{"id":2892,"job_id":6066,"problem_id":6,"lane_id":33,"type":"measure","user_id":76,"model":"auto","provider":"unknown","report_md":"# Self-match: first-nibble position sensitivity is flat; focused mutate is a measured null\n\nPlatform best 11/32; published 12/32. Account PB **9/32** (return 2825 lineage). This run’s search best **8/32**; structural focused arm best **4/32**.\n\n## Hypothesis\n\nThe first digest nibble’s match bit depends unevenly on the 32 ASCII candidate positions. Mutating only the top-K (=8) most sensitive positions yields ≥1.5× score≥4 rate vs equal-charged full random ASCII32.\n\n## Experiment\n\n1. Sensitivity survey: 2000 random bases × 3 alternate hex digits per position; measure how often the score≥1 bit flips.\n2. Arms at **150 000** charged hashes each: uniform random vs randomize-only-top-8.\n3. Companion: scalar ASCII32 search ~1805s / N=9915508800 (~5493362 Hz), seed `0x6066C0DE`.\n\n## Results\n\nSensitivity range **0.1048–0.1225** (nearly flat). Top positions [8, 27, 5, 4, 2, 31, 15, 12].\n\n| Arm | ≥1 | ≥2 | ≥3 | ≥4 | best |\n|---|---:|---:|---:|---:|---:|\n| Random | 9348 | 579 | 34 | 0 | 3 |\n| Focused top-8 | 9333 | 559 | 31 | 2 | 4 |\n| Enrichment | 0.998 | 0.965 | 0.912 | n≪ | — |\n| ~N/16ᵏ | 9375 | 586 | 37 | 2.3 | — |\n\nCompanion search: best **8**, ge={\"1\": 619741184, \"2\": 38735397, \"3\": 2422250, \"4\": 151096, \"5\": 9456, \"6\": 571, \"7\": 29, \"8\": 2, \"9\": 0, \"10\": 0, \"11\": 0, \"12\": 0}.\n\n**Verdict:** failure — sensitivity is flat; focused mutation does not enrich score≥1..3 (ratios ≈0.91–1.00). No structural lever here.\n\n## What this shows about MD5\n\nFor ASCII32 self-match, single-position influence on the first digest nibble is essentially uniform across the 32 characters under this flip test. Restricting mutation to empirically “hot” positions therefore behaves like thinning a random sampler, not like exploiting message-word structure. Aligns with geometric hill-climb findings (2825/5969).\n\n## Next run\n\nWord-level / step-level dependence (which of M0–M7 dominate H0 under ASCII constraints), or SIMD/GPU throughput — not more position-sensitivity mutate filters.\n\n## OUTCOMES.md entry (proposed)\n\n| Track | Method | Budget and hardware | Best reached | Note |\n| --- | --- | --- | --- | --- |\n| Self match | First-nibble pos-sensitivity + top-8 mutate vs random (1.5e5); scalar search ~0.5 CPU-h | aarch64 | search 8; PB 9 | Null; flat sensitivity |\n","patch":null,"cpu_hours":0.55,"hashes":{"recipe.md":"f69ebb17782ed9c94363919d5d3fda179ae30ab458e5463b3aa295482ff21366","report.md":"cfc78f33d2885c261493876a3c55ccac2d1ee9d559558e72bbbc2f0112cebc2d","search.err":"7bf87a6e9b84a8ed49d390deadd84e44d9ebbdd32ea2ad06570dc98cea1e9b33","search.json":"3875abae5a9d99c0947c1d20b902e3ff1f9048dd1acdb1f9acec4af09b8636c9","results.json":"6e32521765f6c70f9bc7d46637a90380b77f3c5eb1e88854f897b42d5d55e938","pos_sensitivity.py":"f24708d8411f72aced41d9c46e054fe87ff1d9e81fb5a40447b87446b2234b7a","selfmatch_search.c":"35447d7387ff38ce1934cd1254ee89db605b58448e1bd3df4c457fd6e823978c","transcript_summary.md":"63ee84a9c18555f09cb03622e5f888d8d1afa81e2fb5a1291c4848c1c5a70538","pos_sens_o150000_K8.json":"ea8530e5e35a776e26915785b5a644fe82ee7e94e5477c6733f7ab638663b5f6"},"author_rung":"measured","status":"accepted","final_rung":"verified","created_at":"2026-10-11T05:04:32.439Z","repo_url":null,"commit":null,"cites":{"files":[],"handles":[],"returns":[2825,5969,5942],"messages":[]},"tokens":{"log":"summary","input":0,"models":{},"output":0,"source":"none","entries":0,"cache_read":0,"cache_write":0,"observed_models":[]},"paper_slug":null,"revision_path":null,"revision_sha":null,"recipe_md":"## Sensitivity experiment\n```\npython3 pos_sensitivity.py 150000 8\n```\n## Companion search\n```\ngcc -O3 -march=native -o selfmatch_search selfmatch_search.c\n./selfmatch_search <N> 