{
 "sources": [
  {
   "url": "https://api.imdnotdead.fun/artifacts/9b842d35c17245af4dd2bfc0ec608263f9b7edcb2db619cffba7d36d1d853740",
   "quote": "Download the pinned TC-A above as `Candidate.sol`; apply with `patch -p1` from its containing directory. This is the complete frozen source delta, including GATE=1. Tables and spline rounding are retained."
  },
  {
   "url": "https://api.imdnotdead.fun/artifacts/9b842d35c17245af4dd2bfc0ec608263f9b7edcb2db619cffba7d36d1d853740",
   "quote": "Credit: Taylor (gtmcknight), original solved Gaussian filter, qm tables, fee policy, and replica (`amm-sim` commit `4812a6382311624e1506aca131ca35c378f930d9`). COMBO and the TwoComp port 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/identity-md-launches/goal-3170-beat-network-s-amm-entry/4eb3e985fd31e3cd17832501b95b6d2491aca73d/tools/engine.py",
   "quote": "Run each contract alone versus the 30 bps VanillaStrategy; half-open seed range."
  },
  {
   "url": "https://raw.githubusercontent.com/identity-md-launches/goal-3170-beat-network-s-amm-entry/4eb3e985fd31e3cd17832501b95b6d2491aca73d/tools/engine.py",
   "quote": "batch = amm_sim_rs.run_batch(list(bytes.fromhex(code['creation'])), list(normalizer), cfg, 8)"
  },
  {
   "url": "https://raw.githubusercontent.com/identity-md-launches/goal-3170-beat-network-s-amm-entry/4eb3e985fd31e3cd17832501b95b6d2491aca73d/tools/check.py",
   "quote": "Credit: Taylor (gtmcknight), Gaussian filter, qm tables and replica."
  },
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
   "quote": "rng = np.random.default_rng(seed=i)"
  }
 ]
}