{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","idea":"Isolated staleness-dependent rival pull; six increasing alpha(age) curves, unchanged integer tell, price filter, posterior odds, one-sided router bounds and full QM tables.","setup":{"reference_url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research","reference_commit":"66604b3426d8e97a73e2c39940b9b4dece51cc73","commands":["curl -fsL https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/tell/fetch.sh -o test/scratch/fetch.sh","sh test/scratch/fetch.sh https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research test/scratch/amm","Decode result.base_code_zb64 with base64 then zlib to test/scratch/amm/stalerival.py; decode result.code_zb64 to test/scratch/amm/agealpha.py.","Decode result.reproduction_zb64 to a JSON mapping; write its files relative to test/scratch/.","curl -fsL https://raw.githubusercontent.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/45e7563d1a29ffca9d608fdf60c90bf2624d2d01/score.py -o test/scratch/score.py","PROCS=8 timeout 470 python3 -I test/scratch/amm/run.py stalerival:Policy 64900 8 test/scratch/timing.json soft=1 qm=qm_k1e-5.json a0=0.35 ainf=0.35","PROCS=8 timeout 470 python3 -I test/scratch/amm/diagnostic.py","PROCS=8 timeout 470 python3 -I test/scratch/amm/garble_selected.py","PROCS=8 timeout 470 python3 -I test/scratch/amm/gates.py","For start=64000,64064,64128,64192, separately: PROCS=8 timeout 470 python3 -I test/scratch/amm/experiment.py choose <start> 64","For start=10000,10064,...,11984, separately: PROCS=8 timeout 470 python3 -I test/scratch/amm/experiment.py report <start> 64"],"baseline_sha256":"176f8115fb67d99340f1de1e6994042dfaa41f830c22e000595df3377cc6a2b3","fetch_check":{"files":34,"mismatched":0},"dependencies":"Python standard library only; no installation or native dependency","timing_8_seeds_seconds_rounded":2,"workers":8,"score_url":"https://raw.githubusercontent.com/identity-md-launches/goal-3178-build-shared-evaluation-kit/45e7563d1a29ffca9d608fdf60c90bf2624d2d01/score.py"},"rule":{"state_kept":"BASE state plus configuration enabled/later in subclass; BASE already keeps router_t (last binding timestamp, initially 0) and router_age. No new observations.","per_callback":"Convert amounts/reserves to int(float(v)*1e18) exactly as BASE, reconstruct floats, save old rival estimate and fees, then execute TellPolicy. On a retail callback form cand=s*(1-old_bid_fee)/0.997 for isBuy, else s*0.997/(1-old_ask_fee). For binding detection, prior is old rival estimate clipped into [exp(m)*0.997, exp(m)/0.997] on the first callback of a new timestamp. Binding is cand<prior on buy or cand>prior on sell. Only binding updates router_t=t; age=max(0,t-router_t). If the nonbinding candidate is against the current one-sided estimate (log(cand/s2h)>0 on buy, <0 on sell), use alpha=a0+(ainf-a0)*age/(age+tau); replace s2h=exp(log(s2h)+alpha*log(cand/s2h)), synced=True, redo the existing lookup for phase 1 if cnt<=1 else 2. Round fees exactly as BASE. Arb callbacks have no pull. Band clipping and soft pulls never reset the binding timestamp.","later_callbacks":"pick uses its chosen alpha(age) on every eligible callback, including later callbacks at the same timestamp; any binding callback resets age for subsequent callbacks. pick_own_later explicitly has its own later-callback alpha=0.35, while first callbacks use the chosen curve. Later means self.first is false (t-last_timestamp<1), including t=0.","arithmetic":"Python float for filter and curve; integer/WAD observation and tell path identical to BASE. No Solidity fixed-point equivalence claimed."},"frozen":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","name":"rise_faster","params":{"a0":0,"ainf":0.7,"tau":1},"code_sha256":"768f699130ff58e103f641669d8a6721dc6a33ede0be49078a890be2e8398d13","params_sha256":"2468cf53608c6997ba147c1b780e739f296bf7c88889dc7d59b53044e36d96f6","base_code_sha256":"176f8115fb67d99340f1de1e6994042dfaa41f830c22e000595df3377cc6a2b3","frozen_utc":"2026-11-10T15:24:10.775688+00:00","report_read_before_freeze":false,"later_callback_alpha":{"pick":"same chosen alpha(age)","pick_own_later":0.35},"selection":"highest paired mean on 64000..64255 among surviving six predeclared settings"},"choose":{"seeds":[64000,64255],"n":256,"settings_declared_before_scoring":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","settings":{"rise_fast":{"a0":0,"ainf":0.7,"tau":2},"rise_faster":{"a0":0,"ainf":0.7,"tau":1},"rise_slow":{"a0":0,"ainf":0.7,"tau":4},"rise_high":{"a0":0,"ainf":0.9,"tau":2},"rise_floor":{"a0":0.15,"ainf":0.7,"tau":2},"rise_low":{"a0":0,"ainf":0.5,"tau":2}},"choose_seeds":[64000,64255],"block_size":64,"drop":"mean_diff + 3 se < 0","pick":"highest surviving mean_diff","report_later_arm":"same chosen a0/ainf/tau, later callbacks constant 0.35 (own alpha); pick uses age curve for every callback","recorded_before_scoring":true},"settings_sha256":"da3220210a379f4e5fb704720554b574be7d70b105b731bb2f9fd564635e2e40","table":[{"name":"rise_fast","params":{"a0":0,"ainf":0.7,"tau":2},"n":256,"mean_diff":0.01625952222851379,"se":0.009998701427118251,"worst5":[{"seed":64143,"diff":-0.5068147437883681},{"seed":64240,"diff":-0.44288395751340204},{"seed":64076,"diff":-0.4113084717012043},{"seed":64003,"diff":-0.3603463218513525},{"seed":64008,"diff":-0.3382705605083629}],"min":-0.5068147437883681,"dropped":false},{"name":"rise_faster","params":{"a0":0,"ainf":0.7,"tau":1},"n":256,"mean_diff":0.025401064376998406,"se":0.010946522020542786,"worst5":[{"seed":64240,"diff":-0.4310732412622542},{"seed":64114,"diff":-0.37980866566829263},{"seed":64247,"diff":-0.3501767745117377},{"seed":64143,"diff":-0.34449545891186517},{"seed":64242,"diff":-0.3257543948394641}],"min":-0.4310732412622542,"dropped":false},{"name":"rise_slow","params":{"a0":0,"ainf":0.7,"tau":4},"n":256,"mean_diff":0.013906960113851952,"se":0.010794966010190955,"worst5":[{"seed":64005,"diff":-0.5098210600833681},{"seed":64140,"diff":-0.4316110116270693},{"seed":64222,"diff":-0.40847880434199624},{"seed":64240,"diff":-0.4076172883476943},{"seed":64008,"diff":-0.4011600655884422}],"min":-0.5098210600833681,"dropped":false},{"name":"rise_high","params":{"a0":0,"ainf":0.9,"tau":2},"n":256,"mean_diff":0.01921033243127912,"se":0.011976229100727903,"worst5":[{"seed":64095,"diff":-1.011994184746527},{"seed":64240,"diff":-0.479604600074822},{"seed":64242,"diff":-0.4708614533836908},{"seed":64085,"diff":-0.4380038992635491},{"seed":64149,"diff":-0.4229059342203527}],"min":-1.011994184746527,"dropped":false},{"name":"rise_floor","params":{"a0":0.15,"ainf":0.7,"tau":2},"n":256,"mean_diff":0.015222459662184162,"se":0.009708661270662174,"worst5":[{"seed":64081,"diff":-0.4595273914392237},{"seed":64058,"diff":-0.4329495959917722},{"seed":64245,"diff":-0.3867818108243455},{"seed":64240,"diff":-0.3686818854206422},{"seed":64149,"diff":-0.34299088561857616}],"min":-0.4595273914392237,"dropped":false},{"name":"rise_low","params":{"a0":0,"ainf":0.5,"tau":2},"n":256,"mean_diff":0.002935298768773187,"se":0.009978162023729895,"worst5":[{"seed":64240,"diff":-0.4121698689099844},{"seed":64098,"diff":-0.4047107234107443},{"seed":64140,"diff":-0.3974222968410004},{"seed":64075,"diff":-0.3759482514079764},{"seed":64145,"diff":-0.3548803065298216}],"min":-0.4121698689099844,"dropped":false}],"rule":"highest cumulative paired mean among surviving settings after 256 seeds; BASE constant 0.35; stop a setting when mean_diff+3*se<0 using kit score.summarize at 64-seed block boundaries"},"report":{"seeds":[10000,12047],"n":2048,"order":"ascending contiguous 64-seed blocks; within each block BASE, pick, pick_own_later; parameters/code frozen before first report seed","baseline":"stalerival:Policy a0=0.35 ainf=0.35 soft=1 qm=qm_k1e-5.json","base_mean_edge":536.6208103550729,"arms":[{"name":"pick","minus_base":{"n":2048,"mean_diff":0.01970998860079745,"se":0.004066268023068066,"worst5":[{"seed":11701,"diff":-2.20673035101629},{"seed":10300,"diff":-0.8106354842481096},{"seed":11695,"diff":-0.7617335071444131},{"seed":10233,"diff":-0.7387874313023417},{"seed":10879,"diff":-0.7218744944398168}],"min":-2.20673035101629},"mean_edge":536.6405203436738,"params":{"a0":0,"ainf":0.7,"tau":1}},{"name":"pick_own_later","minus_base":{"n":2048,"mean_diff":0.01110666894129339,"se":0.0025910204951536515,"worst5":[{"seed":10879,"diff":-0.7687795446546488},{"seed":11643,"diff":-0.6680529075794084},{"seed":10233,"diff":-0.6127746309708186},{"seed":11630,"diff":-0.6072010954979987},{"seed":10209,"diff":-0.5172482690318247}],"min":-0.7687795446546488},"mean_edge":536.6319170240142,"params":{"a0":0,"ainf":0.7,"tau":1,"later":0.35}}],"blocks":[{"start":10000,"n":64,"seconds":20.063745737075806},{"start":10064,"n":64,"seconds":22.580102920532227},{"start":10128,"n":64,"seconds":19.68916344642639},{"start":10192,"n":64,"seconds":19.742453575134277},{"start":10256,"n":64,"seconds":20.964239597320557},{"start":10320,"n":64,"seconds":21.39070463180542