{ "blocked": null, "valid": true, "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 PHAT_ALPHA_SAME = 120000000000000000;\n uint256 constant REVERT_U = 0;\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 = 128000000000000000;\n uint256 constant DIR_TOX_COEF = 640000000000000000;\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[3] = WAD; \n slots[5] = initialX > 0 ? wdiv(initialY, initialX) : 100 * WAD;\n slots[6] = 950000000000000; slots[7] = 800000000000000000; slots[8] = 2000000000000000;\n slots[15] = 400000000000000000 | (uint256(2000000000000000) << 160); slots[13] = 902500000000; slots[14] = slots[5]; \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 = uint64(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 uint256 sigmaForFast = sigmaHat;\n uint256 fastHat = slots[14];\n uint256 uncertainty = slots[13];\n uint256 silent = trade.timestamp > lastTs ? trade.timestamp - lastTs : 0;\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 // Process variance is propagated inside the censored update.\n if (uncertainty > 100000000000000) uncertainty = 100000000000000;\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 // S: infer a no-trade interval center from the last post-trade spot.\n uint256 silenceScale = WAD;\n if (firstInStep && silent > 1) {\n uint256 g = silent - 1;\n if (g > 1) g = 1;\n uint256 w = WAD - _powWad(800000000000000000, g);\n uint256 s = slots[2] >> 64;\n if (s == 0) s = pHat;\n uint256 c = (wmul(s, WAD - prevBidFee) + wdiv(s, WAD - prevAskFee)) / 2;\n if (c >= pHat) pHat += wmul(w, c - pHat);\n else pHat -= wmul(w, pHat - c);\n silenceScale = WAD - wmul(300000000000000000, w);\n }\n\n {\n uint256 ret = pHat > 0 ? wdiv(absDiff(pImplied, pHat), pHat) : 0;\n uint256 alpha = firstInStep ? PHAT_ALPHA : PHAT_ALPHA_RETAIL;\n uint256 prePhat = pHat;\n bool secondPrint = !firstInStep && stepTradeCount == 1;\n bool sameDir = false; bool oppDir = false;\n if (secondPrint) {\n bool up2 = pImplied >= pHat;\n uint256 d1 = slots[12];\n if (d1 != 0) { sameDir = (d1 == 1) == up2; oppDir = !sameDir; }\n if (sameDir) alpha = PHAT_ALPHA_SAME;\n }\n if (firstInStep) { slots[12] = pImplied >= pHat ? 1 : 2; }\n uint256 adaptiveGate = wmul(sigmaHat, GATE_SIGMA_MULT);\n if (adaptiveGate < MIN_GATE) adaptiveGate = MIN_GATE;\n alpha = wmul(alpha, silenceScale);\n adaptiveGate = wmul(adaptiveGate, silenceScale);\n if (ret <= adaptiveGate) { pHat = wmul(pHat, WAD - alpha) + wmul(pImplied, alpha); }\n if (oppDir && REVERT_U > 0) {\n uint256 pre = slots[11];\n if (pre > pHat) pHat = pHat + wmul(pre - pHat, REVERT_U);\n else pHat = pHat - wmul(pHat - pre, REVERT_U);\n }\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 // Censored assumed-density posterior. No external or future inputs.\n uint256 arbProbability;\n (fastHat, uncertainty, arbProbability) = _posterior(PosteriorInput(\n fastHat, uncertainty, pImplied, spot, slots[2] >> 64,\n prevBidFee, prevAskFee, firstInStep, silent, trade.isBuy,\n trade.reserveY > 0 ? wdiv(trade.amountY, trade.reserveY) : 0\n ));\n slots[13] = uncertainty;\n slots[14] = fastHat;\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 skewRatio = tradeRatio;\n uint256 cleanSize = uint80(slots[15] >> 160);\n if (cleanSize == 0) cleanSize = 2000000000000000;\n uint256 skewCap = wmul(cleanSize, 8000000000000000000);\n if (skewRatio > skewCap) skewRatio = skewCap;\n