{
  "annotation_id": "c1172832-9542-4a6a-8203-0f362d095613",
  "date_created": "2026-03-02T18:00:42.162000Z",
  "date_modified": "2026-03-02T18:00:42.162000Z",
  "file_hash": "49f735b5a83b98abe994675468c75b867b8c5ba20428ad8819e37424fb9ad00e",
  "private": false,
  "record": {
    "abstract": "A general-purpose, self-adapting Monte Carlo (MC) algorithm implemented in\nthe program {\\tt Foam} is described. The high efficiency of the MC, that is\nsmall maximum weight or variance of the MC weight is achieved by means of\ndividing the integration domain into small cells. The cells can be\n$n$-dimensional simplices, hyperrectangles or a Cartesian product of them. The\ngrid of cells, ``foam\u0027\u0027, is produced in the process of the binary split of the\ncells. The next cell to be divided and the position/direction of the division\nhyperplane is chosen by the algorithm which optimizes the ratio of the maximum\nweight to the average weight or (optionally) the total variance. The algorithm\nis able to deal, in principle, with an arbitrary pattern of the singularities\nin the distribution.",
    "arxiv_id": "physics/0210061",
    "authors": [
      "S. Jadach"
    ],
    "categories": [
      "physics.comp-ph"
    ],
    "doi": "10.1016/S0920-5632(03)90682-7",
    "title": "Foam: A General purpose Monte Carlo Cellular Algorithm",
    "url": "https://arxiv.org/abs/physics/0210061"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "c3e3618a-5206-4cf1-bce6-abdcc5533671",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}