QAdapt / REPRODUCTION_VALIDATION.json
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Rename QAdapt v1 checkpoint to Qadapt-r9-v1.safetensors
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{
"schema_version": 1,
"release_version": "v1",
"validated_at": "2026-07-29",
"status": "pass",
"upstream": {
"repository": "https://github.com/NVIDIA/Ising-Decoding.git",
"commit": "33acb152e403bc189f2effdb07f1a87b34c745f1",
"patch_sha256": "15f8e7d2f18158a769a5ba06d183239090c88c606519c8468f9a814998c6a986",
"git_apply_check": "pass",
"clean_clone_gpu_smoke": "pass"
},
"artifacts": {
"QAdapt": {
"relative_path": "Qadapt-r9-v1.safetensors",
"safetensors_sha256": "65f979c9f23f1b13b76876c6e5df204d1bd28b0e3322483d966db0efb840600d",
"source_checkpoint_sha256": "59d55a948a1a99458f7ccb0bba83335a779ef90eb8b36125407b65d45d771f9f",
"tensor_equality": "exact",
"tensor_count": 94,
"parameter_count": 650374
},
"Ising-Fast-T0-e100": {
"relative_path": "baselines/ising-fast-t0-e100/model.safetensors",
"safetensors_sha256": "af5e13e389358d4aa19afa92f6d1ff368e8f64e8497f23c51ddeed9d367f724a",
"source_checkpoint_sha256": "c23c9b1507cf4d213ce1b6526f87ee9e2f9db2bd8dc336c16f915b77724a0661",
"tensor_equality": "exact",
"tensor_count": 8,
"parameter_count": 912772
}
},
"environment": {
"python": "3.12.3",
"torch": "2.7.0a0+79aa17489c.nv25.04",
"numpy": "1.26.4",
"stim": "1.16.0",
"pymatching": "2.4.0",
"safetensors": "0.5.3",
"cuda": "12.9",
"gpu": "NVIDIA A100-SXM4-80GB"
},
"t0_t4": {
"status": "pass",
"protocol": {
"distance": 9,
"rounds": 9,
"shots_per_basis_per_task": 262144,
"bases": ["X", "Z"],
"seed": 12345
},
"actual_mean_ler_by_task": {
"T0": {
"pymatching": 0.045360565185546875,
"ising-fast": 0.04070091247558594,
"qadapt": 0.036182403564453125
},
"T1": {
"pymatching": 0.05428314208984375,
"ising-fast": 0.05145454406738281,
"qadapt": 0.046100616455078125
},
"T2": {
"pymatching": 0.15405654907226562,
"ising-fast": 0.14002418518066406,
"qadapt": 0.1307964324951172
},
"T3": {
"pymatching": 0.0500640869140625,
"ising-fast": 0.04494285583496094,
"qadapt": 0.040164947509765625
},
"T4": {
"pymatching": 0.098663330078125,
"ising-fast": 0.09106636047363281,
"qadapt": 0.0831298828125
}
},
"actual_mean_ler_across_tasks": {
"pymatching": 0.08048553466796875,
"ising-fast": 0.07363777160644532,
"qadapt": 0.06727485656738282
},
"qadapt_reduction_vs_ising_fast_percent": 8.64083051435735,
"max_absolute_ler_delta_vs_release_reference": 0.000681,
"interpretation": "All five tasks reproduce within ordinary finite-shot and software-version variation. The paper architecture table used different T0-only epochs and is not evidence for these final e100 artifacts."
},
"synthetic_ood": {
"status": "pass",
"protocol": {
"axis_combinations": 11,
"multipliers": [1.2, 1.5, 2.0, 2.5, 3.0],
"distances": [7, 9],
"jobs": 110,
"shots_per_basis_per_job": 262144,
"bases": ["X", "Z"]
},
"actual": {
"d7": {
"pymatching_mean_ler": 0.2453592127019709,
"ising_fast_mean_ler": 0.23453282442959872,
"qadapt_mean_ler": 0.2268583124334162,
"qadapt_reduction_vs_ising_fast_percent": 3.2722549668036893,
"qadapt_wins": 55,
"comparisons": 55,
"ising_fast_backend_latency_us_per_round": 2.446139354042408,
"qadapt_backend_latency_us_per_round": 2.300856614889897
},
"d9": {
"pymatching_mean_ler": 0.2519276358864524,
"ising_fast_mean_ler": 0.24441146850585938,
"qadapt_mean_ler": 0.23654133189808238,
"qadapt_reduction_vs_ising_fast_percent": 3.2200357274103615,
"qadapt_wins": 55,
"comparisons": 55,
"ising_fast_backend_latency_us_per_round": 5.014288594494714,
"qadapt_backend_latency_us_per_round": 4.730247553071063
}
},
"absolute_ler_delta_vs_paper": {
"d7_ising_fast": 0.00006020285866476,
"d7_qadapt": -0.00014780217950994,
"d9_ising_fast": -0.00002417130903765,
"d9_qadapt": 0.00000766407359728
},
"interpretation": "QAdapt wins all 110 retained comparisons. Backend timing is machine-dependent and excludes neural inference and transfers."
},
"willow": {
"status": "pass",
"protocol": {
"rounds": 10,
"bases": ["X", "Z"],
"fine_tuning": false,
"d5_shots": 400000,
"d7_shots": 100000
},
"actual": {
"d5": {
"ising_fast_logical_errors": 39852,
"ising_fast_ler": 0.09963,
"qadapt_logical_errors": 37543,
"qadapt_ler": 0.0938575,
"qadapt_reduction_vs_ising_fast_percent": 5.79393756900532,
"ising_fast_backend_latency_us_per_round": 0.7209028746001422,
"qadapt_backend_latency_us_per_round": 0.6945591699331999
},
"d7": {
"ising_fast_logical_errors": 8412,
"ising_fast_ler": 0.08412,
"qadapt_logical_errors": 8201,
"qadapt_ler": 0.08201,
"qadapt_reduction_vs_ising_fast_percent": 2.50832144555397,
"ising_fast_backend_latency_us_per_round": 1.344656078144908,
"qadapt_backend_latency_us_per_round": 1.3134985323995352
}
},
"ler_and_logical_error_match_to_paper": "exact",
"interpretation": "The third-party archive is not redistributed. Timing is machine-dependent; the LER and logical-error counts exactly reproduce the report."
},
"tests": {
"public_config": {"tests": 36, "status": "pass"},
"safetensors_export_and_load": {"tests": 9, "status": "pass"},
"compileall": "pass",
"full_upstream_suite": {
"tests": 456,
"successful": 424,
"skipped": 15,
"errors": 16,
"failures": 1,
"status": "environment_incomplete",
"non_release_blockers": {
"missing_optional_cuquantum": 11,
"missing_upstream_nvidia_model_files": 4,
"missing_optional_onnx_graphsurgeon": 2
}
},
"python_compat_script": {
"status": "environment_constraint_conflict",
"detail": "The script pinned the container's NVIDIA pre-release torch build while the public requirements requested the normal torch package, so pip stopped before code checks."
}
}
}