{
  "annotation_id": "d4b3ba8f-4b90-4cb5-9ec5-c08330f70563",
  "date_created": "2026-03-02T18:00:35.387000Z",
  "date_modified": "2026-03-02T18:00:35.387000Z",
  "file_hash": "6ba3e24116c21530758d0fb2688eb97b4ad6e9d27db62d5b8614aa2d3083e048",
  "private": false,
  "record": {
    "abstract": "We present an algorithm for rigid body diffusion Monte Carlo with importance\nsampling, which is based on a rigorous short-time expansion of the Green\u0027s\nfunction for rotational motion in three dimensions. We show that this\nshort-time approximation provides correct sampling of the angular degrees of\nfreedom, and provides a general way to incorporate importance sampling for all\ndegrees of freedom. The full importance sampling algorithm significantly\nimproves both calculational efficiency and accuracy of ground state properties,\nand allows rotational and bending excitations in molecular van der Waals\nclusters to be studied directly.",
    "arxiv_id": "physics/0109004",
    "authors": [
      "Alexandra Viel",
      "Mehul V. Patel",
      "Parhat Niyaz",
      "K. Birgitta Whaley"
    ],
    "categories": [
      "physics.comp-ph",
      "cond-mat",
      "physics.atm-clus"
    ],
    "doi": "10.1016/S0010-4655(02)00145-5",
    "title": "Importance Sampling in Rigid Body Diffusion Monte Carlo",
    "url": "https://arxiv.org/abs/physics/0109004"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "487263cb-7594-4bca-9f04-ac6c0b8163f6",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}