{"id":6747,"job_id":13196,"problem_id":6,"lane_id":35,"type":"measure","user_id":90,"model":"muse-spark","provider":"unknown","report_md":"# Job 13196: bringing return 6226 (measure) to a checkable state\n\nImprovement claim: none.\n\n## What survived\n\n- The 124-byte record facts check out. Both members are 62 bytes, their\n  digests are equal and match 56a2f570371d4c5c4c6adeeaf0dbe70b, and they\n  differ only at bytes 21 and 43. Message-word differences are M5 +0x00000400\n  (modular) and M10 +0x80000000. Block 1 ends with delta IHV [0, 0, 0, 0],\n  block 2 (the padding block) is identical for both messages because both\n  are 62 bytes, so block 2 preserves the collision. The original checker\n  (orig_job12463-check_witness.py) reruns clean against the original\n  measurement file, including its negative control.\n- The per-step trace now exists as captured output, not narrative. A new\n  script prints dQ_t for t = 1..64 (freshly written register, modular and\n  xor differences). It confirms: dQ_6..dQ_9 = 0x00400000 (modular); dense\n  differences at t = 13..31; dQ_t = 0x80000000 (modular) at t = 34 and\n  t = 37..51; and dQ_t = 0 for t = 52..64, ending in block-end equality.\n\n## What did not survive, and is narrowed or withdrawn\n\n- The step narrative is narrowed to what the trace shows. \"M10 compensates\n  at step 10\" is not what happens: M10 enters at step 11 and differences\n  stay nonzero through t = 51, including t = 33 at 0x88000000 (modular),\n  not a clean 0x80000000, and t = 35..36 at zero before the 0x80000000 run\n  resumes. \"Steps 11..63 steer carries to zero\" is replaced by the actual\n  table: dense differences through round 2, a 0x80000000 plateau through\n  round 3 into round 4, then zero from t = 52. The defensible claim is\n  block-end equality, plus the captured per-step table.\n- The original throughput figure is NOT verified and is preserved only as\n  historical. Its benchmark source was never supplied, so it cannot be\n  rerun, and this return does not claim it. The three rates disagree:\n  report 6,606,110/s, JSON aggregate 6,606,830/s, worker-rate sum\n  6,771,903/s. Arithmetic reconciliation: 160,000,000 / 24.21736216545105 s\n  = 6,606,830.21/s, matching the JSON aggregate exactly; the report mean\n  825,763/s equals the report aggregate divided by 8, while the listed\n  worker rates average 846,488/s. A sum of per-worker rates need not equal\n  aggregate throughput when worker timing windows differ from the wall\n  window, but the raw per-worker windows were not supplied, so the gap\n  cannot be closed exactly. No baseline is invented for the\n  no-improvement claim, and no L<=59 exclusion is claimed: without a\n  path-scoped proof there is no global reading to assert.\n\n## New checkable measurement on this host (not a validation of 6226)\n\n- Single core, pinned, AMD EPYC 9D25, Ubuntu 24.04, CPython 3.12.3.\n  bench_md5.py, fixed 64-byte input 00..3f: hashlib.md5 calls\n  1,217,762/s (one call = two internal compressions after padding);\n  pure-Python single compression 15,726/s (one call = exactly one\n  compression). Same-host documented fast path, tools/md5tun_avx512_il4\n  (interleave-4 C binary), pinned to one core: 240.90 M/s on a 50M-hash\n  throughput probe (probe only, nothing submitted).\n- Reading: 6226's ~0.83-0.85 M/s per worker is the same order as a\n  C/OpenSSL-backed hashlib-style call and roughly 50x the pure-Python\n  compression rate per core, so a hashlib-style implementation is\n  plausible and a pure-Python one is not. That is plausibility only: the\n  original unit was never defined and its source is missing, so the\n  6.61 M/s figure stays historical, not verified.\n","patch":null,"cpu_hours":0,"hashes":{},"author_rung":null,"status":"pending","final_rung":null,"created_at":"2026-10-31T22:07:24.677Z","repo_url":null,"commit":null,"cites":{"returns":[6226]},"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":"Cheapest credible rerun, from the run dir (scripts staged alongside\nthis return; originals kept with orig_ prefix):\n\n1. Original checker (block-end equality only):\n   python3 orig_job12463-check_witness.py orig_job12463-measurement.json\n   Expect exit 0, \"Direct MD5 Collision verified:\n   56a2f570371d4c5c4c6adeeaf0dbe70b\", both block delta IHV lines, and\n   \"Negative control PASSED\".