{"item":"sparse-spline-residual","batch":"e01-a-table-recovery","status":"done","method":"One method: a quantized sparse residual added to C0 qm-spline grid-node values. C0 QMS1 decoder is unchanged (qmref.py parse/basis/surfaces verbatim). Corrected ask node F'=max(0,F_spline+r/qd), A=round(w+F',6), B=point mirror of A, so ask/bid mirror, phase/synced tags and the sd axis keep their form. Nodes are chosen by occ^A*e^2, where e=F_full-F_c0 and occ is TellPolicy(C0 tables) lookup weight on 60000..60255, splatted as real.py interpolates and mapped through the mirror for bids. TellPolicy classifier/filter, soft=1 and qm_k1e-5 information weight are unchanged.","inputs_verified":{"C0_artifact_sha256":"8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","C0_Strategy_sol_sha256":"c68887cff61180e12ba2b1ceb333edf76a830f91f63b5d775a8806fb9ec08aca (42,990 bytes, matches)","QMS1_blob":"10,167 bytes, sha256 3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e (matches qm-spline/C0)","fetch":"fetch.sh: 34 files, 0 mismatched","decoded_check":"run.py gauss soft=1 qm=<decoded C0 tables> on seeds 10000..10002 = 443.101741 / 571.454483 / 525.908441, equal to every printed digit of C0 check values","check_py_verify":"11856 vectors, 0 differ from expected; 4661 of 4661 arbitrage read, 9 of 7195 retail read as arbitrage","readme_gate_tellpol":"run.py tellpol:TellPolicy 10000 3 soft=1 qm=qm_k1e-5.json gives 446.798260 / 574.326680 / 529.637987 here, against README 446.752500 / 574.326680 / 529.609154. Seed 10001 matches; 10000 and 10002 differ by 0.046 and 0.029. The README says these can move with libm. A local full-qm TellPolicy run pairs with tell_qm.json at -0.0020 se 0.0012 (n=2048), so drift against the published rows is small."},"frozen_representation":{"format":"SRS1: magic, u8 qd=4 (unit 0.25 bps), u16 n=576, 64 big-endian 32-byte words (PUSH32 immediates); 9 entries of 28 bits per word: key(20b)=((t*8+l)*321+i)*49+j <<8 | int8 r; sorted; padding 0xfffffff","K":576,"qd":4,"A":1,"payload_bytes":2055,"payload_words":64,"srs1_sha256":"805c2bc1ac5f2973ff2485083ab7cedce304a16a0f22d9f3bf62c501f26b6619","decoded_qm_json_sha256":"564f9a8a9db390ed327bd92aef4072ba691e075615ddc1038f9ffec1c127c332","entries_by_level":"levels 0,1,2,3,5 only; 1 entry clipped at int8 bound","determinism":"rebuild from occupancy is byte-identical (cmp); decode of payload equals tune-time decode (cmp)","occupancy_file_sha256":"7c7dcf6982f82e0d295b3cef0a87d989ba498161b95ab0d4cb8c90554f9a4441 (65,376 nodes; regenerated by collect.py, not shipped)"},"holdout_once":{"seeds":"10000..12047","command":"python3 -I run.py tellpol:TellPolicy 10000 2048 out.json soft=1 qm=<decoded