{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","item":"run-volatility","batch":"r1-oracle-ceilings","requires":{"platform":["linux-x64"],"minCpus":8,"runtime":"Python 3 standard library, g++ C++20, glibc. No installed dependencies or network needed for reproduction."},"source":{"artifacts":{"base":"https://api.imd.fun/artifacts/1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15","replica":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","core":"https://api.imd.fun/artifacts/2ad2abf45223c729557e83e77d22de54c5db7da2be0599658144906b91dbf0f7","fast":"https://api.imd.fun/artifacts/72b58a1407966f0223f06ab7c6ddd979a24fb4593f1a9b3dc43508a7f133d00b","harness":"https://api.imd.fun/artifacts/9ad960e6c7e11509b81f2852f7f34d395425adc226141b0bc828ed6f5f344663","probes":"https://api.imd.fun/artifacts/6c23d23d4a21a37a502bf47a69d9f87b4c7ac84f614f2097e2488c6d5e6dd164","probe2":"https://api.imd.fun/artifacts/9d06411b9d249e074a426b33b08474edac375f300111ace5bb34928f853531e6","build_fast":"https://api.imd.fun/artifacts/8d5400696659b56bc12eeffc34dec5e58c5c119ddddaca681792db59586dd760"},"measured_implementation":"Supplied C++ replica; isolated core.hpp hook below. Cython and earlier oracle examples inspected, not run.","loci":{"volatility_distribution":{"url":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","decoded_file":"config.hpp","function":"config_for: sigma=.000882+(.001008-.000882)*r.uniform()"},"units_and_order":{"url":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","decoded_file":"core.hpp","function":"Core.run: drift=-0.5*sigma*sigma, vol=sigma*sqrt(1); price then own/rival arb then generated retail orders then routing"},"baseline_use":{"url":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","decoded_file":"policy.hpp","function":"Knobs.process_variance=893025000000; Policy.update adds it to posterior v during silent steps and current step; Policy.fees uses root(v)"},"scoring":{"url":"https://api.imd.fun/artifacts/9ad960e6c7e11509b81f2852f7f34d395425adc226141b0bc828ed6f5f344663","decoded_field":"implementation_zb64 -> score.py","sha256":"38856d193fa9f8e8a7ca0e43b62778f5d9f7b8a6bc7bf67168843ca1e03c6958"},"measured_evidence":"per_seed_deltas; controls.evidence_zb64; reproduction.source_archive includes the exact source, runner and score.py"}},"conclusion":"Volatility truth in QLX5 fails the +0.08 gate at the first report look. This plug-in effect is not a universal bound.","gain_vs_base":0.028547394601922793,"se":0.012706129241827322,"n":128,"metric":"Mean paired difference in complete 10,000-step runs of final own-pool edge (probe minus unchanged QLX5).","statistics":{"sample_sd":0.14375344239246057,"se_definition":"sample SD of paired run deltas (n-1 denominator) / sqrt(n)","base_mean":527.480386131213,"probe_mean":527.5089335258149,"lower_2se":0.003135136118268149,"upper_2se":0.05395965308557744,"source":"Unmodified supplied score.py; exact binary64 paired rows are embedded in per_seed_deltas.report."},"seeds":{"choose":{"actual":[64000,65023],"n":1024,"inclusive":true},"report":{"actual":[10000,10127],"n":128,"planned":[10000,12047],"planned_n":2048,"inclusive":true},"controls":{"oracle_off":[64000,64127],"callback_and_exogenous_trace":[64000,64007]},"no_other_experiment_seeds":true},"source_sha256":"2092df4f2801811a7c17a658ca0a601ae4416b0ffd212fdc40f6333faf9c9310","base_source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","advance":false,"stop":{"early_stop":true,"reason":"At report n=128, mean+2*se=0.05395965308557744 < 0.08. Stopped before 10128; no later report looks evaluated.","prespecified_looks":[128,256,512,1024,2048],"bar":0.08,"history":[{"n":128,"seeds":[10000,10127],"mean":0.028547394601922793,"se":0.012706129241827322,"lower_2se":0.003135136118268149,"upper_2se":0.05395965308557744,"bar":0.08,"early_stop":true,"at":"2026-11-11T14:38:35.432002+00:00","command":"python3 -B score.py --base measurements/report_base.csv --candidate measurements/report_probe.csv --bar 0.08","base_csv_sha256":"4f6ac8c672e94d747b50132e9d8cf9b753183bce762dec44cacf515dbcabb434","probe_csv_sha256":"5cf1b0ecc206ad640a9ff1db9921dd2b0118ecc2fbb60a9acbeb8158bdac4cbd"}],"advance_rule":"Only after all 2048 report seeds, with mean-2*se >= 0.08 and controls passing.","inference_note":"The two-SE values implement the requested sequential screening rule; they are not an anytime-valid confidence sequence."