{
  "request_url": "/research/api/request",
  "results": [
    {
      "abstract": "A diffusion generator trained on 300 checkpoints of a small MLP's last layer was asked to produce new weights at equal accuracy. It copied: for every one of 600 generated samples, some training checkpoint predicts the same class on all 450 test inputs.",
      "caveats": [
        "One 330-parameter head on 8x8 digits",
        "Replicates Zeng et al. 2025 (copying)"
      ],
      "date": "2026-10-13",
      "key_numbers": [
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          "complete_digest": "2bffc7f62ddbdaf25d759b32677a49f93f81dda53f762d6f758f8051722397f2",
          "displayed_prefix": "2bffc7f62ddbdaf2",
          "label": "generated samples with zero disagreement novelty",
          "sha256": "2bffc7f62ddbdaf25d759b32677a49f93f81dda53f762d6f758f8051722397f2",
          "source": "weightgen-audit/runs/2026-10-13/results.json",
          "value": "600 of 600"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "weight-generator-memorisation",
      "title": "Can a generator write new network weights?",
      "url": "https://qmai.dev/research/weight-generator-memorisation/",
      "verdict": "MISS"
    },
    {
      "abstract": "With symmetry augmentation the generator stopped copying but degraded: mean accuracy 0.86-0.88 versus 0.96 for the checkpoints, and its samples sat about as far away as plain noise.",
      "caveats": [
        "One 330-parameter head on 8x8 digits"
      ],
      "date": "2026-10-13",
      "key_numbers": [
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          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "15c9b6f5e0b98f4d",
          "label": "generated mean accuracy",
          "sha256": "15c9b6f5e0b98f4d",
          "source": "weightgen-audit/runs/2026-10-13-symm/results.json",
          "value": "0.86-0.88 (checkpoints 0.96)"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "weight-generator-symmetry-arm",
      "title": "Same audit, symmetry-augmented generator",
      "url": "https://qmai.dev/research/weight-generator-symmetry-arm/",
      "verdict": "MISS"
    },
    {
      "abstract": "A template search over optimizer update rules won on its training tasks but beat tuned Adam on only 0, 1 and 0 of 4 held-out task families across three seeds (3 of 4 needed). The best rules were bounded Adam variants that overfit two training instances.",
      "caveats": [
        "Template mutator, not a model",
        "5 held-out seeds per family (smallest p = 1/32)"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public",
          "complete_digest": "70f64a1fce5db56ef05fd228e2a49d5aa850dabf8230c9f73e5250575c0abd0f",
          "displayed_prefix": "70f64a1fce5db56e",
          "label": "held-out families beaten per seed (need 3 of 4)",
          "sha256": "70f64a1fce5db56ef05fd228e2a49d5aa850dabf8230c9f73e5250575c0abd0f",
          "source": "rule-search-lab/runs/2026-10-13/RESULTS.json",
          "value": "0/4, 1/4, 0/4"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "optimizer-rule-search-run-1",
      "title": "Can a search invent a better optimizer? (run 1)",
      "url": "https://qmai.dev/research/optimizer-rule-search-run-1/",
      "verdict": "MISS"
    },
    {
      "abstract": "With 8 training instances per family the search again failed on held-out families (0, 0 and 1 of 4). The hypothesis that more training instances shrink the train/held-out gap was not supported: it shrank on 2 seeds and grew on 1.",
      "caveats": [
        "Template mutator, not a model"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "a6340037f38c893c",
          "label": "held-out families beaten per seed (need 3 of 4)",
          "sha256": "a6340037f38c893c",
          "source": "rule-search-lab/runs/2026-10-13-run2/RESULTS.json",
          "value": "0/4, 0/4, 1/4"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "optimizer-rule-search-run-2",
      "title": "Can a search invent a better optimizer? (run 2, 8 training instances)",
      "url": "https://qmai.dev/research/optimizer-rule-search-run-2/",
      "verdict": "MISS"
    },
    {
      "abstract": "Turning a server's prompt cache on changed 39 of 720 replies (5.4%). Strict verdicts changed in 5 of 720 cases, which is not significant (the confidence interval starts at 0).",
      "caveats": [
        "Two small models near the accuracy floor, CPU, one server build"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public",
          "complete_digest": "f9b7ba116c66772ce7312c330cc0087fb04819c50e506d6790a1d5c226d31511",