candidate>","paired_vs_tell_qm":{"n":2048,"mean_diff":-0.061103,"se":0.005125,"sum":-125.13975,"sumsq":117.765587,"worst5":[[10522,-1.008008],[11821,-0.936868],[10596,-0.914203],[11025,-0.827782],[11511,-0.782915]]},"paired_vs_C0_compressed_TellPolicy_same_machine":{"n":2048,"mean_diff":0.050943,"se":0.004653,"sum":104.331057,"sumsq":96.07915,"worst5":[[11607,-0.792487],[10543,-0.790498],[11981,-0.712822],[10357,-0.702706],[11613,-0.701917]]},"C0_compressed_vs_tell_qm":{"n":2048,"mean_diff":-0.112046,"se":0.006275,"sum":-229.470807,"sumsq":190.75906,"worst5":[[10843,-1.8952],[11025,-1.389354],[11113,-1.126072],[10460,-1.09048],[10322,-1.074865]]},"local_full_vs_tell_qm":{"n":2048,"mean_diff":-0.002024,"se":0.001199,"sum":-4.145598,"sumsq":6.030799,"worst5":[[11413,-0.465065],[11714,-0.398294],[10852,-0.337024],[11528,-0.318679],[11770,-0.30056]]},"cand_vs_local_full":{"n":2048,"mean_diff":-0.059079,"se":0.005131,"sum":-120.994153,"sumsq":117.514207,"worst5":[[10522,-1.026035],[11821,-0.936868],[10596,-0.90869],[11448,-0.818477],[11025,-0.810814]]},"loss_recovered":"C0 loss vs tell_qm 0.1120 to candidate 0.0611: 45% of C0 compression loss recovered on holdout","first_trade_misread_and_price_rms":{"hold_cand":{"first_trades":14353188,"misread":3416,"misread_rate":0.000238,"price_rms_bps":7.1438,"mean_edge":536.471104},"hold_c0":{"first_trades":14364734,"misread":3393,"misread_rate":0.000236,"price_rms_bps":7.1337,"mean_edge":536.420161},"tellqm":{"first_trades":14350251,"misread":3420,"misread_rate":0.000238,"price_rms_bps":7.1494,"mean_edge":536.532208}}},"rows":{"note":"holdout candidate edges, seeds 10000..12047 in order (seed = 10000 + line index), from run.py tellpol:TellPolicy 10000 2048 soft=1 qm=<decoded candidate>; zlib+base64 of a one-column CSV, 6 dp. Per-row first/misread are summed in holdout_once.first_trade_misread_and_price_rms","n":2048,"seed0":10000,"rows_zb64":"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","rows_csv_sha256":"85ec7264a1bfa1ffeba585e00e51e61a013ad6d2c62fc87ce02c48a879dc0d38","mean_edge":536.471104},"tuning_60000_60255":{"improvement_over_C0_compressed_TellPolicy":{"n":256,"mean_diff":0.075806,"se":0.01277,"sum":19.406376,"sumsq":12.116791,"worst5":[[60132,-0.76628],[60213,-0.495623],[60044,-0.490871],[60231,-0.484898],[60034,-0.463587]]},"cand_vs_full":{"n":256,"mean_diff":-0.047111,"se":0.01371,"sum":-12.060416,"sumsq":12.83922,"worst5":[[60182,-0.845665],[60111,-0.808965],[60020,-0.681772],[60122,-0.623303],[60238,-0.546837]]},"C0_vs_full":{"n":256,"mean_diff":-0.122917,"se":0.016396,"sum":-31.466792,"sumsq":21.417689,"worst5":[[60020,-1.142346],[60122,-0.867211],[60210,-0.82389],[60165,-0.778983],[60182,-0.761183]]},"misread_price":{"tune_cand":{"first_trades":1788021,"misread":432,"misread_rate":0.000242,"price_rms_bps":7.1465,"mean_edge":529.648061},"tune_c0":{"first_trades":1789555,"misread":439,"misread_rate":0.000245,"price_rms_bps":7.1374,"mean_edge":529.572255},"tune_full":{"first_trades":1787620,"misread":406,"misread_rate":0.000227,"price_rms_bps":7.1522,"mean_edge":529.695172}},"sweep":[{"cfg":"K128_q8_a1","bytes":519,"vs_c0":0.0292,"se":0.0098,"fee_max_bps":36.404,"visit_rms_bps":0.702,"fmt":"u32 12-bit"},{"cfg":"K256_q8_a1","bytes":1031,"vs_c0":0.0219,"se":0.0108,"fee_max_bps":36.405,"visit_rms_bps":0.639,"fmt":"u32 12-bit"},{"cfg":"K512_q8_a1","bytes":2055,"vs_c0":0.0695,"se":0.0124,"fee_max_bps":36.77,"visit_rms_bps":0.554,"fmt":"u32 12-bit"},{"cfg":"K512_q8_a0.5","bytes":2055,"vs_c0":0.0306,"se":0.0107,"fee_max_bps":26.727,"visit_rms_bps":0.659,"fmt":"u32 