{
  "annotation_id": "296e710e-b8d2-418c-a01c-b195adc00226",
  "date_created": "2026-03-02T18:00:39.866000Z",
  "date_modified": "2026-03-02T18:00:39.866000Z",
  "file_hash": "10bd4bf9beed36e6b40d725493ec5517cd158bb1f6c71e4123611f2b747579d6",
  "private": false,
  "record": {
    "abstract": "Systematic inaccuracy is inherent in any computational estimate of a\nnon-linear average, due to the availability of only a finite number of data\nvalues, N. Free energy differences (DF) between two states or systems are\ncritically important examples of such averages in physical, chemical and\nbiological settings. Previous work has demonstrated, empirically, that the\n``finite-sampling error\u0027\u0027 can be very large -- many times kT -- in DF estimates\nfor simple molecular systems. Here, we present a theoretical description of the\ninaccuracy, including the exact solution of a sample problem, the precise\nasymptotic behavior in terms of 1/N for large N, the identification of\nuniversal law, and numerical illustrations. The theory relies on corrections to\nthe central and other limit theorems, and thus a role is played by stable\n(Levy) probability distributions.",
    "arxiv_id": "physics/0201046",
    "authors": [
      "Daniel M. Zuckerman",
      "Thomas B. Woolf"
    ],
    "categories": [
      "physics.comp-ph",
      "physics.chem-ph",
      "physics.data-an"
    ],
    "doi": "10.1103/PhysRevLett.89.180602",
    "title": "Theory of Systematic Computational Error in Free Energy Differences",
    "url": "https://arxiv.org/abs/physics/0201046"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "72f24f64-0c77-4b08-8c7b-8c1e93f063af",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}