          "displayed_prefix": "f9b7ba116c66772c",
          "label": "replies changed",
          "sha256": "f9b7ba116c66772ce7312c330cc0087fb04819c50e506d6790a1d5c226d31511",
          "source": "cache-flip-study/runs/2026-10-13-droplet/results.json",
          "value": "39 of 720 (5.4%)"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public",
          "complete_digest": "f9b7ba116c66772ce7312c330cc0087fb04819c50e506d6790a1d5c226d31511",
          "displayed_prefix": "f9b7ba116c66772c",
          "label": "verdicts changed",
          "sha256": "f9b7ba116c66772ce7312c330cc0087fb04819c50e506d6790a1d5c226d31511",
          "source": "cache-flip-study/runs/2026-10-13-droplet/results.json",
          "value": "5 of 720 (not significant)"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "prompt-cache-verdict-flips",
      "title": "Does a server's prompt cache change evaluation verdicts?",
      "url": "https://qmai.dev/research/prompt-cache-verdict-flips/",
      "verdict": "MISS"
    },
    {
      "abstract": "On a randomly initialised tiny model both methods sat near chance; the score ratios were 0.842, 1.059 and 0.957 (0.9 needed on every seed). Inconclusive.",
      "caveats": [
        "Random-init model; CPU memory only"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public",
          "complete_digest": "20da7001daf41faf5bbeec1c89fa7bfe3fe57effb380be250ff85f2e6212818b",
          "displayed_prefix": "20da7001daf41faf",
          "label": "score ratio per seed (need 0.9 each)",
          "sha256": "20da7001daf41faf5bbeec1c89fa7bfe3fe57effb380be250ff85f2e6212818b",
          "source": "mezo-vs-adam/runs/2026-10-13/results.json",
          "value": "0.842, 1.059, 0.957"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "mezo-vs-adamw-pilot-1",
      "title": "Memory-light fine-tuning (MeZO) vs AdamW-LoRA, pilot 1",
      "url": "https://qmai.dev/research/mezo-vs-adamw-pilot-1/",
      "verdict": "MISS"
    },
    {
      "abstract": "From a pretrained tiny base, AdamW-LoRA reached 0.987-0.995 while MeZO reached 0.55-0.60 of that score (0.9 needed). This pilot separates the methods; MeZO scored almost nothing on the generation task.",
      "caveats": [
        "Tiny 2-layer model, CPU"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "8166e81199f16d5e",
          "label": "MeZO score ratio per seed (need 0.9)",
          "sha256": "8166e81199f16d5e",
          "source": "mezo-vs-adam/runs/2026-10-13-pilot2/results.json",
          "value": "0.60, 0.55, 0.60"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "mezo-vs-adamw-pilot-2",
      "title": "Memory-light fine-tuning (MeZO) vs AdamW-LoRA, pilot 2",
      "url": "https://qmai.dev/research/mezo-vs-adamw-pilot-2/",
      "verdict": "MISS"
    },
    {
      "abstract": "A pre-registered per-task viability gate was applied to a small adapter-training pilot on six tasks. Only 3 of 6 tasks were viable (the rule needed 4), so the gate said stop.",
      "caveats": [
        "The results file itself was not sealed",
        "A 0.0025 miss is inside one standard error"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public",
          "complete_digest": "b8fb0e758968ccda948da345c82806a3baad5529e3789d472f5eaf75ebd6447f",
          "displayed_prefix": "b8fb0e758968ccda",
          "label": "viable tasks (need 4 of 6)",
          "sha256": "b8fb0e758968ccda948da345c82806a3baad5529e3789d472f5eaf75ebd6447f",
          "source": "sealed-gate/examples/r3_stage_a/STAGE_A_PUBLIC.json",
          "value": "3 of 6"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "sealed-gate-adapter-pilot",
      "title": "A sealed gate on a six-task adapter-training pilot",
      "url": "https://qmai.dev/research/sealed-gate-adapter-pilot/",
      "verdict": "STOP"
    },
    {
      "abstract": "On 64 held-out graphs (CPU simulation), a learned model wrote QAOA angles with a mean approximation ratio of 0.766 versus 0.812 for one fixed angle set. The pilot is valid; the learned generator missed.",
      "caveats": [
        "Pilot on one graph family; per-graph optimisation beats fixed angles by only about 0.007"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "706df148f5f02d81",
          "label": "mean approximation ratio, p=1 (learned vs fixed)",
          "sha256": "706df148f5f02d81",
          "source": "qaoa-weightgen/runs/2026-10-13-pilot/summary.json",
          "value": "0.766 vs 0.812"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "qaoa-angle-generation-pilot",
      "title": "Can AI write a quantum circuit's settings? (QAOA pilot)",
