{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved; replica/filter/policy/tables. Research snapshot 66604b3426d8e97a73e2c39940b9b4dece51cc73. LEANBASE and QLITE from the credited IdentityMD artifacts named in sources.json.","question":"Does carrying inferred rival reserves between detected splits beat LEANBASE or QLITE on Taylor's Python replica?","conclusion":"No for the tested carry rule and widths. The best live setting is not advanced.","arms":[{"name":"LEANBASE","definition":"Unchanged leanbase:Policy from the supplied artifact.","parameters":{"soft":1,"qm":"qm_k1e-5.json","a0":0.35,"ainf":0.35,"variant":"A"}},{"name":"QLITE","definition":"Unchanged published cap24+GATE winner: qlgate:Policy over LEANBASE; exact split candidate on hits, bound plus 0.35 pull on misses.","parameters":{"soft":1,"qm":"qm_k1e-5.json","a0":0.35,"ainf":0.35,"q":1,"pull":1,"cap":24,"order":"b","gate":6}},{"name":"CARRY-0","definition":"CARRY rule in carry_definition; width=0","parameters":{"width":0,"soft":1,"qm":"qm_k1e-5.json","cap":24,"order":"b","gate":6,"pull":0},"report_selected":false},{"name":"CARRY-1","definition":"CARRY rule in carry_definition; width=1","parameters":{"width":1,"soft":1,"qm":"qm_k1e-5.json","cap":24,"order":"b","gate":6,"pull":0},"report_selected":false},{"name":"CARRY-2","definition":"CARRY rule in carry_definition; width=2","parameters":{"width":2,"soft":1,"qm":"qm_k1e-5.json","cap":24,"order":"b","gate":6,"pull":0},"report_selected":true},{"name":"ORACLE-R","definition":"LEANBASE price belief and tell, but each lookup uses the true current post-event rival spot supplied by an oracle-only wrapper, with synced=true. No true price, true arb flag or model parameters are supplied to the policy; rival bound/pull disabled.","parameters":{"soft":1,"qm":"qm_k1e-5.json","a0":0,"ainf":0,"synced":true}}],"choose":{"seeds":[64000,64255],"n":256,"selection":"highest paired mean against QLITE on all 256 choose seeds; tie goes to lower width","results":{"LEANBASE":{"against_LEANBASE":{"mean_diff":0.0,"se":0.0,"n":256},"against_QLITE":{"mean_diff":-0.031226264681749827,"se":0.01003380310795843,"n":256}},"QLITE":{"against_LEANBASE":{"mean_diff":0.031226264681749827,"se":0.01003380310795843,"n":256},"against_QLITE":{"mean_diff":0.0,"se":0.0,"n":256}},"CARRY-0":{"against_LEANBASE":{"mean_diff":-1.4309950206569868,"se":0.043281892184090405,"n":256},"against_QLITE":{"mean_diff":-1.4622212853387366,"se":0.043657773638172,"n":256}},"CARRY-1":{"against_LEANBASE":{"mean_diff":-1.391645116384907,"se":0.04587211458175956,"n":256},"against_QLITE":{"mean_diff":-1.422871381066657,"se":0.04613306632822557,"n":256}},"CARRY-2":{"against_LEANBASE":{"mean_diff":-1.354015827336381,"se":0.0451774375755342,"n":256},"against_QLITE":{"mean_diff":-1.3852420920181308,"se":0.04531202674592624,"n":256}},"ORACLE-R":{"against_LEANBASE":{"mean_diff":0.1272228920125884,"se":0.020265169933024598,"n":256},"against_QLITE":{"mean_diff":0.09599662733083858,"se":0.016897692926648427,"n":256}}},"frozen_before_report":true,"screen":{"CARRY-0":{"status":{"reason":"worse","n":128,"available":128},"rounds":[{"n":128,"mean_diff":-1.4551168258985756,"se":0.05746181000141575,"worst5":[{"seed":64044,"diff":-3.483245207600362},{"seed":64043,"diff":-3.202740607798546},{"seed":64034,"diff":-2.6745963997418585},{"seed":64058,"diff":-2.634505604275205},{"seed":64112,"diff":-2.6123138726894695}]}]},"CARRY-1":{"status":{"reason":"worse","n":128,"available":128},"rounds":[{"n":128,"mean_diff":-1.4753055314608479,"se":0.06494050472569914,"worst5":[{"seed":64124,"diff":-3.1148640601149964},{"seed":64031,"diff":-3.098283039442549},{"seed":64052,"diff":-2.8875866989408223},{"seed":64070,"diff":-2.875368826133979},{"seed":64051,"diff":-2.832572942832712}]}]},"CARRY-2":{"status":{"reason":"worse","n":128,"available":128},"rounds":[{"n":128,"mean_diff":-1.3731113989198058,"se":0.059442026505395366,"worst5":[{"seed":64074,"diff":-3.1016368361924833},{"seed":64005,"diff":-3.04785553140141},{"seed":64070,"diff":-2.5515975790572156},{"seed":64043,"diff":-2.5483581707503618},{"seed":64083,"diff":-2.521618108504299}]}]}},"screen_note":"Shared score.py returned worse for all widths at 128 seeds. Already launched fixed selection blocks were completed to satisfy the specified 256-seed choice; no additional settings or contract work followed."