Open QEC harness – greedy vs. GE, uniform vs. clustered k=4

QEC Evaluation Suite

Finite-size diagnostic tooling for circuit-level and holographic-style quantum error correction.

Digital evaluation / telemetry only — not hardware, not a production decoder, not an asymptotic threshold paper.

Layer C framing: tensor-network model of bulk-boundary encoding with greedy recovery (HaPPY); optional matched-sample GF(2) GE ablation.

Claims detail: QEC_CLAIMS.md · Prefer JSON under public/data/ if anything disagrees with this README.

Layers

Layer What it is Primary artifacts A Surface Stim rotated surface; graphlike DEM; MWPM smoke public/data/layer_a_surface_smoke.json A Floquet Period-3 honeycomb; schedule-valid; not graphlike MWPM peer of surface public/data/layer_a_floquet_smoke.json B Geometry Educational graph invariants — not circuit-level QEC public/data/geometry_lab_metrics.json C HaPPY Depth-1 (n=10, k=6) & capped depth-2 (n=20, k=16); greedy + matched GE public/data/happy_*.json

Headline results (reproducible JSON)

Matched greedy vs GE (same erasure masks)

Depth p_erase Greedy central GE central 1 0.3 0.664 0.304 2 0.3 0.59 0.0575

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