{
 "sources": [
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/router.rs",
   "quote": "let numerator = r * (y2 + gamma2 * total_y) - y1;"
  },
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/arbitrageur.rs",
   "quote": "let new_x = (k / (gamma * fair_price)).sqrt();"
  },
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/arbitrageur.rs",
   "quote": "let x_virtual = (k * gamma / fair_price).sqrt();"
  },
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/market/retail.rs",
   "quote": "let mu = mean.ln() - 0.5 * sigma * sigma;"
  },
  {
   "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
   "quote": "retail_size_sigma=1.2,"
  },
  {
   "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_sim_rs/src/evm/strategy.rs",
   "quote": "const GAS_LIMIT_TRADE: u64 = 250_000;"
  },
  {
   "url": "https://api.imd.fun/artifacts/528a6da78583c6142644a552c86670f9d25c20e39e92f4de44deae05ddc8cecd",
   "quote": "Second-print reclassification within a step"
  },
  {
   "url": "https://api.imd.fun/artifacts/da313379a2e69e9286668865e06b18dfcae25732c82b934b0fd9c2ef0d8c2ff5",
   "quote": "// Interior retail routing"
  }
 ]
}