},"report":{"LEANBASE":{"against_LEANBASE":{"mean_diff":0.0,"se":0.0,"n":1024},"against_QLITE":{"mean_diff":-0.03777940540015512,"se":0.004890203753792384,"n":1024}},"QLITE":{"against_LEANBASE":{"mean_diff":0.03777940540015512,"se":0.004890203753792384,"n":1024},"against_QLITE":{"mean_diff":0.0,"se":0.0,"n":1024}},"CARRY-2":{"against_LEANBASE":{"mean_diff":-1.3835710067615916,"se":0.023020285829357865,"n":1024},"against_QLITE":{"mean_diff":-1.4213504121617468,"se":0.02300051465154155,"n":1024}},"ORACLE-R":{"against_LEANBASE":{"mean_diff":0.14321572096371615,"se":0.009519073155560588,"n":1024},"against_QLITE":{"mean_diff":0.10543631556356103,"se":0.008394035953880422,"n":1024}}},"report_protocol":{"seeds":[10000,11023],"n":1024,"metric":"replica edge per seed; each policy separately against the 30 bps rival","pairing":"same seed, independent policy state; differences computed before averaging","se":"sample standard deviation of per-seed differences divided by sqrt(n)","report_runs_per_arm_per_seed":1,"model_selection_from_report":false,"blocks":[{"seed0":10000,"n":64},{"seed0":10064,"n":64},{"seed0":10128,"n":64},{"seed0":10192,"n":64},{"seed0":10256,"n":64},{"seed0":10320,"n":64},{"seed0":10384,"n":64},{"seed0":10448,"n":64},{"seed0":10512,"n":64},{"seed0":10576,"n":64},{"seed0":10640,"n":64},{"seed0":10704,"n":64},{"seed0":10768,"n":64},{"seed0":10832,"n":64},{"seed0":10896,"n":64},{"seed0":10960,"n":64}]},"best_live":"CARRY-2","ceiling":{"arm":"ORACLE-R","against_LEANBASE":{"mean_diff":0.14321572096371615,"se":0.009519073155560588,"n":1024},"against_QLITE":{"mean_diff":0.10543631556356103,"se":0.008394035953880422,"n":1024},"interpretation":"Measured true-rival-spot comparator, not a proven global upper bound."},"advance":false,"advance_test":{"required_mean_diff":0.02,"observed_mean_diff":-1.4213504121617468,"se":0.02300051465154155,"mean_minus_2se":-1.4673514414648299},"cost":{"storage_words":{"semantic_rival_state":1,"synced_flag":1,"incremental_minimal_port_vs_QLITE":0,"additional_between_callback_information_in_reference":"one carried spot and one boolean, separate from inherited s2h/synced; diagnostics excluded"},"arithmetic_a_callback":{"carry_band":"1 sqrt, 2 exp, 2 multiplies, 1 division, 1 subtraction, 1 addition, min/max comparisons; 1 log plus subtraction/multiplication for lookup coordinate. Width is a constant. Common filtering/table/tell work excluded.","split_test":"unchanged q-lite cap24: at most 24 counted binary64 operations on eligible callbacks; hit update adds own spot division, fee conversion/division, subtraction, multiply/divide. This is an algorithm count, not gas.","reserves":"The invariant lets spot encode both reserves, so no reserve square root is required during the policy callback."},"solidity_gas":null,"static_algorithm_estimate_only":true},"checks":{"fetched_manifest_files":34,"manifest_mismatches":0,"baseline_hashes_match_artifacts":true,"all_report_blocks_match_frozen_hashes":true,"q0_equals_leanbase":true,"audit_does_not_change_carry_edges":true,"one_lookup_per_callback":true,"diagnostic_callbacks":86677,"split_hit_audit":{"CARRY-0":{"seeds":[64000,64007],"hits":44264,"mismatches_gt_1e_minus9_log":19,"mismatches_gt_point1_bps":6,"max_error_bps":10.94675417129987,"true_arbitrage_among_mismatches":0},"QLITE":{"seeds":[64000,64007],"hits":45499,"mismatches_gt_1e_minus9_log":26,"mismatches_gt_point1_bps":7,"max_error_bps":14.386472716441851,"true_arbitrage_among_mismatches":0}},"split_hit_note":"The prior artifact's zero-false-hit observation is not assumed universal. These are measured post-hit spot discrepancies on new policy trajectories, not a Solidity test. The unchanged QLITE baseline also has rare discrepancies; source was not changed to suppress them.","split_discrepancy_causes":{"CARRY-0":{"hit_discrepancies":19,"rival_zero":6,"rival_positive_below_execution_threshold":13,"rival_above_execution_threshold":0},"QLITE":{"hit_discrepancies":26,"rival_zero":7,"rival_positive_below_execution_threshold":19,"rival_above_execution_threshold":0}},"diagnostic_replica_annotations_preserve_all_16_edges":true,"split_discrepancy_interpretation":"All