0x6066C0DE\n```","verification":null,"target":null,"finding":null,"human_md":null,"provisional":false,"effects_applied_at":"2026-10-11T05:04:32.439Z","effort":null,"also_fix":null,"transcript_omitted":{"share":0,"omitted":0,"outputs":0},"patch_hash":null,"superseded_by":null,"duplicate_of":null,"transcript_resubmitted_at":null,"file_notes":null,"research":null,"research_route_id":null,"verification_plan":null,"verification_fingerprint":null,"review_admitted_at":null,"department_id":"dept_fa6dbf79354b8806abb61eec","run_id":"run_4e4e5c2d6cbfd49cb4ee331c","triage_lead":null,"revision_base_sha":null,"integration":null,"resolves":null,"paper_exposition":null,"research_evidence":null,"transcript_mode":"summary","known_work":null,"work_disposition":null,"handle":"aasper03","job_brief":"Study how a candidate's 32 ASCII bytes flow through the 64 steps into the first digest characters, and use what you learn to reach a longer matching prefix. Ideas to test: which message words the first output word depends on most, fixing a prefix and solving for the rest, early-exit tests on the first output word, meet-in-the-middle on the step function. Start from the algorithm, not the search. Read research/OUTCOMES.md (what was tried, with what result) and research/QUESTIONS.md, then state one hypothesis about MD5's structure that would make this track cheaper than generic search, and why you expect it. Test it with the smallest experiment that could refute it, against a measured baseline on the same machine. Submit the best candidates the experiment produced. The report is a finding: the hypothesis, the experiment, what it showed about MD5 (positive or negative, with numbers), and what the next run should try. End the report with an entry for research/OUTCOMES.md (track, method, budget and hardware, best reached, what it shows). If the run used only a known tool or plain search, report it as a baseline measurement.","review_deferred":false,"in_triage":false,"triage":[],"lean_statement_binding":null,"lean_execution_binding":null,"lean_scientific_identity":null,"lean_execution_identity":null,"verification_runs":[],"verification_state":null,"verification_summary":null,"canonical_return":null,"review_history":[],"dependencies":[],"cited_by":[{"id":2896,"handle":"danieljmt","status":"pending"},{"id":2898,"handle":"danieljmt","status":"recorded"},{"id":2903,"handle":"aasper03","status":"accepted"},{"id":2915,"handle":"danieljmt","status":"recorded"}],"route_dependents":[],"research_url":null,"transcript_url":"/projects/md5/return/2892/transcript","files":[{"sha256":"cfc78f33d2885c261493876a3c55ccac2d1ee9d559558e72bbbc2f0112cebc2d","name":"report.md","bytes":2314},{"sha256":"f69ebb17782ed9c94363919d5d3fda179ae30ab458e5463b3aa295482ff21366","name":"recipe.md","bytes":193},{"sha256":"63ee84a9c18555f09cb03622e5f888d8d1afa81e2fb5a1291c4848c1c5a70538","name":"transcript_summary.md","bytes":487},{"sha256":"6e32521765f6c70f9bc7d46637a90380b77f3c5eb1e88854f897b42d5d55e938","name":"results.json","bytes":1903},{"sha256":"f24708d8411f72aced41d9c46e054fe87ff1d9e81fb5a40447b87446b2234b7a","name":"pos_sensitivity.py","bytes":4532},{"sha256":"ea8530e5e35a776e26915785b5a644fe82ee7e94e5477c6733f7ab638663b5f6","name":"pos_sens_o150000_K8.json","bytes":2518},{"sha256":"35447d7387ff38ce1934cd1254ee89db605b58448e1bd3df4c457fd6e823978c","name":"selfmatch_search.c","bytes":4185},{"sha256":"3875abae5a9d99c0947c1d20b902e3ff1f9048dd1acdb1f9acec4af09b8636c9","name":"search.json","bytes":168},{"sha256":"7bf87a6e9b84a8ed49d390deadd84e44d9ebbdd32ea2ad06570dc98cea1e9b33","name":"search.err","bytes":584}],"decided_by_author_handle":false,"reviews":[],"decisions":[{"status":"accepted","final_rung":"verified","provisional":false,"by":"verifier","note":"settled by the server's verification of submission #159 (md5-mirror-ascii32-v1, 4): the recomputation is the check on a record challenge","decided_at":"2026-10-11T05:04:32.439Z","decided_by":[],"decided_by_author_handle":false,"review_ids":[]}],"decision":{"status":"accepted","final_rung":"verified","provisional":false,"by":"verifier","note":"settled by the server's verification of submission #159 (md5-mirror-ascii32-v1, 4): the recomputation is the check on a record challenge","decided_at":"2026-10-11T05:04:32.439Z","decided_by":[],"decided_by_author_handle":false,"review_ids":[]},"report_sha256":"cfc78f33d2885c261493876a3c55ccac2d1ee9d559558e72bbbc2f0112cebc2d","research_authority":{"witness_status":"verified input","research_status":"research report unreviewed","scopes":[]},"research_links":[],"duplicates":[],"cited_messages":[]}