{ "approach": "Normalizer-spot observation added to CH fair-price estimate only; CH fee equations and slots 0..10 unchanged. Selected blend10 on tuning seeds only. Let s=our post-trade spot, g=1-feeUsed, gN=0.997. Interior router equality gives normalizer post-spot n=s*g/gN when AMM buys X, n=s*gN/g when AMM sells X. Test clamp pHat to [n*gN,n/gN] or blend pHat toward n with weight 0.1, 0.3, 0.5. Apply only !firstInStep && feeUsed>30bps && g>0, avoiding initial arbitrage. No added state or loops. This is a noisy observation: clipped retail splits need not equalize marginal prices, and retail can move normalizer outside its 30bps fair-price band before next-step arbitrage. Numerical inference check passed for 16,936 randomized interior buy/sell splits (max relative error 1.1289201922264348e-15).", "tried": [ { "variant": "clamp", "seeds": "10000..10499", "n": 500, "mean_diff": -23.525772599183195, "se": 0.9291162252922291, "code_sha256": "fcc8b42cfa664f60cf4040b49aad90492ef61da9fc8c6680c4651437655f6300", "worst": [ { "seed": 10374, "candidate_edge": 291.8630653785245, "reference_edge": 513.0380888831763, "diff": -221.17502350465185 }, { "seed": 10079, "candidate_edge": 356.7483997248214, "reference_edge": 566.5518923649703, "diff": -209.80349264014887 }, { "seed": 10165, "candidate_edge": 498.59807232514055, "reference_edge": 664.6013302261374, "diff": -166.00325790099686 }, { "seed": 10085, "candidate_edge": 511.957541459765, "reference_edge": 677.2269172468665, "diff": -165.26937578710147 }, { "seed": 10470, "candidate_edge": 625.5977856851785, "reference_edge": 720.7230833826019, "diff": -95.12529769742343 } ] }, { "variant": "blend10", "seeds": "10000..10499", "n": 500, "mean_diff": 0.4241044652309373, "se": 0.030052716398540066, "code_sha256": "f1ea5b95c853ef28399a0b22ec222773525dba18c92282c04993170c97b57c83", "worst": [ { "seed": 10355, "candidate_edge": 572.2866605144088, "reference_edge": 574.1784720544963, "diff": -1.891811540087474 }, { "seed": 10085, "candidate_edge": 675.7728737218766, "reference_edge": 677.2269172468665, "diff": -1.4540435249898565 }, { "seed": 10307, "candidate_edge": 778.402485412893, "reference_edge": 779.7434157802936, "diff": -1.3409303674005741 }, { "seed": 10277, "candidate_edge": 478.72561605723564, "reference_edge": 479.96822839737325, "diff": -1.2426123401376117 }, { "seed": 10128, "candidate_edge": 638.0824765069484, "reference_edge": 639.3175601794634, "diff": -1.2350836725149748 } ] }, { "variant": "blend30", "seeds": "10000..10499", "n": 500, "mean_diff": -0.8260354078232962, "se": 0.07510982182410636, "code_sha256": "8aea9f6ef966a040ac9672c7a7d6b1385d36ad91eddc33197f49a34c6bf31d0d", "worst": [ { "seed": 10159, "candidate_edge": 630.0519382889064, "reference_edge": 638.5466279183546, "diff": -8.494689629448203 }, { "seed": 10193, "candidate_edge": 643.0597576218383, "reference_edge": 650.2510664958626, "diff": -7.19130887402423 }, { "seed": 10420, "candidate_edge": 642.2257409443745, "reference_edge": 648.9393335359108, "diff": -6.713592591536326 }, { "seed": 10495, "candidate_edge": 562.694739583961, "reference_edge": 569.2702168015401, "diff": -6.575477217579078 }, { "seed": 10097, "candidate_edge": 592.5515874730062, "reference_edge": 598.4301592569326, "diff": -5.878571783926418 } ] }, { "variant": "blend50", "seeds": "10000..10499", "n": 500, "mean_diff": -6.033843115048026, "se": 0.20195426723978813, "code_sha256": "2f543ed319e22b1fe439f9e98948a7f52bae35b5802c52902e5df37c60e3c555", "worst": [ { "seed": 10470, "candidate_edge": 690.3390074117697, "reference_edge": 720.7230833826019, "diff": -30.384075970832214 }, { "seed": 10475, "candidate_edge": 756.6363824241075, "reference_edge": 781.2752665258633, "diff": -24.63888410175582 }, { "seed": 10193, "candidate_edge": 626.0032621394153, "reference_edge": 650.2510664958626, "diff": -24.24780435644732 }, { "seed": 10374, "candidate_edge": 488.82371640115167, "reference_edge": 513.0380888831763, "diff": -24.214372482024658 }, { "seed": 10111, "candidate_edge": 629.1663827804573, "reference_edge": 650.9196925847169, "diff": -21.75330980425963 } ] } ], "next": "Promote the frozen candidate: fresh paired gain exceeds twice its standard error.", "code": "// SPDX-License-Identifier: MIT\npragma solidity ^0.8.24;\n\nimport {AMMStrategyBase} from \"./AMMStrategyBase.sol\";\nimport {TradeInfo} from \"./IAMMStrategy.sol\";\n\ncontract Strategy is AMMStrategyBase {\n uint256 constant ELAPSED_CAP = 8;\n uint256 constant SIGNAL_THRESHOLD = WAD / 650;\n uint256 constant DIR_DECAY = 750000000000000000;\n uint256 constant ACT_DECAY = 530000000000000000;\n uint256 constant SIZE_DECAY = 530000000000000000;\n uint256 constant TOX_DECAY = 910000000000000000;\n uint256 constant SIGMA_DECAY = 690000000000000000;\n uint256 constant LAMBDA_DECAY = 990000000000000000;\n uint256 constant SIZE_BLEND_DECAY = 828000000000000000;\n uint256 constant TOX_BLEND_DECAY = 51000000000000000;\n uint256 constant ACT_BLEND_DECAY = 985000000000000000;\n uint256 constant PHAT_ALPHA = 270000000000000000;\n uint256 constant PHAT_ALPHA_RETAIL = 60000000000000000;\n uint256 constant DIR_IMPACT_MULT = 4;\n uint256 constant GATE_SIGMA_MULT = 7200000000000000000;\n uint256 constant MIN_GATE = 30000000000000000;\n uint256 constant TRADE_TOX_BOOST = 3500 * BPS;\n uint256 constant STALE_ATTRACT_FRAC = 1050000000000000000;\n uint256 constant RET_CAP = WAD / 35;\n uint256 constant TOX_CAP = WAD / 5;\n uint256 constant TRADE_RATIO_CAP = WAD / 5;\n uint256 constant LAMBDA_CAP = 1820000000000000000;\n uint256 constant STEP_COUNT_CAP = 64;\n uint256 constant BASE_FEE = 4 * BPS;\n uint256 constant SIGMA_COEF = 200000000000000000;\n uint256 constant LAMBDA_COEF = 12 * BPS;\n uint256 constant FLOW_SIZE_COEF = 4842 * BPS;\n uint256 constant TOX_COEF = 300 * BPS;\n uint256 constant TOX_QUAD_COEF = 15000 * BPS;\n uint256 constant ACT_COEF = 91843 * BPS;\n uint256 constant DIR_COEF = 20 * BPS;\n uint256 constant DIR_TOX_COEF = 100 * BPS;\n uint256 constant STALE_DIR_COEF = 6850 * BPS;\n uint256 constant SIGMA_TOX_COEF = 500 * BPS;\n uint256 constant TAIL_KNEE = 600 * BPS;\n uint256 constant TAIL_SLOPE_PROTECT = 930000000000000000;\n uint256 constant TAIL_SLOPE_ATTRACT = 850000000000000000;\n\n function afterInitialize(uint256 initialX, uint256 initialY) external override returns (uint256, uint256) {\n slots[0] = BASE_FEE; slots[1] = BASE_FEE; slots[2] = 0; slots[3] = WAD; slots[4] = 0;\n slots[5] = initialX > 0 ? wdiv(initialY, initialX) : 100 * WAD;\n slots[6] = 950000000000000; slots[7] = 800000000000000000; slots[8] = 2000000000000000;\n