{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","item":"retail-law","batch":"r1-oracle-ceilings","round":1,"source":{"qlx5":"https://api.imd.fun/artifacts/1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15","replica":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","score_py":"https://api.imd.fun/artifacts/9ad960e6c7e11509b81f2852f7f34d395425adc226141b0bc828ed6f5f344663","retail_law":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b (decoded config.hpp and core.hpp)","calibrated_fill_law":"https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/real.py"},"finding":"No advance for this QLX5 retail-likelihood hook: exact run retail parameters yield +0.0005688303743349721 paired edge, SE 0.007191058917739013, n=128; upper two-SE 0.014950948209812999 is below 0.08. This excludes the tested parameter substitution at the prescribed screen, not all possible policies using retail-law information.","gain_vs_base":0.0005688303743349721,"se":0.007191058917739013,"n":128,"seeds":{"choose":{"start":64000,"end_inclusive":65023,"n":1024,"used":"all three candidate mappings and oracle-off controls"},"report":{"start":10000,"end_inclusive":10127,"n":128,"planned_end_inclusive":12047,"unused":"10128..12047; early-stop, no further report evaluation"}},"source_sha256":"c72de3145ffb1d049dc254397533c72efe8ceb01bbf82c1c0a44f3535c7babcc","base_source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","advance":false,"stop":{"reason":"mean + 2*se < 0.08 at the first report checkpoint; mandatory early stop","bar":0.08,"upper_2se":0.014950948209812999,"lower_2se":-0.013813287461143055,"planned_checkpoints":[128,256,512,1024,2048],"stopped_at":128,"report_tuning":false},"history":[{"mean":0.0005688303743349721,"se":0.007191058917739013,"n":128,"bar":0.08,"upper_2se":0.014950948209812999,"early_stop":true,"seed_start":10000,"seed_end_inclusive":10127}],"info":{"true_distribution":"N_t ~ Poisson(lambda); full order quote-notional S ~ LogNormal(mu, tau), mu=ln(M)-tau^2/2. M uniform [19,21), lambda uniform [0.6,1), tau=1.2 fixed. Sides are independently equiprobable but no realized side is supplied. These ranges and draws come from decoded replica config.hpp/core.hpp.","exposed_fields":["lambda (orders per simulation step)","mu (natural-log quote-notional full-order location)","tau (full-order log standard deviation; 1.2 in every run)"],"not_exposed":["fair price","run volatility","seed","realized arrival count","realized full-order size","order index","arb/retail label","rival reserves","router split","next-trade side or size"],"timing":"Only inside successful own-pool execute, after reserves and fee balances are updated and immediately before the existing pol.trade callback. Not at initialization, on rival callbacks, on empty steps, or before a trade is priced. Fields are run constants; no future realization is supplied.","consumption":"At every own callback, overwrite only k.retail_rho, k.retail_logmean, k.retail_logsd. Existing update() consumes them only on the first own callback at a timestamp with t > tlast. Silent updates, tell, posterior thresholds, rival tracker, table selection/interpolation, all table bytes and all remaining constants are fixed.","units":{"edge":"quote-token Y edge accumulated over a complete 10,000-step run, same replica scoring as unchanged QLX5; no relative normalization","gain":"mean over complete paired runs of candidate edge