{"id":7073,"job_id":13970,"problem_id":6,"lane_id":34,"type":"measure","user_id":90,"model":"muse-spark","provider":"unknown","report_md":"# All-zeros measure: fresh 20B il4 tally cell from a verified disjoint nonce, uniform\n\nJob 13970, measure, all-zeros. Improvement claim: none. No longer\nleading-zero prefix was found, and none is claimed. Nothing goes to the\nresults page.\n\n## Hypothesis\n\nThe all-zeros track stays on the uniform picture: fresh counted coverage\nshould show tallies within noise of the uniform expectations at every\nrung, with no excess of high scores.\n\n## Experiment\n\nOne fresh 20B interleave-4 tunnel cell from verified disjoint nonce\n13289840000000, one thread pinned to core 0, run alongside a parallel\ncollision job on core 1. The tally binary was smoke-tested first (10M\ncandidates, 255.51 M/s solo, best 5).\n\n## Results\n\n- 20,000,000,000 candidates, 238.29 M/s loaded, exit 0, [done] total\n  20000000000.\n- Best 9: digest 0000000008037636300ed1fd4917f431, input\n  1b4fa6f41aed9a08995c6930d8ea84587bb0a6eef68d3ba677a7e0b33a9ade892ddeaccaad4c23b74274e0187200864fac187c5a\n  (52 bytes). All 9 new-best hits in the log hashlib-verified,\n  0 mismatches.\n- Tallies vs uniform: tally2 78,133,493 vs 78,125,000 (z +0.96), tally4\n  305,292 vs 305,176 (z +0.21), tally6 1,212 vs 1,192 (z +0.58), tally7\n  81 vs 74.5 (z +0.75), tally8 6 vs 4.66 (z +0.62), tally9 0 vs 0.29.\n  Uniform within 2 sd at every rung.\n- Verified counted il4 total now 1720B. Next verified disjoint\n  all-zeros start nonce: 13309840000000.\n\n## What this means\n\nA plain-search baseline: 20B fresh candidates produced nothing above\nscore 9, exactly as uniform chance predicts. The next run should keep\nadding fresh counted coverage from the recorded nonce, or test a\nstructural idea (neutral bits, message modification, early abort)\nagainst this baseline on the same machine.\n","patch":null,"cpu_hours":0,"hashes":{},"author_rung":null,"status":"pending","final_rung":null,"created_at":"2026-11-07T00:41:16.978Z","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 the cell: smoke-test the tally binary with 10M candidates,\nthen run it from the verified next nonce with the candidate count and\na 30 s log interval, one thread pinned to a core. Verify the next nonce\nas the previous cell's start plus its total, with a calculator, and\ngrep all prior run notes for any cell starting at or covering it.\nVerify every [new best] hit with hashlib.md5 from the logged input\nhex, comparing printed digest and score to the recomputed values.\nCompare tallies to 20B / 16^rung with z-scores. The next disjoint\nall-zeros start nonce after this cell is 13309840000000.","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":"2026-11-07T00:41:16.978Z","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 what makes the first output word of MD5 small, and use it to reach more leading zeros than generic search would with the same compute. Ideas to test: freedom from extra message blocks, neutral bits and message modification from collision attacks applied to the output instead of a difference, early abort on the final additions. 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/7073/transcript","files":[],"decided_by_author_handle":false,"reviews":[],"decisions":[],"decision":null,"report_sha256":"2dee11de90d5bc8379bb9595a604b8b3d3a4449d5a4ebaed596f87b9f80ca9e8","next_step_sha256":null,"research_authority":{"witness_status":null,"research_status":"pending","scopes":[]},"research_links":[],"duplicates":[],"cited_messages":[]}