{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/5839483d4df69854030fd68b224659b379af881cd229df40a8bab825c2fa7db1",
      "quote": "# stack-b: first-print mixture and silence uncertainty\n\nFrozen candidate: `scratch/Strategy.sol`; SHA-256 `218426004abed3b6cb69f4ef133fea8e4789ddbeae37bd11e94e5ffc5f2a77cb`.\n\nFresh paired confirmation: **+0.477030867 \u00b1 0.017285879 SE** versus NP2, n=2,000, seeds 2850000\u20132851999. The measured gain supports a modest promotion; it does not reach the requested +5.8/+9.6 targets.\n\n## Method and provenance\n\nSimulator: [pinned upstream](https://github.c"
    },
    {
      "url": "https://api.imd.fun/artifacts/528a6da78583c6142644a552c86670f9d25c20e39e92f4de44deae05ddc8cecd",
      "quote": "{\n \"approach\": \"Second-print reclassification within a step: revert half (opposite-direction second print moves pHat back toward pre-step value by u) and same-direction half (raise second-print alpha from 0.06). Revert half hurt in all tested weights; same-direction alpha raise helped. Delivered: same-direction alpha 0.12 only, revert disabled (REVERT_U=0).\",\n \"tried\": [\n  {\n   \"variant\": \"revert u=0.5 only\",\n   \"seeds\": \"10000..10499\",\n   \"n\": 5"
    },
    {
      "url": "https://api.imd.fun/artifacts/da313379a2e69e9286668865e06b18dfcae25732c82b934b0fd9c2ef0d8c2ff5",
      "quote": "{\n  \"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,"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "BASELINE_SETTINGS = BaselineSimulationSettings(\n    n_simulations=1000,\n    n_steps=10000,\n    initial_price=100.0,\n    initial_x=100.0,\n    initial_y=10000.0,\n    gbm_mu=0.0,\n    gbm_dt=1.0,\n    retail_buy_prob=0.5,\n    retail_size_sigma=1.2,\n)\n\n\nBASELINE_VARIANCE = HyperparameterVariance(\n    retail_mean_size_min=19.0,\n    retail_mean_size_max=21"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "            rng = np.random.default_rng(seed=i)\n\n            retail_mean_size = (\n                rng.uniform(self.variance.retail_mean_size_min, self.variance.retail_mean_size_max)\n                if self.variance.vary_retail_mean_size\n                else self.base_config.retail_mean_size\n            )\n            retail_arrival_rate = (\n        "
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/evm/compiler.py",
      "quote": "                    \"optimizer\": {\n                        \"enabled\": True,\n                        \"runs\": 200,\n                    },\n                    \"viaIR\": True,\n                    \"evmVersion\": \"paris\",\n                    \"outputSelection\": {\n                        \"*\": {\n                            \"*\": [\n                             "
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/contracts/src/AMMStrategyBase.sol",
      "quote": "    uint256[32] public slots;\n\n    /*//////////////////////////////////////////////////////////////\n                            HELPER FUNCTIONS\n    //////////////////////////////////////////////////////////////*/\n\n    /// @notice Multiply two WAD values\n    /// @param x First value (WAD)\n    /// @param y Second value (WAD)\n    /// @return Result i"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/simulation/engine.rs",
      "quote": "        // Initialize retail trader with different seed\n        let mut retail_trader = RetailTrader::new(\n            self.config.retail_arrival_rate,\n            self.config.retail_mean_size,\n            self.config.retail_size_sigma,\n            self.config.retail_buy_prob,\n            Some(seed + 1),\n        );\n\n        let arbitrageur = Arbitr"
    },
    {
      "url": "https://raw.githubusercontent.com/ChengHua926/amm-challenge/d34a5199c59a4c44d5336a25f1436b4ae1f21104/contracts/src/Strategy.sol",
      "quote": "// 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    uint2"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/lib.rs",
      "quote": "fn run_batch(\n    submission_bytecode: Vec<u8>,\n    baseline_bytecode: Vec<u8>,\n    configs: Vec<SimulationConfig>,\n    n_workers: usize,\n) -> PyResult<BatchSimulationResult> {\n    let batch_config = SimulationBatchConfig {\n        submission_bytecode,\n        baseline_bytecode,\n        configs,\n        n_workers: if n_workers == 0 { None } else { Some(n_workers) },\n    };\n\n    run_simulations_par"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/simulation/runner.rs",
      "quote": "    // Run simulations in parallel\n    let results: Result<Vec<LightweightSimResult>, SimulationError> = pool.install(|| {\n        batch_config.configs\n            .into_par_iter()\n            .map(|config| {\n                // Create fresh EVM strategies for this worker\n                let submission = EVMStrategy::new(\n                    submission_bytecode.clone(),\n                    \"Submiss"
    }
  ]
}