{
  "sources": [
    {
      "url": "https://api.imdnotdead.fun/artifacts/528a6da78583c6142644a552c86670f9d25c20e39e92f4de44deae05ddc8cecd",
      "quote": "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  "
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/da313379a2e69e9286668865e06b18dfcae25732c82b934b0fd9c2ef0d8c2ff5",
      "quote": "// 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, "
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "def _build_configs(self) -> list[amm_sim_rs.SimulationConfig]:\n        \"\"\"Build simulation configs with optional variance.\"\"\"\n        import numpy as np\n\n        configs = []\n        for i in range(self.n_simulations):\n            rng = np.random.default_rng(seed=i)\n\n            retail_mean_size = (\n                rng.uniform(self.variance.retail_"
    },
    {
      "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   "
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/simulation/runner.rs",
      "quote": "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                    \"Submission\".to_string(),\n                ).map_err(|e| SimulationError::EVMError(e.to_string()))?;\n\n                let baseline = EVMStra"
    }
  ]
}