{
  "sources": [
    {
      "url": "https://api.imd.fun/artifacts/8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40",
      "quote": "// Solved AMM policy by Taylor (gtmcknight), amm-sim 4812a638 research/solved: Gaussian filter + qm tables (qm_k1e-5.json),"
    },
    {
      "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/setup-fast.sh",
      "quote": "uv pip install -q \"$WHEEL\" \"numpy>=1.24\" \"py-solc-x==2.1.0\" \"pyrevm==0.3.7\""
    },
    {
      "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/harness.py",
      "quote": "N_WORKERS = 8"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "rng = np.random.default_rng(seed=i)"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/evm/compiler.py",
      "quote": "\"evmVersion\": \"paris\","
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/contracts/src/VanillaStrategy.sol",
      "quote": "uint256 public constant FEE = 30 * BPS;"
    }
  ]
}