{"ready":true,"credit":"Taylor (gtmcknight), amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","submission":false,"authorization":"No submission made. Requester must ask the user before any submission.","gates":{"P":"pass"},"P":{"expected":"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","actual":"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","stdout_sha256":"10f187b4b7d36e2d034ac4c74766f4b6670b3f766a2d291c7370050b799dcbf8","returncode":0,"input_digest":"0dabe003f62d413d6cb222acca4586f806e2a3f94b183d02569f04fd010f2d5e","gates_py_sha256":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604","method":"Kit gatep.py verified all pinned Taylor inputs then executed unmodified gates.py; not a cached first-run claim."},"exact_rule":"Fixed QLX5+AGE only. Preserve QLX5 raw integer denominator search (no binade-safe substitution), nc=5 offsets [0,+1,-1,+2,-2], existing cap/order/domain checks, dt<=6, tell/filter/U1/fee guard. On non-arb callbacks qx OR ordinary binding bound: r=c, syn=true, rt=t&0x1fffffff. Otherwise only if c!=r: age=t-rt; alpha_wad=floor(7e17*age/(age+1)); if alpha_wad>0 then r=exp(ln(r)+trunc(alpha_wad*(ln(c)-ln(r))/1e18)); syn=true even when alpha=0. If c==r do nothing. Initial rt=0. Arb leaves rt/offset unchanged. Offset m independent signed int256 in slot 6. Slot 2 fb[0:63], fa[64:127], timestamp[128:191], cnt[192:223], rt[224:252], kind[253:254], syn[255].","source_sha256":"c25a999646859d187f9a03655b4c7b3009a41b9cb20b4a7b56a19d612242ebc4","code_zb64":"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","reference_encoding":"base64(zlib(UTF8 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Gate P uses its distinct pinned 4812a638 originals enumerated above.","tables":[{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/solved/calib_out_2048.json","sha256":"fdf24c7aa2b604d770336a5783276da8ed4d50bca9dbcc02e98b4da58f608d26"},{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/solved/pol_mid.json","sha256":"efbb5ee102db4d312f64565d9bf7232b6becbe02b624164f744a402bbbf2983b"},{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/solved/qm_k1e-5.json","sha256":"5ff53e42ca87390e5f65d1caa3f7a480e67a8212fb0670274dfd562b05ba1afd"}]},"artifact_field_encodings":"*_zb64 are base64(zlib(UTF8)); bundle.data is base64(tar.xz). fields specify exact input fields, decoded SHA256, member names where needed."},"preservation":{"TellMath_byte_identical_to_QLX5":true,"TellMath_sha256":"406cc6caa93112162a88f1fee3487e87907831916429041e15fef5d3978996bc","U1_blob_identical":true,"state_slots":[0,1,2,3,4,5,6]},"smoke":{"status":"pass","seeds":[64000,64001,64002,64003],"callbacks_per_seed":2000,"callbacks":8000,"exact_fee_wad_equality":true,"method":"Contract drives Taylor replica2; same WAD callback integers passed separately to fresh contract and independent Python integer reference. Each retains its own fees, reserves, offset, belief and rt. EVM state reads only diagnostics, never inputs to reference. Actual U1 blob decoded independently without qm tables.","rows":[{"seed":64000,"callbacks":2000,"max_fee_error_bps":[0.0,0.0],"fee_errors_over_001_bps":0,"arb_mismatches":0,"offset_mismatches":0,"rt_mismatches":0,"kind_mismatches":0,"max_relative_rival_diff":0.0,"peak_tx_gas_pyrevm":175103,"kinds":{"1":1136,"0":718,"2":146},"split_hits":1124,"examples":[],"trace_sha256":"50c285dfbc1ddaf5af2e1eb84860f9328846f7fc49b92b968dedb6ef7e90dfd9"},{"seed":64001,"callbacks":2000,"max_fee_error_bps":[0.0,0.0],"fee_errors_over_001_bps":0,"arb_mismatches":0,"offset_mismatches":0,"rt_mismatches":0,"kind_mismatches":0,"max_relative_rival_diff":0.0,"peak_tx_gas_pyrevm":171589,"kinds":{"1":1212,"0":662,"2":126},"split_hits":1194,"examples":[],"trace_sha256":"78c5