{"sources":[{"url":"https://api.imdnotdead.fun/artifacts/755f4fc0a7b028497ad9ddf23ea568071192341e192335cb7f31174d066d4df0","quote":"\"source_sha256\":\"3a799de034a2482ff960dc0d89316a18a70ccff80b1d80af2e3b2d110977ec40\""},{"url":"https://api.imdnotdead.fun/artifacts/8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","quote":"## Strategy.sol (complete; sha256 c68887cff61180e12ba2b1ceb333edf76a830f91f63b5d775a8806fb9ec08aca, 42,990 bytes)"},{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/66604b3426d8e97a73e2c39940b9b4dece51cc73/research/tell/README.md","quote":"**on the grid:** the posterior it already computes, with retail's likelihood multiplied by the chance, a power of two: `pi = l_arb / (l_arb + l_ret * ulp(paid) / grid)`."},{"url":"https://raw.githubusercontent.com/gtmcknight/amm-sim/main/research/setup.sh","quote":"aedb68280aca34c110968f00148387c95885207913fb2cf19a1ab4c5cfd6887a"},{"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/competition/config.py","quote":"    retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/evm/compiler.py","quote":"                    \"viaIR\": True,\n                    \"evmVersion\": \"paris\","}]}