qig-bench

Artifact-validation harness and governance helpers for QIG experiment results.

Install

pip install qig-bench

Usage

from qig_bench import run_suite
from qig_bench.compare import compare

results = run_suite(backend="my-backend", verification_root="path/to/qig-verification")
table = compare({"my-backend": results})
print(table)

run_suite reads existing JSON artifacts; it does not run the named backend. The backend argument is a label. Reported time covers reading/validation and the bridge fit, not physics computation or QPU execution. Passing this suite checks stored-result consistency, not independent reproduction or speedup.

Core Benchmarks

Seven certified value-source benchmarks plus one Class-B reproduction-control.

κ supersession (2026-06-13, EXP-107 / frozen-facts-1.02F). The legacy ~63/64 matrix-trace kappa_L4 is a Class-B (FAIL-013) camera self-portrait, retired as a universal constant and kept here only as a labelled reproduction-control — never a value source. The certified κ slopes are small and signed: kappa_JT_cert = +0.02810 (row 9) and kappa_h = −0.00475 (row 2). The retired grid-interpolation benchmark regime_h_t (row 4) has been removed. Do not treat 63.32 / 63.79 / 64 as a physical constant.

The foundational readers use EXP-169's canonical registry result file, results/exp169/20260720_exp169_certified_foundational_series.json, selecting series[].kappa_certified_A1 at L=3 or L=4. Frozen-facts row 59 records the certified results (landed in 1.09F and retained in 1.11F); the July 21 rerun corroborates them but does not supersede the canon-nominated artifact. Missing, ambiguous or invalid certified entries fail; legacy fields never substitute.

For local checks: pip install -e ".[dev,certification]" then python -m pytest -q. Release CI runs these tests before building; tags derive versions via hatch-vcs.

The cross-package camera test follows qig-warp's current sensitivity-based dmrg_tolerance contract (precision / |dO/dE|), not the retired Anderson size-scaling assumption. Its MPS fixture uses actual TeNPy SpinHalfSite objects. Release CI installs the certification extras so these checks run rather than skip.