{
  "annotation_id": "95de6963-f918-4999-b4eb-7608e7ebbf51",
  "date_created": "2026-03-02T18:01:14.459000Z",
  "date_modified": "2026-03-02T18:01:14.459000Z",
  "file_hash": "a011b5238b5c2760486737c625ff05b73680f589e58d73768450e4cd208a3b6a",
  "private": false,
  "record": {
    "abstract": "We present a cross-language C++/Python program for simulations of quantum\nmechanical systems with the use of Quantum Monte Carlo (QMC) methods. We\ndescribe a system for which to apply QMC, the algorithms of variational Monte\nCarlo and diffusion Monte Carlo and we describe how to implement theses methods\nin pure C++ and C++/Python. Furthermore we check the efficiency of the\nimplementations in serial and parallel cases to show that the overhead using\nPython can be negligible.",
    "arxiv_id": "physics/0609191",
    "authors": [
      "J. K. Nilsen"
    ],
    "categories": [
      "physics.comp-ph",
      "cond-mat.other"
    ],
    "doi": "10.1016/j.cpc.2007.06.013",
    "title": "MontePython: Implementing Quantum Monte Carlo using Python",
    "url": "https://arxiv.org/abs/physics/0609191"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e9e0cec5-c427-42e7-8f24-1f435f0d8ae2",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}