{"credit":"Taylor (gtmcknight), github.com/gtmcknight/amm-sim@4812a6382311624e1506aca131ca35c378f930d9 research/solved","table":1,"measurement_role":"bound","geometry":{"shape_level_row_column":[3,43,30],"lattice_millibps":500,"level_knots":[0,3,7],"level_knot_sd_bps":[0,12,34],"row_knots":[0,82,107,119,124,128,130,133,135,136,139,140,143,144,145,146,147,148,150,152,154,156,158,159,161,162,164,165,166,167,168,169,170,171,172,173,175,178,181,185,189,202,320],"column_knots":[0,9,12,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,34,36,37,38,39,40,41,42,48],"rows_below_160":24,"rows_at_or_above_160":19,"column_split":{"lower_columns":[0,10],"upper_columns":[11,29],"lower_knots":[0,22],"upper_knots":[23,48],"lower_weight_share":0.5241,"profile_seeds":[64000,64127]},"level_visit_weight_share":[0.3972,0.5905,0.0123]},"seeds_scan":[400000,402047],"seeds_confirm":[410000,418191],"directions":[{"id":"a.L0","levels":[0],"unit":"lattice units (0.5 bps) on every node of the level","steps":[{"step":-2,"nodes_changed":1290,"scan":{"gain":-0.051264,"se":0.004604,"n":2048},"confirm":null},{"step":-1,"nodes_changed":1290,"scan":{"gain":-0.012294,"se":0.003487,"n":2048},"confirm":null},{"step":1,"nodes_changed":1290,"scan":{"gain":-0.034532,"se":0.003597,"n":2048},"confirm":null},{"step":2,"nodes_changed":1290,"scan":{"gain":-0.090386,"se":0.004968,"n":2048},"confirm":null}]},{"id":"a.L1","levels":[1],"unit":"lattice units (0.5 bps) on every node of the level","steps":[{"step":-2,"nodes_changed":1290,"scan":{"gain":-0.087548,"se":0.005154,"n":2048},"confirm":null},{"step":-1,"nodes_changed":1290,"scan":{"gain":-0.034346,"se":0.003931,"n":2048},"confirm":null},{"step":1,"nodes_changed":1290,"scan":{"gain":-0.001306,"se":0.004011,"n":2048},"confirm":null},{"step":2,"nodes_changed":1290,"scan":{"gain":-0.028296,"se":0.005808,"n":2048},"confirm":null}]},{"id":"a.L2","levels":[2],"unit":"lattice units (0.5 bps) on every node of the level","steps":[{"step":-2,"nodes_changed":1290,"scan":{"gain":-7.3e-05,"se":0.002102,"n":2048},"confirm":null},{"step":-1,"nodes_changed":1290,"scan":{"gain":0.002024,"se":0.002028,"n":2048},"confirm":null},{"step":1,"nodes_changed":1290,"scan":{"gain":0.004092,"se":0.002187,"n":2048},"confirm":{"gain":3.6e-05,"se":0.00102,"n":8192}},{"step":2,"nodes_changed":1290,"scan":{"gain":0.001191,"se":0.002096,"n":2048},"confirm":null}]},{"id":"b.L0","levels":[0],"unit":"lattice units on rows with knot < 160","steps":[{"step":-1,"nodes_changed":720,"scan":{"gain":-0.008088,"se":0.003314,"n":2048},"confirm":null},{"step":1,"nodes_changed":720,"scan":{"gain":0.001292,"se":0.00349,"n":2048},"confirm":null}]},{"id":"c.L0","levels":[0],"unit":"lattice units on rows with knot >= 160","steps":[{"step":-1,"nodes_changed":570,"scan":{"gain":-0.002621,"se":0.00207,"n":2048},"confirm":null},{"step":1,"nodes_changed":570,"scan":{"gain":-0.031192,"se":0.002288,"n":2048},"confirm":null}]},{"id":"d.L0","levels":[0],"unit":"lattice units on the lower half of the columns by visit weight","steps":[{"step":-1,"nodes_changed":473,"scan":{"gain":-0.004688,"se":0.003295,"n":2048},"confirm":null},{"step":1,"nodes_changed":473,"scan":{"gain":-0.001921,"se":0.003393,"n":2048},"confirm":null}]},{"id":"e.L0","levels":[0],"unit":"lattice units on the upper half of the columns by visit weight","steps":[{"step":-1,"nodes_changed":817,"scan":{"gain":-0.00398,"se":0.002398,"n":2048},"confirm":null},{"step":1,"nodes_changed":817,"scan":{"gain":-0.030381,"se":0.002461,"n":2048},"confirm":null}]},{"id":"b.L1","levels":[1],"unit":"lattice units on rows with knot < 