      "url": "https://qmai.dev/research/qaoa-angle-generation-pilot/",
      "verdict": "MISS"
    },
    {
      "abstract": "A 2-qubit entangled circuit on Rigetti's 108-qubit Cepheus chip (via Amazon Braket) matched on 98 of 100 shots; the simulator matched 100 of 100. A pipeline test, not a science result; 100 shots can estimate this run's observed mismatch proportion only with wide uncertainty, not a general device or circuit error rate.",
      "caveats": [
        "Not pre-registered",
        "100 shots is a smoke test"
      ],
      "date": "2026-10-13",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "9f9d0634c67b0de8",
          "label": "matched shots, real chip",
          "sha256": "9f9d0634c67b0de8",
          "source": "smoke-20261013/results_cepheus.json",
          "value": "98 of 100"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "0632ec0afc6397c8",
          "label": "matched shots, simulator",
          "sha256": "0632ec0afc6397c8",
          "source": "smoke-20261013/results_sv1.json",
          "value": "100 of 100"
        }
      ],
      "kind": "pipeline-test",
      "preregistered": false,
      "slug": "first-qpu-pipeline-test",
      "title": "Our first circuit on a real quantum chip (pipeline test)",
      "url": "https://qmai.dev/research/first-qpu-pipeline-test/",
      "verdict": "PIPELINE TEST"
    },
    {
      "abstract": "QMAI evaluated a pre-registered readout statistic in two valid run blocks on the Cepheus-1-108Q device. The A-arm primary test rejected in B1 and B2 at the fixed per-block threshold of 1/300, with exact p-values of 8.68e-12 and 7.49e-14 and positive excess statistics of +0.00213 and +0.00257. A third required block was not run because of the queue gate (the device's job queue held 2 other jobs at the block's start time, above the pre-set limit of 0, so no task was created), so the campaign disposition is INCOMPLETE. No replication or non-replication conclusion is available. This note reports the two per-block results, the missing block, the recorded recomputation, and the limits that remain.",
      "caveats": [
        "No replication or non-replication conclusion is available.",
        "The calibration timestamp was unavailable, and independent calibration replications were not established.",
        "The per-block calculation assumes that shots are exchangeable and independent; this program did not establish those assumptions."
      ],
      "date": "2026-10-20",
      "key_numbers": [
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "9bda7681fe29e29b",
          "label": "valid run blocks rejected at 1/300 (B3 not run: queue gate)",
          "sha256": "9bda7681fe29e29b",
          "source": "quantum-2block/SUMMARY_R1.md",
          "value": "2 of 2 run (3 required)"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "9bda7681fe29e29b",
          "label": "exact p, B1 and B2",
          "sha256": "9bda7681fe29e29b",
          "source": "quantum-2block/SUMMARY_R1.md",
          "value": "8.68e-12 and 7.49e-14"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "9bda7681fe29e29b",
          "label": "excess statistic delta, B1 and B2",
          "sha256": "9bda7681fe29e29b",
          "source": "quantum-2block/SUMMARY_R1.md",
          "value": "+0.00213 and +0.00257"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "quantum-readout-replication-2-block",
      "title": "Two-block readout analysis: a campaign left incomplete",
      "url": "https://qmai.dev/research/quantum-readout-replication-2-block/",
      "verdict": "INCOMPLETE"
    },
    {
      "abstract": "QMAI ran a pre-registered, three-resolution check of a three-body gravity scene driven by eight seeded player commands. The checker first passed three controls, then tested four seeds chosen before the episodes. All four seed runs emitted zero flags; their eight energy-error ratios ranged from 3.9999905410799816 to 3.999997730513573, inside the frozen inclusive band from 3.96 to 4.04. The largest momentum or angular-momentum residual in the seed runs was 1.1102230246251565e-15, and every such residual stayed below its pre-registered roundoff bound. Under the frozen rule, the report's verdict is G1_PASS. This runs on a test branch of our engine and is not in a released game yet; there are no collisions in this world yet.",
      "caveats": [
        "This runs on a test branch of our engine and is not in a released game yet; there are no collisions in this world yet.",
        "Four pre-selected seeds are a narrow sample."