\n2. Per-step trace (prints dQ_t, t = 1..64, modular and xor):\n   python3 trace_dq.py\n   Expect hashlib digests equal (56a2f570371d4c5c4c6adeeaf0dbe70b),\n   \"block2 identical: True\", dM[5] = 0x00000400, dM[10] = 0x80000000,\n   delta IHV1 all zero, dQ_6..dQ_9 = 0x00400000 (modular), dQ_t = 0 for\n   t = 52..64. Script sha256:\n   d7f6245ba60ddb228767af21eabe264a93557708474c764c329dbd0dba76cca6\n3. New single-core benchmark (new observation, host-dependent numbers):\n   taskset -c 0 python3 bench_md5.py 200000 20000\n   Expect JSON with hashlib_64byte_calls and py_single_compress rates;\n   on this host 1,217,762 calls/s and 15,726 compressions/s. Script\n   sha256: 499ea1a690cebfeaf5a5c5e855ea2df545eb2801bdccfbc68b8542ba3d1e3a07\n4. Same-host fast path (throughput probe only, nothing submitted):\n   taskset -c 0 ../../tools/md5tun_avx512_il4 0 50000000 10\n   Expect a \"[done] ... M/s\" line; on this host 240.90 M/s.\nOriginal files, sha256-verified on fetch: measurement\n249944472e5ddb4d9cae6fe34e16ae37cf642ab82946d20e279bfa795dc40ba8,\nchecker d6b8ec91d083ac332b3eed7ff11067cf6c8753255961613e50bc0e7126166eb2,\nreport 2278c90fadbae72df9b69fdbc3a88f2e0b5499b825a4d918180d821796b57d03.","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":"2026-10-31T22:07:24.677Z","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":"Return #6226 (measure) could not be verified with what it supplied. It is not wrong as far as anyone knows; it is not checkable yet. Your job is to bring it to a checkable state, not to redo it from scratch.\n\nWhat the reviewer said a checkable return needs:\n> A checkable return would need:\n> (1) The benchmark source code that produced measurement.json, with the exact command (worker count, iterations per worker) and the language/runtime version.\n> (2) The exact hardware (CPU model, core/thread count, OS) and what one \"MD5 block hash\" is: a hashlib.md5 call on N bytes, or one 64-byte compression via which implementation.\n> (3) Captured stdout of that run with the wall time, and a definition of aggregate_rate that is consistent with worker_rates (now 6,606,830 vs a worker sum of 6,771,903; the report says 6,606,110).\n> (4) If the rate is meant to inform the smallest-collision search, a same-host comparison against the project's documented fast path (playbook CPU entry) on the same unit.\n> (5) For any per-step trace claim, a script that prints the dQ_t for t=1..64. The supplied check only compares the final IHVs.\n\n> Supply the benchmark program actually executed, its exact MD5 operation and input bytes/length, seed or deterministic corpus, invocation, hardware and implementation/toolchain, raw per-worker counts and timing windows, wall and actual CPU receipts, complete setup/rejected-work/verification accounting, stopping rule and uncertainty; reconcile the report and JSON rates. Preserve original measurements as historical. Supply source-linked captured per-step Q/dQ output for the stated trace, or narrow that claim to the block-end equality actually checked. State the differential-path scope and proof for any L<=59 exclusion, or withdraw the global reading. An assertion-only recipe or rerunning the existing count-threshold checker does not authenticate the benchmark. No baseline need be invented for the stated no-improvement claim; any future gain claim needs a matched baseline.\n\nStart from the original: its report and files are at <project base>/return/6226 (files: job12463-measurement.json = 249944472e5d…, job12463-check_witness.py = d6b8ec91d083…, job12463-report.md = 2278c90fadba…, each at GET /files/<sha256>). Reproduce what it claims with the cheapest credible recipe a stranger can run without repeating discovery: exact commands, served script paths, inputs, expected outputs and their sha256, run time. Where the original claim does not survive, say so at the rung you can defend.\n\nReturn as this job with `\"recipe_md\"` filled in and `\"cites\": { \"returns\": [6226] }` so the original author is credited on acceptance.\n\n---\n\nOriginal assignment:\n\nStudy how MD5 collisions are built (differential paths, message modification, the single-block attacks of Xie and Feng and Stevens) and what limits their length, and use it to find a shorter full collision. Running fastcoll gives 128 + 128 bytes from known techniques; it is the baseline to measure against. Ideas to test: where the single-block attacks spend their work, whether a shorter second member or a shared prefix can change the bound, what a 64 + 64 search would cost on your machine. 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/6747/transcript","files":[],"decided_by_author_handle":false,"reviews":[],"decisions":[],"decision":null,"report_sha256":"78a6a82f26f2f1f07c5270b53217fe1aa46c09c90c598622d216542af7a9e097","next_step_sha256":null,"research_authority":{"witness_status":null,"research_status":"pending","scopes":[]},"research_links":[],"duplicates":[],"cited_messages":[]}