uint256 push = skewRatio * DIR_IMPACT_MULT;\n if (push > WAD / 4) push = WAD / 4;\n push = wmul(push, 0 + wmul(1000000000000000000, arbProbability));\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 originalLambda = lambdaHat; uint256 originalSize = sizeHat;\n\n if (342406799193418304 > 0) {\n uint256 packedFlow = slots[15];\n uint256 rate = uint80(packedFlow);\n uint256 count = uint80(packedFlow >> 80);\n uint256 meanSize = uint80(packedFlow >> 160);\n if (rate == 0) rate = 400000000000000000;\n if (meanSize == 0) meanSize = 2000000000000000;\n if (isNewStep) {\n uint256 inst = count / silent;\n if (inst > 3 * WAD) inst = 3 * WAD;\n uint256 retention = _powWad(999000000000000000, silent > 64 ? 64 : silent);\n rate = wmul(rate, retention) + wmul(inst, WAD-retention);\n count = 0;\n }\n uint256 weight = firstInStep ? WAD-arbProbability : WAD;\n uint256 correctedWeight = weight;\n if (2 == 2) {\n uint256 missing = wmul(feeUsed, 196030880396139429888);\n if (missing > 333333333333333376) missing = 333333333333333376;\n correctedWeight = wdiv(weight, WAD-missing);\n }\n count += correctedWeight;\n uint256 learning = wmul(WAD-999000000000000000, weight);\n meanSize = _blend(meanSize, tradeRatio, learning);\n slots[15]=rate | (count << 80) | (meanSize << 160);\n uint256 retailRate = wmul(rate, 366383424913407168);\n uint256 retailSize = 2 == 0 ? sizeHat : wmul(meanSize,1883296158119298304);\n lambdaHat = _blend(lambdaHat,retailRate,342406799193418304);\n sizeHat = _blend(sizeHat,retailSize,342406799193418304);\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 lambdaHat = originalLambda; sizeHat = originalSize;\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 staleHat = wmul(pHat, 700000000000000000) + wmul(fastHat, 300000000000000000);\n uint256 staleTox = wdiv(absDiff(spot, staleHat), staleHat);\n if (staleTox > TOX_CAP) staleTox = TOX_CAP;\n uint256 staleShift = wmul(STALE_DIR_COEF, staleTox);\n uint256 attractShift = wmul(staleShift, STALE_ATTRACT_FRAC);\n if (spot >= staleHat) {\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 (!firstInStep && tradeBoost > 16 * BPS) tradeBoost = 16 * BPS;\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 if (firstInStep) {\n if (askFee > bidFee && bidFee > 30 * BPS) bidFee = 30 * BPS;\n else if (bidFee > askFee && askFee > 30 * BPS) askFee = 30 * BPS;\n }\n\n if (bidFee > askFee && askFee > 36 * BPS) askFee = 36 * BPS;\n else if (askFee > bidFee && bidFee > 36 * BPS) bidFee = 36 * BPS;\n\n slots[0] = bidFee; slots[1] = askFee; slots[2] = (spot << 64) | 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\n struct PosteriorInput {\n uint256 mu; uint256 v; uint256 obs; uint256 spot; uint256 preSpot;\n uint256 bid; uint256 ask; bool first; uint256 silent; bool buy; uint256 size;\n }\n function _posterior(PosteriorInput memory x) internal pure returns (uint256, uint256, uint256) {\n if (x.mu == 0) x.mu = x.spot;\n if (x.v < 10000000000) x.v = 10000000000;\n uint256 lo = wmul(x.preSpot, WAD-x.bid);\n uint256 hi = wdiv(x.preSpot, WAD-x.ask);\n if (x.first) {\n if (x.silent>1 && x.preSpot>0) {\n uint256 elapsed=x.silent>8?8:x.silent;\n x.v += 902500000000*(elapsed-1);\n (x.mu,x.v)=_band(x.mu,x.v,lo,hi);\n }\n x.v+=902500000000;\n }\n uint256 mRetail = x.mu;\n uint256 vRetail = x.v;\n // A missing own-pool trade is a censored price observation.