minus base edge","se":"sample SD of paired run differences (ddof=1) / sqrt(n)","likelihood_parameters":"WAD=1e18; natural-log absolute spot move; likelihood weight dimensionless"},"mapping_reason":"Taylor explicitly fitted rho=.26 and ln(median)=ln(11.12e-4), log-sd=1.176 to the FIRST OWN FILL. Those are not the raw Poisson rate and raw full-order lognormal parameters. Preserve this calibrated router/selection correction at the midpoint, then transport it with the exact run law.","selected_mapping":{"mode":1,"rho":"0.26 * lambda/0.8","fill_logmean":"-6.801595083153746944 + (mu - (ln(20)-0.5*1.2^2))","fill_logsd":"1.176 * tau/1.2","fixed_point":"Exact base WAD constants plus I(delta_mu*1e18); positive ratios converted by from_double then mul, preserving the replica integer arithmetic. Since tau is always 1.2, fill_logsd stays exactly unchanged."}},"controls":{"pass":true,"oracle_off":{"choose_runs":1024,"report_runs":128,"equal_fields":["seed","edge (17-digit round-trip string)","tries","hits","callbacks"],"mismatches":0},"callback_trace_checks":{"n":8,"all_equal":true,"columns":["seed","callbacks","sha256_exact_trace"],"rows":[[64000,9542,"1c54b822a1af9daba4f2dbdfa6bafad767e6701406a3c4defec93899dcc940ee"],[64001,9365,"9ffc4cf589221af247bb0c6b6a1b16c5cba48f47ef61607ad216d598a24cdd72"],[64002,12647,"e801fc7a53266ab4001964954ac414c5681dbaf9f895636ca1c416bc60f6fb3b"],[64003,10803,"b51a961b22c842732d1d0c56e57a74f4c7fbe3b589c9deb12488fd2df0ee4893"],[64004,10227,"d65884854e68f3e562180ed86db82437f7d6f1600fbb6b33bbe98cccce8ca4b0"],[64005,11363,"b7fc181c9b7ce31b834f766cd9e1b34f91746ccaf3355f7900626d986c48512a"],[64006,9274,"ed80c9b79ecb09fd4be3f4f739883f095d69e6760fdd6b90618860d9ca134e37"],[64007,11984,"a0dbae7bb816b90f4d84ad63e11ebdbb6d45aa770d23df066b0f9dfeab4d5fdc"]]},"midpoint_control":{"seed":64000,"mean":20,"rate":0.8,"logsd":1.2,"all_four_traces_equal":true,"sha256":"a9e2aad7646f62b4844ec0c20f1f698539f9aabea3a1bb585e75be00407a31bd"},"law_exposure_count":"Exactly one law exposure per own callback for every off/choose/report run; driver assertions passed.","exogenous_stream_audit":{"n":8,"all_three_arms_equal":true,"steps_per_seed":10000,"scope":"All DEBUG_CORE MARKET and ORDER rows: exact binary64 fair prices, generated quote-notional sizes, and sides in order. SPLIT rows intentionally excluded because fees change routing.","columns":["seed","generated_orders","sha256_MARKET_ORDER_stream"],"rows":[[64000,6592,"4412369f9dff6f446fcf1708086f2ef18de4537e96db12450dff4626bfafbad0"],[64001,6538,"0fe0534c33794bc149b8abe0633ae2a26a2b3999f7b1bce617ae13390a6451cf"],[64002,9897,"d05535602038310ac620d00ae4cfff8f3365dc72665f17fed75051e56e8fe364"],[64003,7842,"ba397d838e73849307ec2a6b63f64cfcf2d8bc025c34ceeaa10a1f109e61eba4"],[64004,7224,"66dbbef4d219eee6420d1538bca8bbeb9e1b02daebe5137e7d57a28a12af5622"],[64005,8421,"8faba426a38c0f61c75d5d30749e4a276c877d441a2cc657f4943b1931372fba"],[64006,6579,"06d7bede5974450a0f80d9ac23f0100fa09b9c9a8e73e51ccd6d0c16c7e7ef3d"],[64007,8969,"c51b19148d2c830f7aef758c5ef246c9f179a7edfad0abd6c7746a4410a20d64"]]},"event_order_and_rng":"Only a constant-law assignment and callback-side observer were added to core.hpp; no existing pricing, routing, arbitrage, Poisson, normal, RNG, price-update, execute, or edge arithmetic was edited. DEBUG_CORE exogenous stream equality independently checked on eight choose seeds.","callback_opportunities":"Hook adds