},{"start":10384,"n":64,"seconds":20.1377272605896},{"start":10448,"n":64,"seconds":20.650676250457764},{"start":10512,"n":64,"seconds":19.61847186088562},{"start":10576,"n":64,"seconds":19.738251209259033},{"start":10640,"n":64,"seconds":19.054653882980347},{"start":10704,"n":64,"seconds":19.43695306777954},{"start":10768,"n":64,"seconds":19.7199125289917},{"start":10832,"n":64,"seconds":20.09966230392456},{"start":10896,"n":64,"seconds":19.826751708984375},{"start":10960,"n":64,"seconds":20.211988925933838},{"start":11024,"n":64,"seconds":22.152748107910156},{"start":11088,"n":64,"seconds":21.765308380126953},{"start":11152,"n":64,"seconds":20.857239961624146},{"start":11216,"n":64,"seconds":23.07499885559082},{"start":11280,"n":64,"seconds":23.070307731628418},{"start":11344,"n":64,"seconds":21.64229702949524},{"start":11408,"n":64,"seconds":24.30919337272644},{"start":11472,"n":64,"seconds":22.788191318511963},{"start":11536,"n":64,"seconds":20.158398151397705},{"start":11600,"n":64,"seconds":19.31299138069153},{"start":11664,"n":64,"seconds":18.671765089035034},{"start":11728,"n":64,"seconds":19.39896583557129},{"start":11792,"n":64,"seconds":18.81775712966919},{"start":11856,"n":64,"seconds":18.84194326400757},{"start":11920,"n":64,"seconds":18.86934208869934},{"start":11984,"n":64,"seconds":18.622956037521362}],"statistic":"sample standard deviation of per-seed edge differences divided by sqrt(n); min and worst5 are seed-level differences"},"cost":{"extra_storage_words":0,"relative_to":"supplied stalerival.py BASE, which already stores last-binding timestamp and age","contract_port_increment_vs_hardcoded_constant":{"extra_storage_words":1,"meaning":"last-binding timestamp; age can be derived, parameters constants; excludes state already used by tell/filter"},"worst_ops_per_callback":{"optimized_curve_vs_optimized_constant_upper_bound":{"subtractions":1,"additions":2,"multiplications":1,"divisions":1,"comparisons":0,"logs":0,"exps":0,"loops":0,"table_lookups":0},"separate_later_arm_extra":{"comparisons":2,"branches":1}},"qualification":"Source-level scalar arithmetic upper bound for an optimized curve versus hardcoded constant, not measured EVM gas. The supplied BASE already evaluates the age formula, so the literal subclass adds only feature-flag and later-alpha branches, no additional curve arithmetic. Python reference redundantly performs BASE lookup before replacement, exactly as supplied."},"diagnostics":{"chosen_curve_parity":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","seeds":[64900,64907],"all_rows_exact":true,"params":{"a0":0,"ainf":0.7,"tau":1}},"P":{"passed":true,"observed_stdout":"seed   perfect-info      gaussian+plain    gaussian+qm       lattice+qm\n10000  448.261189  443.455598  443.522608  443.663520\n10001  576.779199  571.463409  571.623551  571.977293\n10002  531.886497  525.168028  525.865859  526.411631\n","comparison":"All twelve printed values equal pinned solved README."},"parity_and_garbling":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","parity_seeds":[64900,64907],"all_rows_exact":true,"garbled_seeds":[64900,64907],"garbled_callbacks":86543,"identical_fees":true,"seconds":6.397453784942627},"reads_hidden_input":false,"observable_signature":["side","amount_x","amount_y","timestamp","reserve_x","reserve_y"],"hidden_boundary":"run.Blind discards arb, p, s2, j and init sigma/lam/size before invoking Policy; counterfactual shadow receives altered hidden values but identical public callbacks. Fees compared exactly. Metrics may inspect true price outside policy.","later_arm_garbling":{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","seeds":[64900,64907],"arms":{"pick":{"callbacks":86595,"identical_fees":true,"changed":["sigma","lambda","size","arb","true_price","rival_spot","order_index"]},"pick_own_later":{"callbacks":86572,"identical_fees":true,"changed":["sigma","lambda","size","arb","true_price","rival_spot","order_index"]}}},"repairs":["Initial isolated diagnostic import failed because -I omitted its directory; added explicit local sys.path and reran 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","rows_format":"[[seed,pick_minus_base],...] 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Solidity implementation, T/F/G contract gates, gas benchmark, engine evaluation, board claim or submission; this item is Python-only.","No qt1/lb-4 contract comparison: requested experiment compares replica BASE on exactly paired report seeds."],"failed":null}