},"info":{"assigned_truth":"The run-level sigma parameter drawn by config_for, and nothing else.","exposure":"Core stores from_double(sigma*sigma); immediately after each successful own fill and before pol.trade, oracle ON writes only pol.k.process_variance. Oracle OFF never writes it.","initialization":"No truth supplied before afterInitialize-equivalent setup. Both initial fees remain 2823606104386589 WAD; posterior v starts at zero. No added callbacks.","consumption":"Existing Policy.update uses the replaced process variance for each silent step up to the unchanged cap of 12 and for the current step. Posterior v is not overwritten. Same-timestamp callbacks and timestamp zero retain the existing update conditions.","isolation":"No current fair price, future price/noise, labels, router truth, retail parameters or next order are passed into policy. Debug market/ORDER traces are observer output only.","fixed":"policy.hpp, tables.hpp, tell.hpp, all other parameters, initialization, rival strategy, scoring, routing arithmetic, RNG streams and callback execution code are unchanged apart from the one variance assignment."},"timing":{"callback":"Post-own-fill, pre-returned-fee application, before subsequent engine events. Rival callbacks do not expose anything.","steps_per_run":10000,"dt":1,"choose_started_utc":"2026-11-11T14:36:01.925137+00:00","frozen_utc":"2026-11-11T14:37:13.123053+00:00","report_started_utc":"2026-11-11T14:38:21.776636+00:00","report_finished_utc":"2026-11-11T14:38:35.432361+00:00","choose_and_controls_wall_seconds":71.19184689898975,"report_wall_seconds":13.655861940002069,"research_started_utc":"2026-11-11T14:31:39+00:00"},"units":{"sigma":"Per-step standard deviation of the log-price innovation, sampled between 0.000882 and 0.001008.","correct_mapping":"Q = sigma^2 * dt, with dt=1. Integer policy input = trunc(binary64(sigma*sigma)*1e18). QLX5 baseline Q=893025000000/1e18=(0.000945)^2.","posterior":"v is conditional uncertainty of log fair price, separate from Q. The fee tables receive sqrt(v)*10000 as before.","rounding":"Uses the existing from_double conversion. Integer truncation loses less than one variance WAD unit (1e-18), in addition to binary64 multiplication rounding.","edge":"Token-Y/quote-value units accumulated by the unchanged replica scoring equations; not bps and not per trade."},"controls":{"pass":true,"oracle_off":{"n":128,"seeds":[64000,64127],"edge_and_all_emitted_state_fields_exact":true,"paired_gain":0.0,"se":0.0,"fields":"edge, tries, hits, callbacks, sigma, variance_wad, exposures, init_bid, init_ask; final policy state and both pools encoded bit-exactly"},"callback_trace":{"n":8,"seeds":[64000,64007],"base_vs_off_byte_identical":true,"callbacks_compared":85205,"fields":"trade direction, WAD amounts, timestamp, post-fill own reserves, returned bid and ask"},"exogenous_trace":{"n":8,"steps_per_run":10000,"base_off_on_byte_identical":true,"market_and_order_records":142062,"fields":"binary64 fair-price path and every retail order side and size in original order","on_callbacks":85228,"interpretation":"Oracle ON may change fills and hence own callback counts through fees. Scheduling and callback eligibility are unmodified; exogenous streams remain identical."