{
  "sources": [
    {
      "url": "https://raw.githubusercontent.com/gtmcknight/amm-sim/4812a6382311624e1506aca131ca35c378f930d9/research/solved/README.md",
      "quote": "10000  448.261189  443.455598  443.522608  443.663520\n10001  576.779199  571.463409  571.623551  571.977293\n10002  531.886497  525.168028  525.865859  526.411631"
    },
    {
      "url": "https://api.imd.fun/artifacts/9242f3ebbe1ef8d23e590c9784f147655714aaf8a6da7a841273170f20c9ad9b",
      "quote": "Taylor (gtmcknight): replica2.py (config, price and order streams, the reference run) and the policies scored on it, github.com/gtmcknight/amm-sim @4812a6382311624e1506aca131ca35c378f930d9, research/solved. COMBO/TwoComp/QMRef are IdentityMD items built on Taylor's Gaussian filter and qm tables. Engine source: benedictbrady/amm-challenge @6b6921f8."
    },
    {
      "url": "https://api.imd.fun/artifacts/d56e3af5cc1e32dcc52be27046df89fb403d770a7fabf39e1a0ef94827349a5a",
      "quote": "Taylor (gtmcknight): replica2.py, the Gaussian filter, fee rule and qm tables (github.com/gtmcknight/amm-sim @4812a6382311624e1506aca131ca35c378f930d9, research/solved). COMBO/TwoComp/qt1-ref are IdentityMD items built on them. Engine: benedictbrady/amm-challenge @6b6921f8d463314aa7c96234e1be25a25245f704."
    },
    {
      "url": "https://api.imd.fun/artifacts/3385a6e029d6bea8c32e24205e2207988e325b8b70ad133c8b2083a052e3ac3e",
      "quote": "Taylor (gtmcknight): solved policy, Gaussian filter, qm tables and replica; IdentityMD qt1/TwoComp/ComboG and cp-c build on that work."
    },
    {
      "url": "https://raw.githubusercontent.com/identity-md-launches/goal-3170-beat-network-s-amm-entry/4eb3e985fd31e3cd17832501b95b6d2491aca73d/contracts/Candidate.sol",
      "quote": "// Two-component posterior port; credit Taylor (gtmcknight) for policy, filter and tables."
    },
    {
      "url": "https://raw.githubusercontent.com/identity-md-launches/goal-3170-beat-network-s-amm-entry/4eb3e985fd31e3cd17832501b95b6d2491aca73d/reference/qt1/Strategy.sol",
      "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/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/types/wad.rs",
      "quote": "    pub fn from_f64(value: f64) -> Self {\n        Wad((value * WAD as f64) as i128)\n    }"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "        for i in range(self.n_simulations):\n            rng = np.random.default_rng(seed=i)"
    }
  ]
}