\n if (x.first && x.preSpot > 0) {\n (mRetail, vRetail) = _band(x.mu, x.v, lo, hi);\n }\n if (!x.first) {\n // A later print is retail. Only an interior route is an observation\n // of the other pool, with explicit observation uncertainty.\n uint256 fee = x.buy ? x.bid : x.ask;\n if (fee > 30 * BPS) {\n uint256 normal = x.buy ? wdiv(wmul(x.spot, WAD-fee), WAD-30*BPS)\n : wdiv(wmul(x.spot, WAD-30*BPS), WAD-fee);\n uint256 residual = wdiv(absDiff(normal, x.mu),x.mu);\n uint256 noise = 9000000000000 + wmul(residual,residual);\n uint256 k = wdiv(x.v,x.v+noise);\n return (_blend(x.mu,normal,k),wmul(x.v,WAD-k),0);\n }\n return (x.mu,x.v,0);\n }\n uint256 e = wdiv(absDiff(x.obs,x.mu),x.mu);\n uint256 totalV = x.v + 22500000000;\n uint256 z = wdiv(wmul(e,e),totalV);\n uint256 density = _powWad(wdiv(WAD,WAD+z/8),4);\n uint256 odds = wmul(density,wdiv(4000000000000000,_isqrt(totalV*WAD)));\n if (x.size > 3000000000000000) odds = wmul(odds,4*WAD/10);\n if (x.silent > 1) odds = wmul(odds,8*WAD/10);\n uint256 sd = _isqrt(x.v*WAD);\n uint256 width = wdiv(hi-lo,x.mu);\n uint256 distance = x.muhi?x.mu-hi:0);\n uint256 zBand = wdiv(wdiv(distance,x.mu),sd);\n uint256 mass = wmul(wdiv(width,width+2*sd),wdiv(WAD,WAD+wmul(zBand,zBand)));\n if (mass < WAD/100) mass = WAD/100;\n odds = wdiv(odds,mass);\n uint256 prob = wdiv(odds,WAD+odds);\n uint256 kArb = wdiv(x.v,totalV);\n uint256 mArb = _blend(x.mu,x.obs,kArb);\n uint256 mean = _blend(mRetail,mArb,prob);\n uint256 between = wdiv(absDiff(mArb,mRetail),x.mu);\n uint256 variance = wmul(prob,wmul(x.v,WAD-kArb)) + wmul(WAD-prob,vRetail)\n + wmul(wmul(prob,WAD-prob),wmul(between,between));\n if (variance > 100000000000000) variance = 100000000000000;\n return (mean,variance,prob);\n }\n function _blend(uint256 a,uint256 b,uint256 w) internal pure returns(uint256) {\n return b>=a ? a+wmul(b-a,w) : a-wmul(a-b,w);\n }\n function _band(uint256 mu,uint256 v,uint256 lo,uint256 hi) internal pure returns(uint256,uint256) {\n // Soft interval likelihood avoids discontinuities at quadrature nodes.\n uint256 sd=wmul(mu,_isqrt(v*WAD));\n uint256[3] memory acc;\n for(uint256 j=0;j<7;j++) {\n uint256 p=j<3 ? (mu>(3-j)*sd?mu-(3-j)*sd:1) : mu+(j-3)*sd;\n uint256 w=j==3?72:(j==2||j==4?45:(j==1||j==5?10:1));\n uint256 distance=phi?p-hi:0);\n uint256 z=sd>0?wdiv(distance,sd):0;\n uint256 likelihood=wdiv(WAD,WAD+4*wmul(z,z));\n w=wmul(w*WAD,likelihood);\n acc[0]+=w;acc[1]+=wmul(w,p);\n uint256 d=wdiv(absDiff(p,mu),mu);\n acc[2]+=wmul(w,wmul(d,d));\n }\n uint256 m=wdiv(acc[1],acc[0]);\n uint256 d=wdiv(absDiff(m,mu),mu);\n uint256 second=wdiv(acc[2],acc[0]);\n return(m,second>wmul(d,d)?second-wmul(d,d):10000000000);\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 // Floor square root: bit-length seed and seven Newton steps (all uint256).\n function _isqrt(uint256 x) internal pure returns (uint256 r) {\n if (x == 0) return 0;\n unchecked {\n uint256 y = x;\n r = 1;\n if (y >> 128 != 0) { y >>= 128; r <<= 64; }\n if (y >> 64 != 0) { y >>= 64; r <<= 32; }\n if (y >> 32 != 0) { y >>= 32; r <<= 16; }\n if (y >> 16 != 0) { y >>= 16; r <<= 8; }\n if (y >> 8 != 0) { y >>= 8; r <<= 4; }\n if (y >> 4 != 0) { y >>= 4; r <<= 2; }\n if (y >> 2 != 0) { r <<= 1; }\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n r = (r + x / r) >> 1;\n uint256 t = x / r;\n return r < t ? r : t;\n }\n }\n\n function getName() external