{
  "annotation_id": "f44d4e35-803e-4ad3-9eb2-02b6ee1bb0c8",
  "date_created": "2026-03-02T18:02:09.947000Z",
  "date_modified": "2026-03-02T18:02:09.947000Z",
  "file_hash": "fa597c3c79015b87bf58eb20744dbb8ceefc82d9d8457fe1dbb6c032637d8b88",
  "private": false,
  "record": {
    "abstract": "Stochastic differential equations (sdes) play an important role in physics\nbut existing numerical methods for solving such equations are of low accuracy\nand poor stability. A general strategy for developing accurate and efficient\nschemes for solving stochastic equations in outlined here. High order numerical\nmethods are developed for integration of stochastic differential equations with\nstrong solutions. We demonstrate the accuracy of the resulting integration\nschemes by computing the errors in approximate solutions for sdes which have\nknown exact solutions.",
    "arxiv_id": "quant-ph/0407039",
    "authors": [
      "Joshua Wilkie"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1103/PhysRevE.70.017701",
    "title": "Numerical Methods for Stochastic Differential Equations",
    "url": "https://arxiv.org/abs/quant-ph/0407039"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0d44983f-27b0-453c-920d-fbdfa3923e5f",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}