{
  "annotation_id": "67f8b096-d984-4975-ae2f-a8e428eec99b",
  "date_created": "2026-02-17T05:53:20.118000Z",
  "date_modified": "2026-02-17T05:53:20.118000Z",
  "file_hash": "0889470cd3bd14a992147ffb9bc9464a170fc38cc40416d94950304197dd7a3e",
  "private": false,
  "record": {
    "abstract": "This work presents a randomized-tamed Milstein scheme for stochastic differential equations whose drift coefficient exhibits superlinear growth in the state variable and limited temporal regularity, quantified by $\\beta$-H\\\"older continuity with $\\beta \\in (0,1]$. The scheme combines a taming mechanism to control the superlinear state dependence with a drift randomization strategy designed to address the challenges posed by low temporal regularity. Under suitable assumptions on temporal smoothness, the scheme achieves an optimal strong $\\mathscr{L}^p$-convergence rate of order one.",
    "arxiv_id": "2601.09437",
    "authors": [
      "Sani Biswas"
    ],
    "categories": [
      "math.NA",
      "cs.NA",
      "math.PR"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "A Randomized Milstein Scheme for SDEs with Superlinear Drift Coefficient",
    "url": "https://arxiv.org/abs/2601.09437",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "4408fd8a-d8d4-4582-9af4-03ecd09eb189",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}