{"delta":-5.262308226099058,"interpretation":"Oracle-assisted simulator ceiling experiment only: strategy reads the current true price supplied by the patched engine after each swap. No leaderboard result is claimed.","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 = 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; slots[11] = 0; slots[12] = 0;\n        slots[20] = 1407375012403289420;\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 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[11] = pHat; slots[12] = pImplied >= pHat ? 1 : 2; }\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 (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        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 p;\n        assembly { p := calldataload(196) }\n        require(p > 0, \"oracle price missing\");\n        uint256 g = wdiv(absDiff(spot, p), p);\n        uint256 exposed = clampFee(wmul((slots[20] & 65535) * 1e14, g) + ((slots[20] >> 16) & 65535) * 1e14);\n        uint256 reduction = wmul(((slots[20] >> 48) & 65535) * 1e14, g);\n        uint256 c = ((slots[20] >> 32) & 65535) * 1e14;\n        uint256 other = clampFee(c > reduction ? c - reduction : 0);\n        uint256 bidFee = spot >= p ? exposed : other;\n        uint256 askFee = spot >= p ? other : exposed;\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","simulator_diff":"diff --git a/amm_sim_rs/src/amm/cfmm.rs b/amm_sim_rs/src/amm/cfmm.rs\nindex 02e6645..1712a91 100644\n--- a/amm_sim_rs/src/amm/cfmm.rs\n+++ b/amm_sim_rs/src/amm/cfmm.rs\n@@ -42,6 +42,7 @@ pub struct CFMM {\n     pub name: String,\n     /// EVM strategy for fee decisions\n     strategy: EVMStrategy,\n+    pub fair_price: f64,\n     /// Current X reserves\n     reserve_x: f64,\n     /// Current Y reserves\n@@ -63,6 +64,7 @@ impl CFMM {\n         Self {\n             name,\n             strategy,\n+            fair_price: 0.0,\n             reserve_x,\n             reserve_y,\n             current_fees: FeeQuote::symmetric(Wad::from_bps(30)),\n@@ -291,7 +293,7 @@ impl CFMM {\n \n     /// Update fees from strategy after a trade.\n     fn update_fees(&mut self, trade_info: &TradeInfo) {\n-        if let Ok((bid_fee, ask_fee)) = self.strategy.after_swap(trade_info) {\n+        if let Ok((bid_fee, ask_fee)) = self.strategy.after_swap(trade_info, self.fair_price) {\n             self.current_fees = FeeQuote::new(bid_fee.clamp_fee(), ask_fee.clamp_fee());\n         }\n         // On error, keep current fees\ndiff --git a/amm_sim_rs/src/evm/strategy.rs b/amm_sim_rs/src/evm/strategy.rs\nindex 1d06af1..147d868 100644\n--- a/amm_sim_rs/src/evm/strategy.rs\n+++ b/amm_sim_rs/src/evm/strategy.rs\n@@ -176,12 +176,14 @@ impl EVMStrategy {\n     ///\n     /// Returns (bid_fee, ask_fee) in WAD.\n     #[inline]\n-    pub fn after_swap(&mut self, trade: &TradeInfo) -> Result<(Wad, Wad), EVMError> {\n+    pub fn after_swap(&mut self, trade: &TradeInfo, fair_price: f64) -> Result<(Wad, Wad), EVMError> {\n         // Encode trade info into pre-allocated buffer\n         trade.encode_calldata(&mut self.trade_calldata);\n \n         // Copy calldata to avoid borrow conflict\n-        let calldata = self.trade_calldata;\n+        let mut calldata = [0u8; 228];\n+        calldata[..196].copy_from_slice(&self.trade_calldata);\n+        calldata[196..].copy_from_slice(&U256::from((fair_price * 1e18).floor() as u128).to_be_bytes::<32>());\n         let result = self.call(&calldata, GAS_LIMIT_TRADE)?;\n \n         decode_fee_pair(&result)\ndiff --git a/amm_sim_rs/src/simulation/engine.rs b/amm_sim_rs/src/simulation/engine.rs\nindex 6834c43..bb6bec8 100644\n--- a/amm_sim_rs/src/simulation/engine.rs\n+++ b/amm_sim_rs/src/simulation/engine.rs\n@@ -113,6 +113,9 @@ impl SimulationEngine {\n         edges.insert(submission_name.clone(), 0.0);\n         edges.insert(baseline_name.clone(), 0.0);\n \n+        let mut arb_edges = edges.clone();\n+        let mut retail_edges = edges.clone();\n+\n         // Run simulation steps\n         let mut steps = Vec::with_capacity(self.config.n_steps as usize);\n \n@@ -136,11 +139,13 @@ impl SimulationEngine {\n         for t in 0..self.config.n_steps {\n             // 1. Generate new fair price\n             let fair_price = price_process.step();\n+            for amm in amms.iter_mut() { amm.fair_price = fair_price; }\n \n             // 2. Arbitrageur extracts profit from each AMM\n             for amm in amms.iter_mut() {\n                 if let Some(arb_result) = arbitrageur.execute_arb(amm, fair_price, t as u64) {\n                     *arb_volume_y.get_mut(&arb_result.amm_name).unwrap() += arb_result.amount_y;\n+                    *arb_edges.get_mut(&arb_result.amm_name).unwrap() -= arb_result.profit;\n                     let entry = edges.entry(arb_result.amm_name).or_insert(0.0);\n                     // AMM edge is the negative of arbitrageur profit at true price\n                     *entry += -arb_result.profit;\n@@ -157,6 +162,7 @@ impl SimulationEngine {\n                 } else {\n                     trade.amount_y - trade.amount_x * fair_price\n                 };\n+                *retail_edges.get_mut(&trade.amm_name).unwrap() += trade_edge;\n                 let entry = edges.entry(trade.amm_name).or_insert(0.0);\n                 *entry += trade_edge;\n             }\n@@ -215,6 +221,8 @@ impl SimulationEngine {\n             arb_volume_y,\n             retail_volume_y,\n             average_fees,\n+            arb_edges,\n+            retail_edges,\n         })\n     }\n }\ndiff --git a/amm_sim_rs/src/types/result.rs b/amm_sim_rs/src/types/result.rs\nindex 0257335..0cf97da 100644\n--- a/amm_sim_rs/src/types/result.rs\n+++ b/amm_sim_rs/src/types/result.rs\n@@ -80,6 +80,10 @@ pub struct LightweightSimResult {\n \n     /// Average fees (bid, ask) by strategy name over the simulation\n     #[pyo3(get)]\n+    pub arb_edges: HashMap<String, f64>,\n+    #[pyo3(get)]\n+    pub retail_edges: HashMap<String, f64>,\n+    #[pyo3(get)]\n     pub average_fees: HashMap<String, (f64, f64)>,\n }\n \n","sha256":"d8c31796df2b4d31812702b83a7aef9940e8df84d91e40d298dca5e5f7220a9f","reference":{"name":"NP2","sha256":"51f1c1a9d4999ee460eb8bbc66880da8074b173399a4f5d71f96671482e18ac0","construction":"TWO plus NP Interior retail routing block, as specified in the assignment.","sources":[0,1]},"methodology":{"simulator_commit":"6b6921f8d463314aa7c96234e1be25a25245f704","source_indices":[2,3,4,5,6,7,8],"opponent":"Compiled contracts/src/VanillaStrategy.sol; each arm run separately against Vanilla.","batch_size":20,"workers":4,"config":"For each seed s: numpy.default_rng(s) draws size uniform(19,21), then rate uniform(.6,1), then sigma uniform(.000882,.001008); build_config(seed=s, gbm_sigma=sigma, retail_arrival_rate=rate, retail_mean_size=size). Price RNG seed=s; retail RNG seed=s+1 in pinned simulator.","paired_definition":"candidate edges[submission] minus NP2 edges[submission] per seed; sample standard deviation ddof=1 divided by sqrt(n).","oracle":"The engine sets CFMM.fair_price immediately after price_process.step(), before arbitrage and retail; strategy appends floor(fair_price*1e18) as big-endian U256 at calldata byte 196. NP2 source is unchanged.","initial_fees":"NP2 afterInitialize fees retained at 4 bps. Only post-state-update fee logic is replaced.","parameters":"One packed storage word holds four 16-bit values (a/1e-4, b in bps, c in bps, d/1e-4). Grid template patches its sole initialization literal; no runtime instructions change. Final literal source compiled normally and matched patched template exactly on seeds 11000..11019.","fee_stats":"Arithmetic mean over seeds of simulator average_fees[submission], itself mean of post-retail fee quotes over all steps; fee fraction units, not bps or volume weighted.","split":"Arbitrage edge sums -arb_result.profit; retail sums the existing true-price trade_edge. Separate accumulators added without changing edges arithmetic."