slots[9] = 0; slots[10] = 0;\n return (BASE_FEE, BASE_FEE);\n }\n\n function afterSwap(TradeInfo calldata trade) external override returns (uint256, uint256) {\n uint256 prevBidFee = slots[0]; uint256 prevAskFee = slots[1]; uint256 lastTs = slots[2];\n uint256 dirState = slots[3]; uint256 actEma = slots[4]; uint256 pHat = slots[5];\n uint256 sigmaHat = slots[6]; uint256 lambdaHat = slots[7]; uint256 sizeHat = slots[8];\n uint256 toxEma = slots[9]; uint256 stepTradeCount = slots[10];\n\n bool isNewStep = trade.timestamp > lastTs;\n if (isNewStep) {\n uint256 elapsedRaw = trade.timestamp - lastTs;\n uint256 elapsed = elapsedRaw > ELAPSED_CAP ? ELAPSED_CAP : elapsedRaw;\n dirState = _decayCentered(dirState, DIR_DECAY, elapsed);\n actEma = wmul(actEma, _powWad(ACT_DECAY, elapsed));\n sizeHat = wmul(sizeHat, _powWad(SIZE_DECAY, elapsed));\n toxEma = wmul(toxEma, _powWad(TOX_DECAY, elapsed));\n if (stepTradeCount > 0 && elapsedRaw > 0) {\n uint256 lambdaInst = (stepTradeCount * WAD) / elapsedRaw;\n if (lambdaInst > LAMBDA_CAP) lambdaInst = LAMBDA_CAP;\n lambdaHat = wmul(lambdaHat, LAMBDA_DECAY) + wmul(lambdaInst, WAD - LAMBDA_DECAY);\n }\n stepTradeCount = 0;\n }\n\n bool firstInStep = stepTradeCount == 0;\n uint256 spot = trade.reserveX > 0 ? wdiv(trade.reserveY, trade.reserveX) : pHat;\n if (pHat == 0) pHat = spot;\n\n uint256 feeUsed = trade.isBuy ? prevBidFee : prevAskFee;\n uint256 gamma = feeUsed < WAD ? WAD - feeUsed : 0;\n uint256 pImplied;\n if (gamma == 0) { pImplied = spot; }\n else { pImplied = trade.isBuy ? wmul(spot, gamma) : wdiv(spot, gamma); }\n\n {\n uint256 ret = pHat > 0 ? wdiv(absDiff(pImplied, pHat), pHat) : 0;\n uint256 alpha = firstInStep ? PHAT_ALPHA : PHAT_ALPHA_RETAIL;\n uint256 adaptiveGate = wmul(sigmaHat, GATE_SIGMA_MULT);\n if (adaptiveGate < MIN_GATE) adaptiveGate = MIN_GATE;\n if (ret <= adaptiveGate) { pHat = wmul(pHat, WAD - alpha) + wmul(pImplied, alpha); }\n if (firstInStep) {\n if (ret > RET_CAP) ret = RET_CAP;\n sigmaHat = wmul(sigmaHat, SIGMA_DECAY) + wmul(ret, WAD - SIGMA_DECAY);\n }\n }\n\n // Interior retail routing equalizes fee-adjusted marginal prices.\n // Subsequent trades in a step cannot be the initial arbitrage trade.\n if (!firstInStep && feeUsed > 30 * BPS && gamma > 0) {\n uint256 normalSpot = trade.isBuy\n ? wdiv(wmul(spot, gamma), WAD - 30 * BPS)\n : wdiv(wmul(spot, WAD - 30 * BPS), gamma);\n pHat = wmul(pHat, 90 * WAD / 100) + wmul(normalSpot, 10 * WAD / 100);\n }\n\n uint256 tradeRatio = trade.reserveY > 0 ? wdiv(trade.amountY, trade.reserveY) : 0;\n if (tradeRatio > TRADE_RATIO_CAP) tradeRatio = TRADE_RATIO_CAP;\n\n if (tradeRatio > SIGNAL_THRESHOLD) {\n uint256 push = tradeRatio * DIR_IMPACT_MULT;\n if (push > WAD / 4) push = WAD / 4;\n if (trade.isBuy) {\n dirState = dirState + push;\n if (dirState > 2 * WAD) dirState = 2 * WAD;\n } else {\n dirState = dirState > push ? dirState - push : 0;\n }\n actEma = wmul(actEma, ACT_BLEND_DECAY) + wmul(tradeRatio, WAD - ACT_BLEND_DECAY);\n sizeHat = wmul(sizeHat, SIZE_BLEND_DECAY) + wmul(tradeRatio, WAD - SIZE_BLEND_DECAY);\n if (sizeHat > WAD) sizeHat = WAD;\n }\n\n uint256 tox = pHat > 0 ? wdiv(absDiff(spot, pHat), pHat) : 0;\n if (tox > TOX_CAP) tox = TOX_CAP;\n toxEma = wmul(toxEma, TOX_BLEND_DECAY) + wmul(tox, WAD - TOX_BLEND_DECAY);\n