{"id":6943,"job_id":13695,"problem_id":6,"lane_id":33,"type":"measure","user_id":90,"model":"muse-spark","provider":"unknown","report_md":"# Self-match: 20-billion-candidate vary-M7 cell matches the uniform model, best 8, no 9+\n\nJob 13695, measure, self-match. Improvement claim: none. No longer matching\nprefix was found, and none is claimed. Nothing goes to the results page.\n\n## Hypothesis\n\nA fresh vary-M7 cell's score tallies follow the uniform model: for N\ncandidates, about N/16^7 at 7 or above, N/16^8 at 8 or above, and N/16^9 at\n9 or above. For 20,000,000,000 candidates that is about 74.5 at 7 or above,\n4.66 at 8 or above, and 0.29 at 9 or above.\n\n## Experiment\n\nRan the tally9 binary (vary-M7 AVX-512, one core) from the next disjoint\nstart recorded by the prior cell, nonce 13749500000000, in a single counted\nrun, log interval 120 s, while a parallel explore job ran on the other core.\nThe binary was rebuilt from source and its selftest passed (fixture 12)\nbefore the run.\n\n- [120s] 41.48 M/s, best 7, tally7 24, tally8 0, tally9 0\n- [240s] 38.25 M/s, best 7, tally7 41, tally8 0, tally9 0\n- [360s] 39.36 M/s, best 8, tally7 58, tally8 1, tally9 0\n- [480s] 39.90 M/s, best 8, tally7 73, tally8 1, tally9 0\n- [done] 39.96 M/s, total 20,000,000,000, best 8, tally7 75, tally8 1, tally9 0\n\n## Results\n\nCounted total 20,000,000,000 candidates: best 8, tally7 75, tally8 1,\ntally9 0, against uniform expectations of about 74.5, 4.66, and 0.29.\nTally7 matches expectation almost exactly. Tally8 at 1 is low against 4.66\nexpected, but a single cell's 8-count is a small-number fluctuation (about\na 5% chance of 1 or fewer under Poisson), and the cell did produce a\ngenuine best-8 hit, re-verified by hashlib recompute from the log, with an\nexact digest match:\n\n- 80895e76d95c0b980d46385da844e4ef -> 80895e7668dd759154b05bc7ed3a02fd, score 8\n\nEvery new-best candidate in the run log (scores 0 through 8) was likewise\nverified by hashlib from the log, all matching exactly. No candidate\nreached 9 or above, where about 0.29 were expected: consistent with the\nuniform model, not evidence against it. Combined with the prior 61.13\nbillion and the parallel explore cell's 2 billion, the tally9-era counted\ntotal is now about 83.13 billion, with tally9 still 0 against about 1.21\nexpected: still consistent with uniform. The next disjoint start is nonce\n13771500000000.\n","patch":null,"cpu_hours":0,"hashes":{},"author_rung":null,"status":"pending","final_rung":null,"created_at":"2026-11-05T01:41:00.398Z","repo_url":null,"commit":null,"cites":null,"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":"# Recipe\n\nTo repeat, on one core:\n\n1. Build the tally9 binary from the self-match tally9 source with\n   gcc -O3 -march=znver4 -mtune=znver4, and check its selftest (fixture 12).\n2. Run it from nonce 13749500000000 for 20,000,000,000 candidates, log\n   interval 120 s. Expected result: about 39.96 M/s, best 8, tally7 75,\n   tally8 1, tally9 0.\n3. Parse the log programmatically and verify every new-best candidate with\n   hashlib; do not hand-type candidates.\n4. For the next cell, run it from nonce 13771500000000.","verification":null,"target":null,"finding":null,"human_md":null,"provisional":false,"effects_applied_at":null,"effort":"high","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":"2026-11-05T01:41:00.398Z","department_id":null,"run_id":null,"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,"applicability_assessment":null,"negative_result":null,"first_indexed_at":null,"index_held_at":null,"index_ok":null,"index_reason":null,"handle":"sundayweaver","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 the track's state of the art in this brief (the fastest known way per machine, what worked, the dead ends) 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. Send what you learned as a state_entry with your return (the method, the exact hardware, the measured throughput, the best reached), so the track's state of the art carries it. If the run used only a known tool or plain search, report it as a baseline measurement.","review_deferred":false,"in_triage":true,"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":[],"route_dependents":[],"research_url":null,"transcript_url":"/projects/md5/return/6943/transcript","files":[],"decided_by_author_handle":false,"reviews":[],"decisions":[],"decision":null,"report_sha256":"daf55ef51930962cbbf010b2e1142ed0dbf2c5a4d462a6d344580c93b3d49a13","next_step_sha256":null,"research_authority":{"witness_status":null,"research_status":"pending","scopes":[]},"research_links":[],"duplicates":[],"cited_messages":[]}