pure override returns (string memory) { return \"censored_10\"; }\n}\n", "sha256": "8fd9c0118ad132be7f077b2277cecdd4fa785faafdc1a35edae06b02aaa408fa", "params": { "a": 0.0, "k": 8.0, "gain": 64.0 }, "mechanism": "For each trade above RS2's original signal threshold, multiply the saturated direction push by a + (1-a)*p, using RS2's posterior arbitrage probability p. Before forming that push, cap its trade ratio at k times the previously stored posterior-cleaned mean size in slot 15, and multiply DIR_COEF and DIR_TOX_COEF by the common gain.", "source": { "url": "https://benedict.dev/optimization-arena-learnings", "quote": "skewing based on information from the arbs" }, "search": { "method": "Grid with fixed opening probes and seed-87 shuffled remaining Cartesian grid", "rng_seed": 87, "budget_seconds": 1500, "elapsed_seconds": 1647.9599876850843, "evaluations": 15, "blocks": [ [ 990000, 990063 ], [ 990064, 990127 ] ], "aux_evaluations": 2, "n_per_evaluation": 64, "pairing": "All candidates and RS2 separately against VanillaStrategy, common simulation seeds; RS2 baseline cached.", "primary_grid": { "a": [ 0, 0.25, 0.5, 0.75, 1 ], "k": [ 0.5, 1, 2, 4, 8 ], "gain": [ 0.5, 1, 2, 4, 8, 16 ] }, "extension_grid": { "a": [ 0 ], "k": [ 8 ], "gain": [ 32, 64, 128 ], "seeds": [ 990064, 990127 ], "shared_deadline": true }, "best": { "params": { "a": 0.0, "k": 8.0, "gain": 64.0 }, "paired": { "n": 64, "mean_diff": 0.4646256499039616, "se": 0.12239828142105712, "worst": [ { "seed": 990073, "d": -1.8005232798363409 }, { "seed": 990112, "d": -1.6016566751960681 }, { "seed": 990064, "d": -1.585412612638379 }, { "seed": 990074, "d": -1.4559553986563856 }, { "seed": 990070, "d": -0.7753726530073664 } ] }, "valid": true, "seeds": [ 990064, 990127 ], "gas": { "max_ok": 200184, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, "top_three": [ { "params": { "a": 0.0, "k": 8.0, "gain": 64.0 }, "paired": { "n": 64, "mean_diff": 0.4646256499039616, "se": 0.12239828142105712, "worst": [ { "seed": 990073, "d": -1.8005232798363409 }, { "seed": 990112, "d": -1.6016566751960681 }, { "seed": 990064, "d": -1.585412612638379 }, { "seed": 990074, "d": -1.4559553986563856 }, { "seed": 990070, "d": -0.7753726530073664 } ] }, "valid": true, "seeds": [ 990064, 990127 ], "gas": { "max_ok": 200184, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 16.0 }, "paired": { "n": 64, "mean_diff": 0.20572333023335787, "se": 0.04198670623414535, "worst": [ { "seed": 990057, "d": -0.5386519797193614 }, { "seed": 990062, "d": -0.3650998658443996 }, { "seed": 990026, "d": -0.3430611609430798 }, { "seed": 990036, "d": -0.2830679974708801 }, { "seed": 990049, "d": -0.2629648997581171 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199799, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 1.0, "k": 8.0, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.1199160893186928, "se": 0.04248684948862137, "worst": [ { "seed": 990016, "d": -0.7312874408229391 }, { "seed": 990049, "d": -0.3801792262786421 }, { "seed": 990047, "d": -0.32528615605815503 }, { "seed": 990031, "d": -0.3090575590271101 }, { "seed": 990058, "d": -0.27895885556739586 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199668, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } } ], "evaluations_log": [ { "params": { "a": 0.0, "k": 2.0, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.020478309304603926, "se": 