no callbacks. Candidate fees can naturally change routed fills and hence subsequent callback counts; those counts are not artificially forced to baseline.","rival_and_scoring":"Unmodified second Pool (30 bps both sides), split(), arb(), execute() arithmetic, edge accumulators and 10,000-step loop. Rival state may diverge endogenously with routing.","qpl":{"decoded_from_base_bytes_equal_replica":true,"bytes":10160,"stored_nodes":9172,"sha256":"830868f9b3e5ad162c4f2070e6faed0782c7b4cc308ab69044b2cf7306f68099","roundtrip_qpl_codec":true},"upstream_parity":{"source":"https://api.imd.fun/artifacts/a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","claimed_n":512,"reference_precision_decimals":6,"claimed_qlx5_max_abs_error":4.994752202946984e-07,"retested_here":false,"reason":"No engine runs or other seed banks allowed; reused the hash-verified engine-faithful source and ran local off controls."},"engine_builds":0,"engine_runs":0,"solidity_generated_or_compiled":0,"submissions":0,"realisable_estimators":0},"ceiling_kind":"Restricted QLX5 sensitivity under perfect run retail-law parameters, with three fixed law-to-first-own-fill transfer maps. Not a solved full-information optimum or universal information upper bound.","limitations":["The exact raw size law is supplied, but the induced first-own-fill displacement distribution also depends on policy quotes, routing, conditioning and pool depth. The existing fitted lognormal is transported, not replaced with a newly solved routing likelihood. Therefore truth exposure is exact while this use of it is approximate.","No fee-table regeneration or law-conditioned policy optimization: task requires all tables and other logic/constants fixed. Potential gains through such changes are not bounded by this experiment.","Three prespecified mappings were compared on choose seeds only. The chosen mapping was frozen before report; other mappings were not evaluated on report.","A mean +/- 2 SE screen is the requested normal-approximation rule, not a rigorous confidence sequence or proof of a universal bound. 128 report seeds do not resolve the sign of this tiny mean.","The supplied replica has published rounded engine parity. No fresh engine validation was performed here. Only assigned parameter truth was exposed.","Leaderboard-gap attribution is unproven; this is a different sample."],"search":{"kind":"Three fixed, midpoint-preserving rate-to-own-fill mappings, each using the same true lognormal-location and shape transport; no scalar optimization, no table edits, no settled oracle repeated.","arms_per_batch":5,"arms":["unchanged QLX5","oracle off","mode 1 linear rate","mode 2 Poisson nonempty probability","mode 3 thinned Poisson nonempty probability"],"mappings":{"1":"rho=.26*(lambda/.8)","2":"rho=.26*(1-exp(-lambda))/(1-exp(-.8))","3":"q=-ln(1-2*.26)/.8; rho=.26*(1-exp(-q*lambda))/(1-exp(-q*.8))"},"choose_stats":{"1":{"mean":-0.0003031485516887811,"se":0.0026857511817320345,"n":1024,"lower_2se":-0.00567465091515285,"upper_2se":0.005068353811775288},"2":{"mean":-0.005180573467073235,"se":0.0025780206818401545,"n":1024,"lower_2se":-0.010336614830753543,"upper_2se":-2.4532103392926018e-05},"3":{"mean":-0.0041392587592513075,"se":0.0024946363944060787,"n":1024,"lower_2se":-0.009128531548063465,"upper_2se":0.0008500140295608499}},"selected_mode":1,"selection_rule":"maximum paired mean, tie lowest mode; no adjustable scalar