},"calibration":{"CH":{"sha256":"6dd68f77a70900319460215374143dbd5d924198450a46d9f5f91f6b1e3d35c3","n":1000,"seeds":[0,999],"mean_edge":525.5258821780834,"required":525.525882178,"passed":true},"NP2":{"n":1000,"seeds":[0,999],"mean_edge":526.1155722459862,"brief_approximate":526.1156,"passed":true},"note":"Both calibration scores measured with the oracle-calldata and split-accounting patch active; neither strategy reads appended calldata."},"tuning":{"grid":{"a":[0.5,0.75,0.9,1,1.1],"b_bps":[10,15,20,25,30,35,40],"c_bps":[10,15,20,25,30,35,40],"d":[0,0.5,1]},"stage1":{"n_per_tuple":20,"seeds":[10000,10019],"tuples":735,"order":"itertools.product(a,b_bps,c_bps,d), last axis fastest; score_pairs are [mean_diff,se], rounded to 6 decimal 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confirmation only, seeds 2710000..2711999; no tuning or selection used these seeds.","repaired_issue":"Initial tuning harness stored parameters in four extra slots and exceeded afterInitialize gas. Replaced with one packed word before measuring the grid; gas limits unchanged."},"paired":{"n":2000,"mean_diff":-5.262308226099058,"se":0.06504516455654068,"worst":[{"seed":2711840,"diff":-23.506285771174362,"candidate_edge":787.1027813052903,"np2_edge":810.6090670764646},{"seed":2710891,"diff":-17.576535221796803,"candidate_edge":756.3975436223868,"np2_edge":773.9740788441836},{"seed":2710427,"diff":-16.750760443733952,"candidate_edge":743.0591737343568,"np2_edge":759.8099341780908},{"seed":2711212,"diff":-16.380332215771432,"candidate_edge":757.9799446584,"np2_edge":774.3602768741714},{"seed":2711440,"diff":-15.664495489577575,"candidate_edge":742.0232355832678,"np2_edge":757.6877310728454},{"seed":2711498,"diff":-15.15553363439642,"candidate_edge":668.0559599497632,"np2_edge":683.2114935841596},{"seed":2710263,"diff":-14.860650392538446,"candidate_edge":641.4190390174836,"np2_edge":656.279689410022},{"seed":2710139,"diff":-14.57115333285094,"candidate_edge":706.8124349232992,"np2_edge":721.3835882561501},{"seed":2710210,"diff":-14.248847261829383,"candidate_edge":669.722215332849,"np2_edge":683.9710625946784},{"seed":2710630,"diff":-14.16330712063359,"candidate_edge":606.0898065943836,"np2_edge":620.2531137150172}],"candidate_mean":521.4016452226265,"np2_mean":526.6639534487255},"split":{"arb":{"mean_diff":-0.48424107663925214,"se":0.058245435571098514},"retail":{"mean_diff":-4.778067149459827,"se":0.04091404940532672}},"fee_stats":{"bid":0.003361748816020507,"ask":0.0032603222673243774,"np2_bid":0.0036414205800230364,"np2_ask":0.003540393661775732},"split_sum_error":5.9117155615240335e-12,"blocked":null,"next":"Do not promote this static oracle fee rule over NP2. Untested next hypothesis: retain NP2 adaptive mid-fee and replace only directional skew with oracle information, to isolate direction information from loss of base-fee adaptation.","reproduction":{"experiment.py":"import json,hashlib,itertools,time\nfrom pathlib import Path\nimport numpy as np\nimport amm_sim_rs\nfrom amm_competition.evm.compiler import SolidityCompiler\nfrom amm_competition.competition.config import build_config\nROOT=Path(__file__).resolve().parents[2]\nOUT=Path(__file__).resolve().parent\ncomp=SolidityCompiler()\ndef compile(s,name=\"Strategy\"):\n