160","steps":[{"step":-1,"nodes_changed":720,"scan":{"gain":-0.024122,"se":0.003589,"n":2048},"confirm":null},{"step":1,"nodes_changed":720,"scan":{"gain":0.008332,"se":0.003527,"n":2048},"confirm":{"gain":0.008361,"se":0.001769,"n":8192}}]},{"id":"c.L1","levels":[1],"unit":"lattice units on rows with knot >= 160","steps":[{"step":-1,"nodes_changed":570,"scan":{"gain":-0.007357,"se":0.003206,"n":2048},"confirm":null},{"step":1,"nodes_changed":570,"scan":{"gain":-0.008048,"se":0.003092,"n":2048},"confirm":null}]},{"id":"d.L1","levels":[1],"unit":"lattice units on the lower half of the columns by visit weight","steps":[{"step":-1,"nodes_changed":473,"scan":{"gain":-0.010242,"se":0.003484,"n":2048},"confirm":null},{"step":1,"nodes_changed":473,"scan":{"gain":0.007358,"se":0.003462,"n":2048},"confirm":{"gain":0.006895,"se":0.001738,"n":8192}}]},{"id":"e.L1","levels":[1],"unit":"lattice units on the upper half of the columns by visit weight","steps":[{"step":-1,"nodes_changed":817,"scan":{"gain":-0.014083,"se":0.003163,"n":2048},"confirm":null},{"step":1,"nodes_changed":817,"scan":{"gain":-0.007144,"se":0.003173,"n":2048},"confirm":null}]},{"id":"f","levels":[0,1,2],"unit":"percent scale of every node","steps":[{"step":-0.5,"nodes_changed":2143,"scan":{"gain":-0.019855,"se":0.0044,"n":2048},"confirm":null},{"step":-0.25,"nodes_changed":1353,"scan":{"gain":-0.000235,"se":0.002764,"n":2048},"confirm":null},{"step":0.25,"nodes_changed":1353,"scan":{"gain":0.002508,"se":0.003813,"n":2048},"confirm":null,"encodable":false,"encode_error":"int8 column difference overflow"},{"step":0.5,"nodes_changed":2143,"scan":{"gain":-0.001176,"se":0.004789,"n":2048},"confirm":null,"encodable":false,"encode_error":"int8 column difference overflow"}]},{"id":"g","levels":[0,1,2],"unit":"row-grid units; new(x) = old(x - step), linear between row knots, ends clamped","steps":[{"step":-0.1,"nodes_changed":2725,"scan":{"gain":-0.051385,"se":0.00455,"n":2048},"confirm":null},{"step":-0.05,"nodes_changed":501,"scan":{"gain":-0.002987,"se":0.00251,"n":2048},"confirm":null},{"step":0.05,"nodes_changed":501,"scan":{"gain":0.004467,"se":0.002199,"n":2048},"confirm":{"gain":0.002453,"se":0.001137,"n":8192}},{"step":0.1,"nodes_changed":2725,"scan":{"gain":-0.002608,"se":0.004646,"n":2048},"confirm":null}]},{"id":"h","levels":[0,1,2],"unit":"millibps per row-grid unit from 160","steps":[{"step":-10,"nodes_changed":1170,"scan":{"gain":0.006546,"se":0.003703,"n":2048},"confirm":{"gain":-0.003776,"se":0.001361,"n":8192}},{"step":-5,"nodes_changed":360,"scan":{"gain":0.003561,"se":0.003267,"n":2048},"confirm":{"gain":-0.001905,"se":0.001077,"n":8192}},{"step":5,"nodes_changed":360,"scan":{"gain":0.000111,"se":0.00216,"n":2048},"confirm":null},{"step":10,"nodes_changed":1170,"scan":{"gain":-0.004937,"se":0.0026,"n":2048},"confirm":null}]}],"confirmed":[{"id":"b.L1","step":1,"gain":0.008361,"se":0.001769},{"id":"d.L1","step":1,"gain":0.006895,"se":0.001738},{"id":"g","step":0.05,"gain":0.002453,"se":0.001137}],"sum_of_confirmed":{"gain":0.00947,"se":0.002293,"n":8192},"gain_vs_base":0.00947,"se":0.002293,"n":8192,"seeds":[410000,418191],"best_figure":"sum of the confirmed steps","best_single_step":{"id":"b.L1","step":1,"gain":0.008361,"se":0.001769},"best_delta_nodes":1326,"best_delta_encodable":true,"bar_check":{"bar":0.03,"upper_2se":0.014057,"early_stop":true,"tool":"harness score.py on the CONFIRM rows of the best