0.033053930594608545, "worst": [ { "seed": 990062, "d": -0.7894210114352518 }, { "seed": 990032, "d": -0.5263294505159593 }, { "seed": 990056, "d": -0.4251303804400095 }, { "seed": 990009, "d": -0.39090027776478564 }, { "seed": 990057, "d": -0.33514547793032534 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199818, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.03591661382292699, "se": 0.033095813783630953, "worst": [ { "seed": 990062, "d": -0.7765986200423072 }, { "seed": 990032, "d": -0.48934199231371167 }, { "seed": 990056, "d": -0.40678999400665816 }, { "seed": 990057, "d": -0.3379883097952643 }, { "seed": 990009, "d": -0.3203200253211662 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199807, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.5, "k": 2.0, "gain": 2.0 }, "paired": { "n": 64, "mean_diff": 0.03865055533739259, "se": 0.021706508530675427, "worst": [ { "seed": 990062, "d": -0.5113083556606739 }, { "seed": 990024, "d": -0.20778132811153682 }, { "seed": 990040, "d": -0.20026226619268073 }, { "seed": 990028, "d": -0.17585007948048315 }, { "seed": 990018, "d": -0.16350688003649338 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199860, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.25, "k": 4.0, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.09328524695105678, "se": 0.024976717851500022, "worst": [ { "seed": 990062, "d": -0.37798648802669277 }, { "seed": 990032, "d": -0.2961937798137342 }, { "seed": 990040, "d": -0.2613222395976891 }, { "seed": 990024, "d": -0.1911907282772063 }, { "seed": 990057, "d": -0.1910908777001623 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199851, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 1.0, "k": 8.0, "gain": 1.0 }, "paired": { "n": 64, "mean_diff": 0.03392256073528532, "se": 0.012645782304049093, "worst": [ { "seed": 990062, "d": -0.29257476185949827 }, { "seed": 990040, "d": -0.25181465114422963 }, { "seed": 990024, "d": -0.17512744391012802 }, { "seed": 990018, "d": -0.08030834777247264 }, { "seed": 990005, "d": -0.07245096808605922 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199656, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 0.5, "gain": 8.0 }, "paired": { "n": 64, "mean_diff": -0.015013807181655459, "se": 0.030946513739647755, "worst": [ { "seed": 990062, "d": -0.8630627867362932 }, { "seed": 990056, "d": -0.4893954616896963 }, { "seed": 990009, "d": -0.4778295893365794 }, { "seed": 990032, "d": -0.4588061654641251 }, { "seed": 990057, "d": -0.325200399101675 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199834, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.75, "k": 4.0, "gain": 2.0 }, "paired": { "n": 64, "mean_diff": 0.07353804988416535, "se": 0.023111282677154933, "worst": [ { "seed": 990062, "d": -0.2820717006863447 }, { "seed": 990055, "d": -0.25843672796258943 }, { "seed": 990007, "d": -0.22006173004052698 }, { "seed": 990005, "d": -0.18195530224045342 }, { "seed": 990024, "d": -0.17847256899403874 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199846, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 16.0 }, "paired": { "n": 64, "mean_diff": 0.20572333023335787, "se": 0.04198670623414535, "worst": [ { "seed": 990057, "d": -0.5386519797193614 }, { "seed": 990062, "d": -0.3650998658443996 }, { "seed": 990026, "d": -0.3430611609430798 }, { "seed": 990036, "d": -0.2830679974708801 }, { "seed": 990049, "d": -0.2629648997581171 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199799, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.5, "k": 1.0, "gain": 8.0 }, "paired": { "n": 64, "mean_diff": 0.11755876017377354, "se": 0.028487789094229728, "worst": [ { "seed": 990026, "d": -0.4560168190674858 }, { "seed": 990049, "d": -0.392061704937646 }, { "seed": 990062, "d": -0.33486237455514356 }, { "seed": 990033, "d": -0.18323203661850584 }, { "seed": 990007, "d": -0.18137231521166086 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199900, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 1.0, "k": 0.5, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.02831384991732655, "se": 0.02167826683474341, "worst": [ { "seed": 990062, "d": -0.5409384636652703 }, { "seed": 990011, "d": -0.24090966194080465 }, { "seed": 990033, "d": -0.22397626000861237 }, { "seed": 990018, "d": -0.2055143156821373 }, { "seed": 990056, "d": -0.202823070538102 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199675, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 1.0, "k": 8.0, "gain": 4.0 }, "paired": { "n": 64, "mean_diff": 0.1199160893186928, "se": 0.04248684948862137, "worst": [ { "seed": 990016, "d": -0.7312874408229391 }, { "seed": 990049, "d": -0.3801792262786421 }, { "seed": 990047, "d": -0.32528615605815503 }, { "seed": 990031, "d": -0.3090575590271101 }, { "seed": 990058, "d": -0.27895885556739586 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199668, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.5, "k": 0.5, "gain": 0.5 }, "paired": { "n": 64, "mean_diff": -0.0420425521121528, "se": 0.024629643941976895, "worst": [ { "seed": 990062, "d": -0.6724339598668507 }, { "seed": 990040, "d": -0.32895861508347934 }, { "seed": 990023, "d": -0.31896503753443994 }, { "seed": 990020, "d": -0.2963935259684263 }, { "seed": 990018, "d": -0.2833598844949847 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199885, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 0.5, "gain": 2.0 }, "paired": { "n": 64, "mean_diff": -0.051445622455981166, "se": 0.028302391182227948, "worst": [ { "seed": 990062, "d": -0.7825722594073454 }, { "seed": 990056, "d": -0.5546478933649723 }, { "seed": 990018, "d": -0.41531652660057716 }, { "seed": 990040, "d": -0.33043200071625733 }, { "seed": 990023, "d": -0.32390761621161346 } ] }, "valid": true, "seeds": [ 990000, 990063 ], "gas": { "max_ok": 199830, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 64.0 }, "paired": { "n": 64, "mean_diff": 0.4646256499039616, "se": 0.12239828142105712, "worst": [ { "seed": 990073, "d": -1.8005232798363409 }, { "seed": 990112, "d": -1.6016566751960681 }, { "seed": 990064, "d": -1.585412612638379 }, { "seed": 990074, "d": -1.4559553986563856 }, { "seed": 990070, "d": -0.7753726530073664 } ] }, "valid": true, "seeds": [ 990064, 990127 ], "gas": { "max_ok": 200184, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 128.0 }, "paired": { "n": 64, "mean_diff": -0.5426124044747889, "se": 0.22474015417795293, "worst": [ { "seed": 990071, "d": -5.268258496567569 }, { "seed": 990112, "d": -4.209526349947851 }, { "seed": 990073, "d": -3.3057261254899686 }, { "seed": 990070, "d": -3.152395897277188 }, { "seed": 990074, "d": -3.0507400473557595 } ] }, "valid": true, "seeds": [ 990064, 