12-bit"},{"cfg":"K1024_q8_a1","bytes":4103,"vs_c0":0.0905,"se":0.0134,"fee_max_bps":30.178,"visit_rms_bps":0.451,"fmt":"u32 12-bit"},{"cfg":"K512_q8_a1.5","bytes":2055,"vs_c0":0.0625,"se":0.0122,"fee_max_bps":40.451,"visit_rms_bps":0.599,"fmt":"u32 12-bit"},{"cfg":"K512_q8_a2","bytes":2055,"vs_c0":0.067,"se":0.0118,"fee_max_bps":40.453,"visit_rms_bps":0.654,"fmt":"u32 12-bit"},{"cfg":"K512_q4_a1","bytes":2055,"vs_c0":0.0641,"se":0.0124,"fee_max_bps":36.821,"visit_rms_bps":0.555,"fmt":"u32 12-bit"},{"cfg":"K384_q8_a1","bytes":1543,"vs_c0":0.0491,"se":0.0114,"fee_max_bps":36.771,"visit_rms_bps":0.592,"fmt":"u32 12-bit"},{"cfg":"K768_q8_a1","bytes":3079,"vs_c0":0.0761,"se":0.0131,"fee_max_bps":36.764,"visit_rms_bps":0.494,"fmt":"u32 12-bit"},{"cfg":"K576_q4_a1","bytes":2055,"vs_c0":0.0758,"se":0.0128,"fee_max_bps":36.821,"visit_rms_bps":0.538,"fmt":"28-bit int8"},{"cfg":"K448_q4_a1","bytes":1607,"vs_c0":0.0571,"se":0.0118,"fee_max_bps":36.821,"visit_rms_bps":0.572,"fmt":"28-bit int8"},{"cfg":"K576_q8_a1","bytes":2055,"vs_c0":0.0679,"se":0.0122,"fee_max_bps":36.77,"visit_rms_bps":0.539,"fmt":"28-bit int8"}],"sweep_note":"Each config is one run.py pass on 60000..60255 (se about 0.012), so differences of about 0.02 between configs are noise. Selection is a top-K prefix by score, so a lighter K can be rebuilt with the same generator (K448: 1,607 B, +0.057)."},"fee_diff_vs_full_TellPolicy_shared_tuning_callbacks":{"how":"collect.py drives TellPolicy(candidate tables) and shadows TellPolicy(full qm) on the same callbacks, setting the shadow fb,fa to the candidate after each call, over 60000..60255","candidate":{"fee_max_bps":36.8207604387738,"fee_mean_bps":0.14483882120132113,"fee_n":5541184,"table_rms_visit_bps":0.5377702687200462,"nodes":65843},"C0_compressed":{"fee_max_bps":36.14763050610925,"fee_mean_bps":0.2609114813725296,"fee_n":5547524,"table_rms_visit_bps":0.8412273062798223,"nodes":65376},"note":"Max 36.8 bps (C0 36.1): this is the compression gap to the full tables, not a port error. Mean falls from 0.261 to 0.145 bps. The final port still needs <=0.01 bps against its own reference (TellPolicy over the decoded candidate tables); that has not been tested here."},"table_error_vs_full_qm":{"visit_weighted_rms_bps":{"C0":0.8412,"candidate":0.5378},"all_nodes":{"C0":{"ask_nodes":536712,"ask_rms_bps":4.8283,"ask_max_bps":204.7921,"bid_rms_bps":4.8283,"bid_max_bps":204.7921},"candidate":{"ask_nodes":536712,"ask_rms_bps":4.8169,"ask_max_bps":204.7921,"bid_rms_bps":4.8169,"bid_max_bps":204.7921}}},"bytes_and_gas":{"measured_in":"forge 1.9.0 scratch harness (solc 0.8.24, via_ir, optimizer 200, paris), standalone contracts, not C0 and not the engine","solidity_matches_python":"forge test: SrsLookup.window equals srres.lookup on 465 windows (entries, near-entries, random, edges): PASS","table_words_runtime_bytes":"about 2,565 (WordsOnly 2,807 minus empty 242)","lookup_logic_bytes":"about 415 (Probe4 3,222 minus WordsOnly 2,807)","net_bytes_measured_standalone":"about 2,980 of C0 3,971 free, leaving about 990 for the detector. Inside C0 it would be different (shared dispatch, inlining).","gas_measured_standalone":"building the 64-word memory table: about 1,750 per callback; 4 windows (ask+bid x 2 sd levels, 2x2 nodes each, bisect on lane-0 then shift-scan): worst 20,271 over the probed calls","gas_estimate_in_C0":"ESTIMATE: 208,775 engine peak + about 22,000, roughly 231,000, leaving about 14,000 under 245,000 for the detector. Skipping a level whose sd weight is 0 would save up to half of the window cost. Not run in C0, not on the engine.","lookup_ops":"per callback: 1 table build (64 PUSH32+MSTORE), 4 windows each about 6 word-bisect probes plus up to about 18 lane scans, 8 int8 adds before the existing clamp"},"limits":["Replica only. No engine, no seeds from 14000000, and C0 was not patched.","The fee-diff gate for a port (<=0.01 bps against the candidate reference) is untested.","Byte and gas figures come from a standalone harness, and the in-C0 cost is an estimate.","The occupancy JSON is regenerated by collect.py rather than shipped.","README gate seeds 10000/10002 differ from published by 0.046/0.029 on this machine (libm)."],"commands":"# Commands (run from a directory holding srres.py, collect.py, tune.py, gen_sol.py; qms/blob.bin = C0's QMS1 blob,\n# amm/ = the fetched tell+solved folders at gtmcknight/amm-sim 66604b34)\npython3 -I srres.py decode qms/blob.bin amm/c0_qm.json                       # C0 tables\npython3 -I amm/run.py gauss 10000 3 out/c0g.json soft=1 qm=c0_qm.json        # 443.101741 571.454483 525.908441 (C0 check values, exact)\npython3 -I amm/run.py tellpol:TellPolicy 60000 256 out/t_full.json soft=1 qm=qm_k1e-5.json\npython3 -I amm/run.py tellpol:TellPolicy 60000 256 out/t_c0.json soft=1 qm=c0_qm.json\npython3 -I collect.py amm amm/c0_qm.json amm/qm_k1e-5.json 60000 256 out/occ_c0.json   # occupancy (C0-TellPolicy) + shadow fee diff\npython3 -I -c \"import json;d=json.load(open('out/occ_c0.json'));json.dump(d['occ'],open('out/occ_c0_flat.json','w'))\"  # sha256 7c7dcf69...4441 here\npython3 -I tune.py . 576,4,1                                                  # build+decode+run.py+pair+shadow (sweep: any K,qd,A list)\npython3 -I srres.py build qms/blob.bin amm/qm_k1e-5.json out/occ_c0_flat.json 576 4 1 final/srs1_K576_q4.bin   # frozen; byte-identical rebuild\npython3 -I srres.py decode qms/blob.bin final/srs1_K576_q4.bin amm/cand_final.json\npython3 -I amm/run.py tellpol:TellPolicy 10000 2048 out/hold_cand.json soft=1 qm=cand_final.json   # holdout, once\npython3 -I amm/pair.py out/hold_cand.json amm/tell_qm.json\npython3 -I gen_sol.py final/srs1_K576_q4.bin gas && forge test --root gas -vv   # Solidity lookup == srres.lookup on 465 windows; gas/size\n","code_zb64":"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","code_sha256":"b223d095633d6d808ebee13aaf809999ed3ff30c0621eeacab5760b3f55b7efa","code_name":"srres.py","bundle_zb64":"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","bundle_sha256":"8f211b6c28423c7849ba9db19a8872e43775fef09938a3718704c009d112a0f6","bundle_files":["COMMANDS.txt","NOTE.txt","SrsLookup.sol","collect.py","gen_sol.py","srs1_K576_q4.b64","tune.py"]}