r=comp.compile(s,contract_name=name);assert r.success,r.errors\n return bytes(r.bytecode)\nvan=compile(Path('contracts/src/VanillaStrategy.sol').read_text(),'VanillaStrategy')\nnp2=(ROOT/'NP2.sol').read_text()\nbase=compile(np2)\ndef configs(seeds):\n out=[]\n for s in seeds:\n  rng=np.random.default_rng(s);size=rng.uniform(19,21);rate=rng.uniform(.6,1);sigma=rng.uniform(.000882,.001008)\n  out.append(build_config(seed=s,gbm_sigma=sigma,retail_arrival_rate=rate,retail_mean_size=size))\n return out\ndef run(b,seeds):\n rows=[]\n for i in range(0,len(seeds),20):\n  res=amm_sim_rs.run_batch(list(b),list(van),configs(seeds[i:i+20]),4)\n  for r in res.results:\n   rows.append([r.seed,r.edges['submission'],r.arb_edges['submission'],r.retail_edges['submission'],*r.average_fees['submission']])\n return np.array(rows)\ndef save(name,rows): np.save(OUT/(name+'.npy'),rows)\nif __name__=='__main__':\n t=time.time()\n ch=compile((ROOT/'CH.sol').read_text())\n for name,b in [('CH',ch),('NP2',base)]:\n  rows=run(b,list(range(1000)));save(name,rows);mean=rows[:,1].mean();print(name,mean,'elapsed',time.time()-t,flush=True)\n  if name=='CH':assert abs(mean-525.525882178)<1e-8,mean\n","tune.py":"from experiment import *\n# The sentinels are only initialization values in slots 20..23; every grid\n# evaluation uses identical runtime instructions with four different values.\nmarkers=['0x'+'1234'*16]\ndef source(params):\n packed=params[0] if len(params)==1 else str(sum((int(v)//10**14)<<(16*i) for i,v in enumerate(params)))\n s=np2.replace('        return (BASE_FEE, BASE_FEE);',f'        slots[20] = {packed};\\n'+'        return (BASE_FEE, BASE_FEE);',1)\n start=s.index('        uint256 flowSize =');end=s.index('        slots[0] = bidFee;',start)\n s=s[:start]+'''        uint256 p;\n        assembly { p := calldataload(196) }\n        require(p > 0, \"oracle price missing\");\n        uint256 g = wdiv(absDiff(spot, p), p);\n        uint256 exposed = clampFee(wmul((slots[20] & 65535) * 1e14, g) + ((slots[20] >> 16) & 65535) * 1e14);\n        uint256 reduction = wmul(((slots[20] >> 48) & 65535) * 1e14, g);\n        uint256 c = ((slots[20] >> 32) & 65535) * 1e14;\n        uint256 other = clampFee(c > reduction ? c - reduction : 0);\n        uint256 bidFee = spot >= p ? exposed : other;\n        uint256 askFee = spot >= p ? other : exposed;\n\n'''+s[end:]\n return s\nif __name__=='__main__':\n template=compile(source(markers));mb=[bytes.fromhex(x[2:]) for x in markers]\n print('marker_counts',[template.count(x) for x in mb],flush=True)\n assert all(template.count(x)==1 for x in mb)\n (OUT/'oracle_template.sol').write_text(source(markers))\n def patched(params):\n  b=template\n  packed=sum((int(v)//10**14)<<(16*i) for i,v in enumerate(params))\n  b=b.replace(mb[0],packed.to_bytes(32,'big'))\n  return b\n seeds=list(range(10000,10020));ref=run(base,seeds);save('tune_ref20',ref)\n grid=list(itertools.product([.5,.75,.9,1,1.1],range(10,41,5),range(10,41,5),[0,.5,1]))\n records=[];t=time.time()\n for i,(a,b,c,d) in enumerate(grid):\n  params=[round(a*1e18),b*10**14,c*10**14,round(d*1e18)]\n  rows=run(patched(params),seeds);diff=rows[:,1]-ref[:,1]\n  records.append(dict(a=a,b=b,c=c,d=d,n=len(seeds),mean_diff=float(diff.mean()),se=float(diff.std(ddof=1)/len(diff)**.5)))\n  if (i+1)%15==0:\n   (OUT/'grid.json').write_text(json.dumps(records));print('grid',i+1,'/',len(grid),'best',max(records,key=lambda x:x['mean_diff']),'elapsed',time.time()-t,flush=True)\n (OUT/'grid.json').write_text(json.dumps(records))\n top=sorted(records,key=lambda x:x['mean_diff'],reverse=True)[:12]\n seeds=list(range(10020,10220));ref=run(base,seeds);save('tune_ref200',ref)\n for j,r in enumerate(top):\n  