{
  "sources": [
    {
      "url": "https://raw.githubusercontent.com/ChengHua926/amm-challenge/d34a5199c59a4c44d5336a25f1436b4ae1f21104/contracts/src/Strategy.sol",
      "quote": "uint256 constant PHAT_ALPHA = 270000000000000000;\n    uint256 constant PHAT_ALPHA_RETAIL = 60000000000000000;"
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/da313379a2e69e9286668865e06b18dfcae25732c82b934b0fd9c2ef0d8c2ff5",
      "quote": "// Interior retail routing equalizes fee-adjusted marginal prices."
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/528a6da78583c6142644a552c86670f9d25c20e39e92f4de44deae05ddc8cecd",
      "quote": "bool secondPrint = !firstInStep && stepTradeCount == 1;"
    },
    {
      "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            )"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "BASELINE_VARIANCE = HyperparameterVariance(\n    retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,\n    retail_arrival_rate_min=0.6,\n    retail_arrival_rate_max=1.0,\n    vary_retail_arrival_rate=True,\n    gbm_sigma_min=0.000882,\n    gbm_sigma_max=0.001008,\n    vary_gbm_sigma=True,\n)"
    },
    {
      "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        );"
    },
    {
      "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>"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/contracts/src/VanillaStrategy.sol",
      "quote": "/// @notice Fixed fee in WAD (30 bps = 0.30% = 30e14)\n    uint256 public constant FEE = 30 * BPS;"
    },
    {
      "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\","
    }
  ]
}