fitted","freeze_sha256":"18c0df7246dd66916694e2a3f3b0b119865ae90d2ef1abd3edd29cccad14d260","freeze_before_any_report":true},"hashes":{"artifact_raw_sha256":{"base":"1ef80bfb6d6791b877b1f4048a5e63cf2ae54153e6e8763ae3f8ab13132dfb15","replica":"a1eef2f3dbbcbc7a1de9d15a2b22d1d25ac6d316a72efde67275b5d5a16ab16b","core":"2ad2abf45223c729557e83e77d22de54c5db7da2be0599658144906b91dbf0f7","fast":"72b58a1407966f0223f06ab7c6ddd979a24fb4593f1a9b3dc43508a7f133d00b","harness":"9ad960e6c7e11509b81f2852f7f34d395425adc226141b0bc828ed6f5f344663","probes":"6c23d23d4a21a37a502bf47a69d9f87b4c7ac84f614f2097e2488c6d5e6dd164","probe2":"9d06411b9d249e074a426b33b08474edac375f300111ace5bb34928f853531e6","build_fast":"8d5400696659b56bc12eeffc34dec5e58c5c119ddddaca681792db59586dd760"},"artifact_ids_verified":true,"replica_sorted_archive_members_sha256":"802962e861d3a922087e897dae86d43b5d36a7e9253b69547086c943da8f7007","harness_implementation_decoded_sha256":"4d4894474104eac9148e52b18d679b994ce73c6a889bafa18169c8dacca22855","harness_dependency_decoded_sha256":"a992fd6855d568b6fbb163423e9dd6ea7c4709b7475d343079c667edeceb9c00","source_bundle_decoded_sha256":"35378a0ea5e4d4e700aec315bfa353ad9fa5aff56949443d2f95bd6a8dbbc75c","source_members_sha256":{"README.txt":"229de585fcd11dcc0dc44f982f93cb73ebe5d6913af1867787de387f729aeca2","build.py":"470966d01ec17319454ef74a73b17e4a99748b36ee2ef2623062d2eef534be27","check_exogenous.py":"d65cea6732388ff1f926a8174feeeb463710584dd4547ef2699d9a9eb3ed3993","experiment.py":"4133d7ead5839166e784f02ecf44b68f59cd4adcc33cbac98d858276499c4ce5","harness/implementation/score.py":"38856d193fa9f8e8a7ca0e43b62778f5d9f7b8a6bc7bf67168843ca1e03c6958","probe.patch":"880ca6021d836f15fa4d2be21363fab6015554e0cd94955ab7c083e21dc08be2","probe/control.cpp":"be23f1a444acd4f5421389e86a613392dcd8928521b8dbf677330c35ebbb7266","probe/core.hpp":"83937b3d19f6ba2628f7e1c12fd2d9a692b23797df4ab4300692e26e9407f22b","probe/policy.hpp":"c72de3145ffb1d049dc254397533c72efe8ceb01bbf82c1c0a44f3535c7babcc","probe/runner.cpp":"978605c97645fa5f5a8b4362e124430cfcbd3d8893ca42ec82913ce616b07810","replica/LICENSES.txt":"838a5b6e542079eaee0a149bfc3775a42a893d6c0d66398f1457affba80172ca","replica/config.hpp":"969308f5c7df99f51ce38806e5f7ae269313618676fefb3efcda112f801a2a47","replica/core.hpp":"28536398dfd70db1b5513ef64c08954a66315844ca003e1d7dbae8ecff1e7e90","replica/distr_exp.hpp":"51d047769faba33168424f5c2f809818f9fd457546129106169128253ce9442c","replica/knobs.hpp":"f038123598839f1d0077d1366f71582dba24e7b2ba2e45ac3c0c5a5677831f4e","replica/main.cpp":"ac162df4c275b93e1cf9fb968852b84eb8916a4814063303a997e4494106636c","replica/math.hpp":"b485e5f23ade82faeed4ebf816be125fc709e4b9f31341ea7da26531703ff2d6","replica/policy.hpp":"c987d597ab85c62fb3714954a414d41a341eb8edc94e0d01cb6a1999e1192a4a","replica/tables.hpp":"12fb00e047d9b9a2f7b399f59c201d895423d10e08e9921a52f08caf2c0e26f6","replica/tell.hpp":"961ee357e91ad8da9a076bfb846afc2b1fb95ca853778cd9574d4c53a0d526bc","replica/uint256.hpp":"1b0ae2990526e14c3895ef77e52ad9bb10f910147a4db9cd09b6dd6709c90647","replica/zig.hpp":"8532a00cc599c056f51e42fc15b015d502f7f93d5c9eecfec8a835441df56130"},"csv_sha256":{"report/base.csv":"3dc705313ba34ce3c5c445418fb1d0cb1bd632c4993d5cdef64ed847f7ba09f7","report/off.csv":"b73676370436bf46c8344c0d51e15a5589b92347dcb6f9a4f00341cabdc4e82f","report/probe.csv":"b9954803a1a9b4cd4d3866b4b267e085d8e12106c606dccbaf5960361e43f0bf"},"probe_patch_sha256":"d51cc5f689f2a7c8f076201d83a0f06f7b90c13d2bd2e79168aa645cbb402531","paired_rows_decoded_sha256":"af4b814fce04a91b2aae27a69c80bb00c9f9af761be0d13314dda1bfdf70adbd"},"hash_scope":{"source_sha256":"Exact