},"entry_point_checks":{"original_replica_main_matches_original_runner_n":8,"on_matches_unchanged_replica_per_seed_exact_variance_knob_n":8,"seeds":[64000,64007]},"variance_unit_check":{"sigma":0.000945,"expected_variance_wad":"893025000000","passed":true},"all_choose_and_report_on_runs":{"exposures_equal_own_callbacks":true,"initial_fees_unchanged":true,"finite_edges":true},"unchanged_headers":["config.hpp","distr_exp.hpp","knobs.hpp","math.hpp","policy.hpp","tables.hpp","tell.hpp","uint256.hpp","zig.hpp"],"tables":{"base_blob_equals_replica_blob":true,"bytes":10160,"sha256":"830868f9b3e5ad162c4f2070e6faed0782c7b4cc308ab69044b2cf7306f68099","source_url":"https://api.imd.fun/artifacts/1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15"},"input_verification":{"all_8_fetched_artifact_hashes_equal_url_ids":true,"decoded_base_hash_verified":true,"replica_source_tree_matches_declared_hash":true,"harness_dependency_headers_equal_replica_headers":true,"core_python_source_matches_declared_hash":true},"upstream_parity":{"kind":"Supplied artifact evidence; 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different initial fees, tables or decision rules could exploit information not captured by this slot substitution.","limitations":["Early stopped at 128 report seeds, not a completed 2048-seed estimate. Choose and report estimates differ; no report tuning was performed.","Only the QLX5 process-noise slot receives sigma truth. Perfect sigma is not perfect current fair price or a perfect posterior.","Fixed tables were not reoptimized for sigma, and initial fees and silent-gap cap remain unchanged. This cannot rule out gains under a different volatility-aware fee policy.","Replica parity is inherited from the verified supplied artifacts at printed precision; no new engine runs were permitted.","Full callback/exogenous traces were checked on eight choose seeds; oracle-off final rows/state were checked on 128. Structural hash/diff checks cover the source used for all runs.","This test makes no claim about live leaderboard scores or how gains from other sources combine."],"search":{"candidate_count":1,"candidate":"Exact sigma-squared substitution; no hyperparameter, scalar, fee, table or policy search.","choose_purpose":"Required choose bank used for effect measurement and controls only. 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Credit: Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved.\npython3 -B - <<'PY'\nimport base64,hashlib,json,lzma,pathlib\nr=json.loads(pathlib.Path('artifacts/goal/batches/r1-oracle-ceilings/items/run-volatility/result.json').read_text())\na=r['reproduction']['source_archive'];raw=lzma.decompress(base64.b85decode(a['data']))\nassert hashlib.sha256(raw).hexdigest()==a['decoded_sha256']\ndst=pathlib.Path('test/scratch/run-volatility-reproduce')\nfor n,s in json.loads(raw).items():\n p=pathlib.PurePosixPath(n);assert not p.is_absolute() and '..' not in p.parts\n f=dst/n;f.parent.mkdir(parents=True,exist_ok=True);f.write_text(s)\nPY","python3 -B test/scratch/run-volatility-reproduce/check_result.py artifacts/goal/batches/r1-oracle-ceilings/items/run-volatility/result.json --out test/scratch/run-volatility-reproduce --replay","python3 -B test/scratch/run-volatility-reproduce/study.py choose","python3 -B test/scratch/run-volatility-reproduce/study.py report"],"command_notes":"First two commands verify and replay the recorded report. Last two repeat choose/freeze/report; use a fresh scratch extraction. Offline, replica only, no external packages.","compile_flags":["g++","-O3","-std=c++20","-ffp-contract=off"],"source_archive_credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved"},"per_seed_deltas":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","report":{"encoding":"base64(zlib(little-endian IEEE-754 binary64 records))","struct_format":"