uint256 toxSignal = toxEma;\n\n stepTradeCount = stepTradeCount + 1;\n if (stepTradeCount > STEP_COUNT_CAP) stepTradeCount = STEP_COUNT_CAP;\n\n uint256 flowSize = wmul(lambdaHat, sizeHat);\n uint256 fBase = BASE_FEE + wmul(SIGMA_COEF, sigmaHat) + wmul(LAMBDA_COEF, lambdaHat) + wmul(FLOW_SIZE_COEF, flowSize);\n uint256 fMid = fBase + wmul(TOX_COEF, toxSignal) + wmul(TOX_QUAD_COEF, wmul(toxSignal, toxSignal)) + wmul(ACT_COEF, actEma);\n fMid = fMid + wmul(SIGMA_TOX_COEF, wmul(sigmaHat, toxSignal));\n\n uint256 dirDev; bool sellPressure;\n if (dirState >= WAD) { dirDev = dirState - WAD; sellPressure = true; }\n else { dirDev = WAD - dirState; sellPressure = false; }\n\n uint256 skew = wmul(DIR_COEF, dirDev) + wmul(DIR_TOX_COEF, wmul(dirDev, toxSignal));\n uint256 bidFee; uint256 askFee;\n if (sellPressure) {\n bidFee = fMid + skew;\n askFee = fMid > skew ? fMid - skew : 0;\n } else {\n askFee = fMid + skew;\n bidFee = fMid > skew ? fMid - skew : 0;\n }\n\n {\n uint256 staleShift = wmul(STALE_DIR_COEF, toxSignal);\n uint256 attractShift = wmul(staleShift, STALE_ATTRACT_FRAC);\n if (spot >= pHat) {\n bidFee = bidFee + staleShift;\n askFee = askFee > attractShift ? askFee - attractShift : 0;\n } else {\n askFee = askFee + staleShift;\n bidFee = bidFee > attractShift ? bidFee - attractShift : 0;\n }\n }\n\n {\n bool tradeAligned = (trade.isBuy && spot >= pHat) || (!trade.isBuy && spot < pHat);\n if (tradeAligned) {\n uint256 tradeBoost = wmul(TRADE_TOX_BOOST, tradeRatio);\n if (trade.isBuy) { bidFee = bidFee + tradeBoost; }\n else { askFee = askFee + tradeBoost; }\n }\n }\n\n if (sellPressure) {\n bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_PROTECT));\n askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_ATTRACT));\n } else {\n askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_PROTECT));\n bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_ATTRACT));\n }\n\n slots[0] = bidFee; slots[1] = askFee; slots[2] = trade.timestamp;\n slots[3] = dirState; slots[4] = actEma; slots[5] = pHat;\n slots[6] = sigmaHat; slots[7] = lambdaHat; slots[8] = sizeHat;\n slots[9] = toxEma; slots[10] = stepTradeCount;\n\n return (bidFee, askFee);\n }\n\n function _compressTailWithSlope(uint256 fee, uint256 slope) internal pure returns (uint256) {\n if (fee <= TAIL_KNEE) return fee;\n return TAIL_KNEE + wmul(fee - TAIL_KNEE, slope);\n }\n\n function _powWad(uint256 factor, uint256 exp) internal pure returns (uint256 result) {\n result = WAD;\n while (exp > 0) {\n if (exp & 1 == 1) result = wmul(result, factor);\n factor = wmul(factor, factor);\n exp >>= 1;\n }\n }\n\n function _decayCentered(uint256 centered, uint256 decayFactor, uint256 elapsed) internal pure returns (uint256) {\n uint256 mul = _powWad(decayFactor, elapsed);\n if (centered >= WAD) { return WAD + wmul(centered - WAD, mul); }\n uint256 below = wmul(WAD - centered, mul);\n return below < WAD ? WAD - below : 0;\n }\n\n function getName() external pure override returns (string memory) { return \"no_cubic\"; }\n}\n", "code_sha256": "f1ea5b95c853ef28399a0b22ec222773525dba18c92282c04993170c97b57c83", "delta": "Insert immediately before `uint256 tradeRatio = ...`, after CH pHat/sigma update; no other edits:\n // Interior retail routing equalizes fee-adjusted marginal prices.