646d6a78e01ca3180ac7908fbc532ee72377d77c88b0784b0f93663ae145"},{"seed":64002,"callbacks":2000,"max_fee_error_bps":[0.0,0.0],"fee_errors_over_001_bps":0,"arb_mismatches":0,"offset_mismatches":0,"rt_mismatches":0,"kind_mismatches":0,"max_relative_rival_diff":0.0,"peak_tx_gas_pyrevm":166343,"kinds":{"1":1227,"0":648,"2":125},"split_hits":1217,"examples":[],"trace_sha256":"cb2b3380acf97b20fc410b3eda22a91061437284c104cc411cf106de5f9be607"},{"seed":64003,"callbacks":2000,"max_fee_error_bps":[0.0,0.0],"fee_errors_over_001_bps":0,"arb_mismatches":0,"offset_mismatches":0,"rt_mismatches":0,"kind_mismatches":0,"max_relative_rival_diff":0.0,"peak_tx_gas_pyrevm":167679,"kinds":{"1":1162,"2":146,"0":692},"split_hits":1140,"examples":[],"trace_sha256":"0bdebb8c321956acb14ae7b554a5d8133941551108976adb0ed54de04645cddb"}],"seconds":2.0240213659999426,"scope":"Smoke only, not Q/T/F/G/E. No native engine seeds. Repaired floating-fee roundoff by integer-WAD transcription and negative-axis interval bug before freeze; no candidate tuning."},"freeze":{"after_smoke":true,"candidate_count":1,"source_sha256":"c25a999646859d187f9a03655b4c7b3009a41b9cb20b4a7b56a19d612242ebc4","reference_sha256":"77cd3ebd1c7813ff7368ea22a4581bc4aafb96b15ed757c5bd41d3acb546c232","changes_after_freeze":"No policy changes; AST packaging and unused-code removal verified by restored replay."},"replay_commands":["python3 -B - <<'PY2'\nimport json,zlib,base64,pathlib,hashlib\nd=json.load(open('artifacts/goal/batches/e06-stack-build/items/stack/result.json'));p=pathlib.Path('test/scratch/replay');p.mkdir(parents=True,exist_ok=True)\ns=zlib.decompress(base64.b64decode(d['code_zb64']));assert hashlib.sha256(s).hexdigest()==d['source_sha256'];(p/'Strategy.sol').write_bytes(s)\nb=zlib.decompress(base64.b64decode(d['reference_zb64']));assert hashlib.sha256(b).hexdigest()==d['reference_sha256']\nfor n,t in json.loads(b).items():\n assert pathlib.Path(n).name==n\n assert hashlib.sha256(t.encode()).hexdigest()==d['reference_file_sha256'][n]\n (p/n).write_text(t)\nPY2",". test/scratch/runtime/env.sh && timeout 465 python3 -B test/scratch/replay/compile.py",". test/scratch/runtime/env.sh && timeout 465 python3 -B test/scratch/replay/smoke.py 64000 4 2000 test/scratch/replay/smoke.json","python3 -B test/scratch/replay/replica_runner.py --start 64000 --count 1 --steps 25 --out test/scratch/replay/runner-check.json",". test/scratch/runtime/env.sh && python3 -B test/scratch/kit/reference/materialize.py --out test/scratch/originals",". test/scratch/runtime/env.sh && timeout 465 python3 -B test/scratch/kit/gatep.py --reference test/scratch/originals/taylor --cache test/scratch/cache/gatep"],"replica_runner_check":{"seed":64000,"steps":25,"edge":0.39998291100618644,"resume":"same invocation repeated, existing row skipped","full_seed_benchmark":false},"restoration":{"status":"pass","files":15,"compile_creation_and_runtime_identical":true,"replayed_callbacks":8000,"trace_hashes_identical":true,"chunk_runner_and_resume":"pass; seed64000,25 steps"},"not_done":["Q unrun: no 1024-seed selection/2048-seed paired LB4/QT1 report, ranking or improvement claim.","T unrun: no 50 full-seed label gate; smoke checks arb/state on four seeds.","F unrun: 4x2000 smoke is not 50x2000 gate F.","G unrun: no engine peak/OOG measurements. pyrevm gas is not engine gas; only size/compiler observed.","E unrun: no native engine seeds used or submission made.","Reference transcribes contract WAD approximations; no independent Gaussian modeling equivalence proof.","Pinned installer binaries/wheels and large P originals are external prerequisites, not embedded. Stdlib replica/U1 sources are embedded."],"source_quote_check":{"urls":20,"all_refetched_and_found":true}}