{
  "annotation_id": "cc8d719d-7304-4abe-b143-b2570376a170",
  "date_created": "2026-02-17T05:53:11.403000Z",
  "date_modified": "2026-02-17T05:53:11.403000Z",
  "file_hash": "a630ac6ee1cf7b4f3e21f58b52e517af8cb7b409f8b4fbcbf7f830610da95cdb",
  "private": false,
  "record": {
    "abstract": "We propose physics-informed digital twin (PIDT): a fiber parameter estimation approach that combines a parameterized split-step method with a physics-informed loss. PIDT improves accuracy and convergence speed with lower complexity compared to previous neural operators.",
    "arxiv_id": "2601.07436",
    "authors": [
      "Zicong Jiang",
      "Magnus Karlsson",
      "Erik Agrell",
      "Christian H\u00e4ger"
    ],
    "categories": [
      "eess.SP",
      "cs.LG",
      "physics.optics"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "PIDT: Physics-Informed Digital Twin for Optical Fiber Parameter Estimation",
    "url": "https://arxiv.org/abs/2601.07436",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "45587eb1-ef9c-4f51-8801-3da6533efc10",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}