990127 ], "gas": { "max_ok": 200253, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } } ] }, "recheck": { "seeds": [ 993000, 993255 ], "n_each": 256, "results": [ { "params": { "a": 0.0, "k": 8.0, "gain": 64.0 }, "paired": { "n": 256, "mean_diff": 0.3206445025592368, "se": 0.050455137650273256, "worst": [ { "seed": 993146, "d": -2.323908292238116 }, { "seed": 993228, "d": -2.1809256517115045 }, { "seed": 993225, "d": -1.825940339318663 }, { "seed": 993105, "d": -1.5296565697427127 }, { "seed": 993163, "d": -1.3680159006598842 } ] }, "valid": true, "gas": { "max_ok": 200639, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 0.0, "k": 8.0, "gain": 16.0 }, "paired": { "n": 256, "mean_diff": 0.26088588173950256, "se": 0.02719992692578005, "worst": [ { "seed": 993105, "d": -1.9596858934139618 }, { "seed": 993146, "d": -1.114604484741676 }, { "seed": 993228, "d": -0.9283669663932415 }, { "seed": 993075, "d": -0.7614141157187078 }, { "seed": 993212, "d": -0.6131034045986326 } ] }, "valid": true, "gas": { "max_ok": 200639, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, { "params": { "a": 1.0, "k": 8.0, "gain": 4.0 }, "paired": { "n": 256, "mean_diff": 0.13464950758224425, "se": 0.0211478484310594, "worst": [ { "seed": 993017, "d": -2.373523135679079 }, { "seed": 993097, "d": -0.8873666218792664 }, { "seed": 993029, "d": -0.7892513107047989 }, { "seed": 993117, "d": -0.6984268746199405 }, { "seed": 993147, "d": -0.5042760003401554 } ] }, "valid": true, "gas": { "max_ok": 200488, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } } ], "selection": "Largest valid paired mean on 993000..993255; no held-out selection" }, "held_out": { "reference": "RS2", "seeds": [ 994000, 994511 ], "n": 512, "mean_diff": 0.3053162324788391, "se": 0.03415373327286404, "worst": [ { "seed": 994083, "d": -2.1953896726931816 }, { "seed": 994128, "d": -2.0751560221143563 }, { "seed": 994433, "d": -2.0194745551781352 }, { "seed": 994114, "d": -1.883641621756965 }, { "seed": 994245, "d": -1.8276814329824447 } ], "valid": true, "candidate_mean": 525.1655694365768, "rs2_mean": 524.860253204098, "frozen_before_held_out": true }, "retail_edge_delta": { "mean": -1.8896580209702858, "se": 0.03699503084968884 }, "arb_edge_delta": { "mean": 2.194974253449122, "se": 0.028873468704483488 }, "gas": { "max_ok": 200640, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0, "scope": "Frozen candidate: search, recheck, and held-out; errors counted for both roles.", "held_out": { "max_ok": 200640, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, "rs2_held_out": { "max_ok": 200269, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, "held_out_raw_counters": [ { "role": "Baseline", "callback": "afterInitialize", "calls": 512, "ok": 512, "max_ok_gas": 21796, "sum_ok_gas": 11159552, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, { "role": "Baseline", "callback": "afterSwap", "calls": 5492165, "ok": 5492165, "max_ok_gas": 22592, "sum_ok_gas": 123919687000, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, { "role": "Baseline", "callback": "getName", "calls": 512, "ok": 512, "max_ok_gas": 21526, "sum_ok_gas": 11021312, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, { "role": "Submission", "callback": "afterInitialize", "calls": 512, "ok": 512, "max_ok_gas": 243099, "sum_ok_gas": 