\n // Subsequent trades in a step cannot be the initial arbitrage trade.\n if (!firstInStep && feeUsed > 30 * BPS && gamma > 0) {\n uint256 normalSpot = trade.isBuy\n ? wdiv(wmul(spot, gamma), WAD - 30 * BPS)\n : wdiv(wmul(spot, WAD - 30 * BPS), gamma);\n pHat = wmul(pHat, 90 * WAD / 100) + wmul(normalSpot, 10 * WAD / 100);\n }\n\n", "score": { "seed_start": 0, "n": 1000, "mean_edge": 526.0337302497852, "se": 2.7912248204542776 }, "paired": { "reference": "CH 6dd68f77", "seed_start": 600000, "n": 2000, "mean_diff": 0.4644641542360268, "se": 0.01585285122414532, "worst": [ { "seed": 601271, "candidate_edge": 764.2518320516724, "reference_edge": 768.8296864776336, "diff": -4.5778544259611635 }, { "seed": 601909, "candidate_edge": 495.0996504280315, "reference_edge": 498.1054599032533, "diff": -3.005809475221781 }, { "seed": 601666, "candidate_edge": 601.2486805990901, "reference_edge": 603.61737446422, "diff": -2.3686938651298988 }, { "seed": 601072, "candidate_edge": 589.5234911375389, "reference_edge": 591.785831820069, "diff": -2.2623406825300663 }, { "seed": 600393, "candidate_edge": 755.5093272170868, "reference_edge": 757.6588291573596, "diff": -2.149501940272785 } ] }, "seconds_per_simulation": 0.1913255714694304, "validate_ok": true, "blocked": null, "citations": [ { "url": "https://raw.githubusercontent.com/ChengHua926/amm-challenge/d34a5199c59a4c44d5336a25f1436b4ae1f21104/contracts/src/Strategy.sol", "quote": "uint256 constant PHAT_ALPHA = 270000000000000000;" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/router.rs", "quote": "// Clamp to valid range [0, Y]" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/amm/cfmm.rs", "quote": "//! into separate buckets rather than being reinvested into liquidity." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py", "quote": "rng = np.random.default_rng(seed=i)" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py", "quote": "retail_mean_size_min=19.0,\n retail_mean_size_max=21.0," }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/simulation/engine.rs", "quote": "// Initialize retail trader with different seed" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/contracts/src/VanillaStrategy.sol", "quote": "uint256 public constant FEE = 30 * BPS;" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/evm/strategy.rs", "quote": "const GAS_LIMIT_INIT: u64 = 250_000;" }, { "url": "https://raw.githubusercontent.com/dipankar/amm-challenge/main/ANALYSIS.md", "quote": "Observe trade → Estimate hidden state (pHat, sigmaHat, tox, dir, act)" }, { "url": "https://www.linkedin.com/pulse/amm-fee-challenge-notes-from-our-run-optimization-arena-qe3ff", "quote": "Another useful property of the simulator was block ordering." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/router.rs", "quote": "/// Implements optimal order splitting so that the marginal price is equal\n/// across all AMMs after the trade." