Output: `results/figs/physical_grid_p5.{svg,pdf,png}`. +- Output: `results/figs/physical_grid_p5_full.{svg,pdf,png}`. - Traceability: plotting code reads the committed JSON directly; no values are copied by hand. - -- cgit v1.2.3