124466688, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, { "role": "Submission", "callback": "afterSwap", "calls": 5253625, "ok": 5253625, "max_ok_gas": 200640, "sum_ok_gas": 618350710004, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 }, { "role": "Submission", "callback": "getName", "calls": 512, "ok": 512, "max_ok_gas": 21607, "sum_ok_gas": 11062784, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } ], "search_all_evaluations_max_ok": 200253, "search_all_evaluations_oog": 0 }, "validation": { "neutral": { "params": { "a": 1, "k": null, "gain": 1 }, "seeds": [ 994600, 994631 ], "n": 32, "mean_diff": 0.0, "se": 0.0, "worst": [ { "seed": 994600, "d": 0.0 }, { "seed": 994601, "d": 0.0 }, { "seed": 994602, "d": 0.0 }, { "seed": 994603, "d": 0.0 }, { "seed": 994604, "d": 0.0 } ], "edges_identical": true, "valid": true, "gas": { "max_ok": 197265, "init_max_ok": 243099, "oog": 0, "revert": 0, "other_halt": 0, "tx_error": 0, "bad_return": 0 } }, "CH": { "seeds": [ 0, 999 ], "n": 1000, "mean": 525.5258821780834, "expected_mean": 525.5258821780834, "absolute_error": 0.0 }, "initialization_body_unchanged": true, "decomposition_reconciliation_max_abs": 1.1368683772161603e-13 }, "generator_source": "def generate(base,a=1.,k=None,gain=1.):\n s=base\n new='uint256 skewRatio = tradeRatio;'\n if k is not None:\n new+=f'\\n uint256 cleanSize = uint80(slots[15] >> 160);\\n if (cleanSize == 0) cleanSize = 2000000000000000;\\n uint256 skewCap = wmul(cleanSize, {int(round(k*1e18))});\\n if (skewRatio > skewCap) skewRatio = skewCap;'\n new+='\\n uint256 push = skewRatio * DIR_IMPACT_MULT;'\n s=s.replace('uint256 push = tradeRatio * DIR_IMPACT_MULT;',new)\n if a!=1:\n s=s.replace('if (push > WAD / 4) push = WAD / 4;',f'if (push > WAD / 4) push = WAD / 4;\\n push = wmul(push, {int(round(a*1e18))} + wmul({int(round((1-a)*1e18))}, arbProbability));')\n if gain!=1:\n s=s.replace('uint256 constant DIR_COEF = 20 * BPS;',f'uint256 constant DIR_COEF = {int(round(20*1e14*gain))};')\n s=s.replace('uint256 constant DIR_TOX_COEF = 100 * BPS;',f'uint256 constant DIR_TOX_COEF = {int(round(100*1e14*gain))};')\n return s\n", "generator_base_url": "https://api.imd.fun/artifacts/19f2ec857df536e8ab62ab1da89ec6623332521ce46849f15bccff402c63e1e5", "generator_base_sha256": "f24b6ca198b744c380842c3a17964a6dc21f311bb04984b26733afa3fee8eaf2", "notes": [ "Measured result; no leaderboard submission was made.", "Search used paired 64-seed blocks within the requested range and a shared 25-minute dispatch budget; the last dispatched simulations could finish after that budget. All selection was complete before the held-out block.", "The cleaned size cap reads the previous packed meanSize from slot 15 before the current trade updates it. The original activity, size, toxicity, and stale-price mechanisms are retained.", "The generator takes the exact RS2 code as its base argument; neutral means a=1, k=None, gain=1. Gain scales the two direction-state coefficients, not the separate stale-price shift.", "Retail and arbitrage edge deltas are reconstructed using the requested harness decomposition with initial fee 0.0004; their seedwise sum reconciles to total paired edge.", "Pinned simulator wheel sha256 aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a; checkout 6b6921f8d463314aa7c96234e1be25a25245f704; Solidity 0.8.24; run_batch threads=8; gas counters reset per 20-seed chunk." ] }