figure"},"best_delta_zb64":"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","advance":true,"source_sha256":"e183e5bc3fb794b7067703b10a7da9920267aa5f4caa968e16ca101b02338f40","dropped":[],"engine_runs":0,"report_set_evaluated":false,"controls":{"implementation_sha256_ok":true,"dependency_sha256_ok":true,"qlx5_source_sha256_ok":true,"qpl_roundtrip_byte_identical":true,"qpl_bytes_found_in_qlx5_source":true,"empty_delta_equals_original_64":{"seeds":[400000,400063],"n":64,"equal":true},"visit_profile_matches_harness_by_column":true,"column_split":{"lower_columns":[0,10],"upper_columns":[11,29],"lower_knots":[0,22],"upper_knots":[23,48],"lower_weight_share":0.5241,"profile_seeds":[64000,64127]},"level_weight_share":[0.3972,0.5905,0.0123],"empty_delta_equals_original_scan":{"seeds":[400000,402047],"n":2048,"equal":true},"harness_validate_py_pass":true,"implementation_sha256":"4d4894474104eac9148e52b18d679b994ce73c6a889bafa18169c8dacca22855"},"steps_scored":{"scan":40,"confirm":6,"sum":1},"scan_script_zb64":"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","scan_script_sha256":"0bc946c91c7342ca5c2a4527705c7b063c9bff5c739b5daea79d38cdc1a2480f","limitations":["Replica only (harness overlay build of Taylor's replica, g++ -O3 -std=c++20 -ffp-contract=off); no engine run, no Solidity, nothing submitted. Seeds 10000..12047 and 64000..65023 were not scored; only the visit profile ran on 64000..64127. The harness validate.py was also run (its control seeds 10010512..10011023) and passed.","Bound reading: the best CONFIRM figure, the sum of the three confirmed steps, is +0.00947 se 0.00229 (mean + 2 se = 0.0141), below the +0.03 promotion bar; no single step exceeds +0.0084. None of these global directions of table 1 is worth promoting. This bounds these line directions only, not finer or joint moves of the table.","The sum was scored on the same CONFIRM seeds that picked its components, and six steps were tested on CONFIRM without a multiple-comparison correction; the figures are optimistic. g +0.05 passes mean - 2 se by 0.0002 only. b.L1 +1 and d.L1 +1 overlap (rows below 160 in columns 0..10 move +2 units in the sum), so their gains are not independent.","'Every node' was read literally for (a)-(e) and (h): nodes stored as 0 move too. A positive offset there lifts a zero fee term to 0.5 bps per unit; a negative one is removed by the interpolation's positive clamp.","(d)/(e): columns were split in stored-column order at the cut closest to half of table 1's visit weight (abs_weight summed over levels, profile seeds 64000..64127): columns 0..10 (rival knots 0..22, 52.4% of weight) and 11..29. The same split was used for both level knots. Reading 'half by visit weight' as the less and more visited columns would give other sets; that reading was not scored.","(g) convention: new(x) = old(x - step) along the row axis, linear between row knots, clamped at rows 0 and 320. (h): delta = step * (row knot - 160) millibps. After rounding to the 0.5 bps lattice the tilt moves only rows at least 25 (step 10) or 50 (step 5) grid units from 160, and the scale (f) moves only nodes of at least 100 units (0.5%) or 200 units (0.25%); the most visited rows (knots 148..167) are untouched by (h) and little touched by (f). nodes_changed gives the realised count.","f +0.25% and +0.5% fail qpl.apply (int8 column difference overflow), so they are not encodable in QPL1 as they stand; they were scored as raw replica deltas with qpl.apply's rounding rule (checked equal to qpl.apply on every encodable step) and are flagged encodable false. Both are not positive at one se on SCAN.","Each delta acts on ask and bid through the unchanged mirrored lookup. Level knot 2 (sd 34 bps) carries 1.2% of table 1's visit weight, so its scans are near zero by construction. se is the sample sd of paired per-seed differences over sqrt(n); gains are rounded to 6 decimals.","Replica-to-engine parity is the harness's published figure (max abs error 4.99e-07 on 512 seeds), re-derived here by validate.py from its archived engine rows; it was not re-measured on an engine."]}