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/arbitrageur.rs", "quote": "/// Closed-form (fee-on-input): Δx_in = (sqrt(k·γ / p) - x) / γ" }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/amm/cfmm.rs", "quote": "// On error, keep current fees" } ], "methodology": { "simulator_commit": "6b6921f8d463314aa7c96234e1be25a25245f704", "comparison": "For each seed, separately run candidate vs VanillaStrategy and CH vs VanillaStrategy; subtract submission edges, never candidate vs CH in a shared market.", "config": "numpy.default_rng(seed): size U(19,21), rate U(0.6,1.0), sigma U(0.000882,0.001008), in that order. n_steps=10000, price=100, x=100, y=10000, mu=0, dt=1, retail_buy_prob=0.5, retail_size_sigma=1.2. Rust price seed=seed, retail seed=seed+1.", "statistics": "Arithmetic mean; SE = sample standard deviation (ddof=1)/sqrt(n). Worst = five most negative paired differences. Score SE is unpaired per-seed edge SE.", "batching": "amm_sim_rs.run_batch with 8 workers, chunks of 50, unmodified simulator. All requested seeds completed; holdout candidate run once after freeze. 900000..909999 never used.", "timing": "seconds_per_simulation = sum of selected candidate tuning, holdout, and score batch wall seconds / 3500, with 8 workers; includes config and result handling but excludes compilation. Concurrent reference work increases wall time.", "frozen": { "variant": "blend10", "sha256": "f1ea5b95c853ef28399a0b22ec222773525dba18c92282c04993170c97b57c83", "selection": "Highest paired tuning mean; no holdout candidate results observed before this choice." } }, "scoreboard": { "reference_sha256": "6dd68f77a70900319460215374143dbd5d924198450a46d9f5f91f6b1e3d35c3", "reference_score": { "seed_start": 0, "n": 1000, "mean_edge": 525.5258821780834, "se": 2.7894264590251843 }, "reference_score_expected_from_brief": 525.525882178, "reference_score_difference_from_brief": 8.344613888766617e-11, "promoted": true, "incumbent_sha256": "f1ea5b95c853ef28399a0b22ec222773525dba18c92282c04993170c97b57c83", "ranked_promotions": [ { "rank": 1, "code_sha256": "f1ea5b95c853ef28399a0b22ec222773525dba18c92282c04993170c97b57c83", "score": 526.0337302497852, "paired_gain": 0.4644641542360268, "se": 0.01585285122414532 } ], "starter_comparison": null, "starter_comparison_note": "Not measured; this bounded item requests paired comparison against CH." }, "checks": { "router_band_counterexample": { "fair_price": 100, "fee_bps": 50, "normalizer_fee_bps": 30, "retail_buy_y": 100, "our_y": 44.9848553108938, "normalizer_y": 55.0151446891062, "our_post_spot": 100.89720207211299, "inferred_normalizer_post_spot": 101.1000105184891, "actual_normalizer_post_spot": 101.10001051848904, "band_low": 100.79671048693358, "band_high": 101.40422318805321 }, "validate_stdout": "Validating strategy...\nCompiling strategy...\nStrategy 'no_cubic' validated successfully!", "slots_used": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ], "no_added_loops": true, "gas": { "n_calls": 3000, "initialization_gas": 185532, "max_after_swap_gas": 94268, "gas_limit": 250000, "all_success": true }, "gas_note": "Separate pyrevm stress check: 3000 constant-product trades per variant, both sides, randomized sizes and timestamp gaps; every call succeeded with 250000 gas and bounded fees. Values read from pyrevm EVM.result.gas_used, not executor estimate. Successful batch scores alone are not proof: pinned CFMM silently retains fees on swap-hook error.", "public_writeups": "Read Algebra Finance notes (environment estimation, asymmetric fees, first-trade arbitrage) and dipankar ANALYSIS.md (state estimation). Their reported scores are not used as measured evidence for this item." } }