      ],
      "date": "2026-10-20",
      "key_numbers": [
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          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "4a5376bd6276e102",
          "label": "energy-error ratios, 4 seeds x 2 (band 3.96-4.04)",
          "sha256": "4a5376bd6276e102",
          "source": "g1-physics/report.json",
          "value": "3.9999905410799816 to 3.999997730513573"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "4a5376bd6276e102",
          "label": "largest momentum or angular-momentum residual",
          "sha256": "4a5376bd6276e102",
          "source": "g1-physics/report.json",
          "value": "1.1102230246251565e-15"
        },
        {
          "algorithm": "SHA-256",
          "artifact_availability": "repository_relative_not_public_prefix_only",
          "complete_digest": null,
          "displayed_prefix": "4a5376bd6276e102",
          "label": "seed runs with zero flags",
          "sha256": "4a5376bd6276e102",
          "source": "g1-physics/report.json",
          "value": "4 of 4"
        }
      ],
      "kind": "experiment",
      "preregistered": true,
      "slug": "game-physics-self-check-g1",
      "title": "A three-body game-world check of energy order and conserved quantities",
      "url": "https://qmai.dev/research/game-physics-self-check-g1/",
      "verdict": "G1_PASS"
    }
  ],
  "schema_version": 2,
  "site": {
    "inventory": {
      "file": "FINDINGS_INVENTORY_20261014_r4.md",
      "file_note": "Filename embeds 2026-10-14 inventory revision; not the latest entry date.",
      "schema_version": 2,
      "sha256_16": "c5b7ebbf9cca5da3",
      "updated_at": "2026-10-20"
    },
    "links": [
      {
        "channel": "YouTube",
        "url": "https://youtu.be/_jruF8kcso0"
      },
      {
        "channel": "LinkedIn (QuantumMind AI)",
        "url": "https://www.linkedin.com/feed/update/urn:li:activity:7516129354016284672/"
      },
      {
        "channel": "LinkedIn (founder)",
        "url": "https://www.linkedin.com/feed/update/urn:li:ugcPost:7516094190192234496"
      },
      {
        "channel": "X",
        "url": "https://x.com/QuantumMindAI/status/2110328572804010173"
      },
      {
        "channel": "Facebook",
        "url": "https://www.facebook.com/2202245964039121"
      },
      {
        "channel": "Instagram",
        "url": "https://www.instagram.com/reel/DeeQNf3gOq8/"
      },
      {
        "channel": "TikTok",
        "url": "https://www.tiktok.com/@quantummindaillc/video/7696480863743249695"
      }
    ],
    "method": "For each pre-registered experiment in this index, the pass rule was written down and sealed by hash before the run. Each ran once and is reported as-is. The first public cohort (2026-10-13) listed nine pre-registered experiments plus one pipeline test; two additional pre-registered experiments were added on 2026-10-20 (see results[] and preregistered fields).",
    "roundup_video": {
      "sha256_16": "3de55bc330bba5f8",
      "title": "What we tested, and what we learned (90 s)"
    },
    "tagline": "What we tested, and what we learned. Misses included.",
    "title": "QMAI Research",
    "write_up_access": "Full write-ups are not public yet. You can request one; requests are reviewed by hand."
  },
  "updated_at": "2026-10-21"
}