audited discrepancies occurred when the rival allocated fill was zero or positive but <=1e-4 (the replica skips those fills). No discrepancy in these audited seeds had rival allocated fill >1e-4. This is measured evidence, not a universal false-positive bound.","source_quotes_verified":13,"packed_replay":{"seed":64000,"exact_edge_matches":4,"arms":4},"rounded_per_seed_statistics_rechecked":true},"reference_encoding":"base64(zlib(UTF-8 JSON name:text map)). Includes arms, runner, original dependency modules, diagnostic runners and frozen.json. Taylor attribution is in this result and bundled CREDIT.txt.","reference_zb64":"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","reference_zb64_sha256":"993e4fa0a8ed55b6ef785e25bf020e52c78c3a537463f7ac9c2ad5864208fa83","dependency_tables":{"pol_mid.json":{"sha256":"efbb5ee102db4d312f64565d9bf7232b6becbe02b624164f744a402bbbf2983b","url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/solved/pol_mid.json"},"qm_k1e-5.json":{"sha256":"5ff53e42ca87390e5f65d1caa3f7a480e67a8212fb0670274dfd562b05ba1afd","url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/solved/qm_k1e-5.json"}},"reproduction":{"runtime":"Python 3 standard library; no installed dependencies","materialization":"Decode reference_zb64 beside the two pinned upstream table JSON files. The tables are unchanged fetched data, excluded from this size-limited result, as in LEANBASE.","report_command":"PROCS=4 timeout 470 python3 -I carry_run.py report SEED0 64 OUT.json LEANBASE QLITE CARRY-2 ORACLE-R","report_seed0":[10000,10064,10128,10192,10256,10320,10384,10448,10512,10576,10640,10704,10768,10832,10896,10960],"callback_steps_per_seed":10000,"all_simulation_commands_timeout_seconds":470,"diagnostic_commands":["PROCS=4 timeout 470 python3 -I carry_run.py choose 64000 8 ../smoke.json","timeout 470 python3 -I carry_check.py","timeout 470 python3 -I 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","report_differences_encoding":{"format":"base64(zlib(JSON rows))","seed0":10000,"seed_step":1,"columns":["QLITE minus LEANBASE","CARRY-2 minus LEANBASE","ORACLE-R minus LEANBASE"],"precision":"6 decimals; max rounding error 0.0000005 per stored difference; summary statistics use original unrounded edges"},"seeds_used":{"choose":[64000,64255],"report":[10000,11023],"smoke_included_in_choose":[64000,64007],"audit_reruns":[64000,64007],"report_reused_for_selection":false,"engine":[]},"not_done":["Python replica only: no Solidity port, engine seeds, gas/size/source-character measurement, leaderboard entry or submission. Contract gates are outside this item.","Only the selected CARRY-2 setting was evaluated on report seeds; CARRY-0 and CARRY-1 were selection-only.","Unknown rival-only retail trades are not observable. Between split hits, carried state is a belief-driven estimate, not the true reserve trajectory.","This tests clipping on every callback as requested, including later callbacks within a step. A step-gated clip, retaining the base bound/pull on misses, and alternative synced rules were not tested; the negative result does not rule them out.","Rare q-lite hit discrepancies mean the recovered reserves are not guaranteed exact on every hit; no classifier repair was attempted.","The two multi-megabyte upstream lookup tables are not embedded in the <=64000-byte result; offline replay needs those exact table files already materialized."],"carry_definition":"Separate carried rival spot initialized to 100, sufficient for reserves x=sqrt(1e6/spot), y=1e6/x. At every own callback, after LEANBASE updates its price belief, clip carried spot to [exp(m-width*sqrt(v))*0.997, exp(m+width*sqrt(v))/0.997]. On a non-arb callback with dt<=6, use the unchanged cap24/order-b q-lite test; a hit resets spot to own_spot*(1-fee)/0.997 for own buys, own_spot*0.997/(1-fee) for own sells. No bound or 0.35 pull modifies the carried state. synced resets on the first callback of a new step, becomes true on a hit, and otherwise persists within the step. The usual table receives this spot and flag. No hidden inputs."}