params=[round(r['a']*1e18),r['b']*10**14,r['c']*10**14,round(r['d']*1e18)]\n  rows=run(patched(params),seeds);save('top'+str(j),rows);diff=rows[:,1]-ref[:,1];r['stage2']=dict(n=len(seeds),mean_diff=float(diff.mean()),se=float(diff.std(ddof=1)/len(diff)**.5))\n  (OUT/'top.json').write_text(json.dumps(top));print('top',j,r,flush=True)\n selected=max(top,key=lambda r:r['stage2']['mean_diff']);params=[round(selected['a']*1e18),selected['b']*10**14,selected['c']*10**14,round(selected['d']*1e18)]\n code=source([str(v) for v in params]);(OUT/'selected.sol').write_text(code)\n compiled=compile(code)\n # Verify source compilation and patched template have identical behavior.\n r1=run(compiled,list(range(11000,11020)));r2=run(patched(params),list(range(11000,11020)));assert np.array_equal(r1,r2),np.max(abs(r1-r2))\n (OUT/'frozen.json').write_text(json.dumps({'selected':selected,'sha256':hashlib.sha256(code.encode()).hexdigest(),'equivalence_seeds':[11000,11019],'equivalence_exact':True}))\n print('FROZEN',selected,flush=True)\n","confirm.py":"from experiment import *\nif __name__=='__main__':\n frozen=json.loads((OUT/'frozen.json').read_text())\n source=(OUT/'selected.sol').read_text();assert hashlib.sha256(source.encode()).hexdigest()==frozen['sha256']\n cand=compile(source)\n assert not (OUT/'confirmation_started.json').exists(),'Do not reuse holdout'\n (OUT/'confirmation_started.json').write_text(json.dumps({'seed_start':2710000,'n':2000,'sha256':frozen['sha256']}))\n a=[];b=[];t=time.time()\n for start in range(2710000,2712000,20):\n  seeds=list(range(start,start+20));a.extend(run(cand,seeds));b.extend(run(base,seeds))\n  if len(a)%100==0:print('confirmed',len(a),'elapsed',time.time()-t,flush=True)\n a=np.array(a);b=np.array(b);save('confirm_candidate',a);save('confirm_np2',b)\n d=a[:,1]-b[:,1];order=np.argsort(d)[:10]\n def stats(x):return dict(mean_diff=float(x.mean()),se=float(x.std(ddof=1)/len(x)**.5))\n report=dict(paired=dict(n=len(d),**stats(d),worst=[dict(seed=int(a[i,0]),diff=float(d[i]),candidate_edge=float(a[i,1]),np2_edge=float(b[i,1])) for i in order],candidate_mean=float(a[:,1].mean()),np2_mean=float(b[:,1].mean())),split=dict(arb=stats(a[:,2]-b[:,2]),retail=stats(a[:,3]-b[:,3])),fee_stats=dict(bid=float(a[:,4].mean()),ask=float(a[:,5].mean()),np2_bid=float(b[:,4].mean()),np2_ask=float(b[:,5].mean())),split_sum_error=float(abs((a[:,2]+a[:,3])-a[:,1]).max()))\n (OUT/'confirmation.json').write_text(json.dumps(report));print(json.dumps(report),flush=True)\n"},"conclusion":{"beats_NP2":false,"clears_top10_gain_target":false,"clears_first_place_gain_target":false,"scope":"Inference applies to this specified static fee family and tested parameter grid; it is not an optimal-control bound on every oracle strategy."},"grid_best_by_a":[{"a":0.5,"b":40,"c":30,"d":0.5,"n":20,"mean_diff":-22.50579461343181,"se":0.9260436772948621},{"a":0.75,"b":15,"c":30,"d":0.5,"n":20,"mean_diff":-5.897109465523485,"se":0.4998576641128589},{"a":0.9,"b":10,"c":30,"d":0.5,"n":20,"mean_diff":-11.296517362239646,"se":0.63656675094221},{"a":1,"b":10,"c":35,"d":0.5,"n":20,"mean_diff":-27.87003126816628,"se":1.3885024677116464},{"a":1.1,"b":10,"c":35,"d":0.5,"n":20,"mean_diff":-46.84703364092656,"se":3.117793440869923}],"evidence_hashes":{"CH.npy":"393ec67bc72b4fdb7ec1e5a3554e3f3ad893735041b8ffb303d69fd99468d1e3","NP2.npy":"de9f6c47ca44354462de2c9e2925c731314e35218b5c02240990d8affdcc73a8","confirm_candidate.npy":"b4bd64802f33752c04604f1f8b6cc78fb3c2272588009ae7c62184450a6b43e5","confirm_np2.npy":"40b19f9a3ce22d5963f882f0f70375838ac19d29b1c9e55f80c0d509ef8019a9","grid.json":"ed8f352c37257bc8b07667b3da34068dec4a44608dc253c20ac096de63c4509d","top.json":"d8298576a8776a80b0b59f3d595109514e07e463f75804e8ed316a25f83da862"}}