UTF-8 probe/policy.hpp bytes, including the oracle observer and unchanged policy. Companion core hook, runner, all headers and build/analysis scripts individually hashed in source_members_sha256. Mode 1 is the measured report policy.","base_source_sha256":"Exact decoded bytes of base.code_zb64.QLX5; no contract compiler was invoked.","artifacts":"SHA256 of exact HTTP response body bytes equals full URL artifact ID, for all eight named/followed artifacts.","source_bundle":"SHA256 of decompressed UTF-8 JSON mapping relative filenames to exact source texts.","replica_archive_members":"Original archive only, sorted by filename; concatenate UTF-8 filename + NUL + file bytes + NUL.","executable":"Source hashes, not cross-machine binary identity, define reproducibility."},"reproduce":{"encoding":"base64(zlib(UTF-8 JSON mapping relative paths to source 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","patch_unified_diff":"Included as probe.patch in source_zb64; patch -p1 applied inside a copy of replica/. Full probe source is also included.","commands":["python3 - <<'PYEXTRACT'\nimport pathlib,json,zlib,base64\nr=json.load(open('artifacts/goal/batches/r1-oracle-ceilings/items/retail-law/result.json'))\np=pathlib.Path('test/scratch/retail-law-reproduce')\nfor name,text in json.loads(zlib.decompress(base64.b64decode(r['reproduce']['source_zb64']))).items():\n q=pathlib.PurePosixPath(name)\n assert not q.is_absolute() and '..' not in q.parts\n f=p/q;f.parent.mkdir(parents=True,exist_ok=True);f.write_text(text)\nPYEXTRACT","cd test/scratch/retail-law-reproduce","python3 build.py","python3 experiment.py choose","./probe/control controls","python3 check_exogenous.py","python3 experiment.py report","python3 harness/implementation/score.py --base report/base.csv --candidate report/probe.csv --bar 0.08"],"requires":{"platform":["linux-x64"],"minCpus":8,"build":"g++ compatible C++20 compiler, flags -O3 -std=c++20 -ffp-contract=off; measured with GCC 14.2.0","runtime":"glibc, C++ standard library, Python 3 standard library. No third-party Python/runtime packages. All application source dependencies embedded. Compiler is a build-tool prerequisite; compiler cache is not an application dependency."}},"paired_rows":{"encoding":"base64(zlib(binary records)); each record struct.pack(\"<Iddd\", seed, base_edge, probe_edge, delta), little endian uint32 + three IEEE754 float64, 28 bytes per record; ascending seed","columns":["seed","base_edge","probe_edge","delta"],"n":128,"data_zb64":"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","oracle_off":"Equal to base for all report rows; not duplicated in payload."},"timing":{"choose_seconds":48.82134938240051,"report_seconds":3.224106788635254,"workers":8,"complete_steps_per_run":10000,"wall_seconds_to_pack":432.5520746707916},"unknowns":{"universal_retail_information_upper_bound":null,"reason":"Not identified by a fixed QLX5 likelihood substitution. A different use of the information may have a different ceiling."},"requires":{"platform":["linux-x64"],"minCpus":8},"local_validation":{"json_and_size":true,"source_quotes_refetched":10,"paired_statistics_recomputed":true,"embedded_source_rebuilt":true,"rebuild_output_checks":4}}
