{
  "annotation_id": "72dab684-e1f3-49f4-9b2d-75e34764c8d0",
  "date_created": "2026-02-17T05:53:12.450000Z",
  "date_modified": "2026-02-17T05:53:12.450000Z",
  "file_hash": "0524d637ab616f2de4eab9d52557ebe801c75d41c41d2411e4030f80ffa4db87",
  "private": false,
  "record": {
    "abstract": "Quantum computing (QC) has experienced rapid growth in recent years with the advent of robust programming environments, readily accessible software simulators and cloud-based QC hardware platforms, and growing interest in learning how to design useful methods that leverage this emerging technology for practical applications. From the perspective of the field of visualization, this article examines research challenges and opportunities along the path from initial feasibility to practical use of QC platforms applied to meaningful problems.",
    "arxiv_id": "2601.07872",
    "authors": [
      "E. Wes Bethel",
      "Roel Van Beeumen",
      "Talita Perciano"
    ],
    "categories": [
      "quant-ph"
    ],
    "doi": "10.1109/MCG.2025.3646315",
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "Quantum Computing and Visualization Research Challenges and Opportunities",
    "url": "https://arxiv.org/abs/2601.07872",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "8f0aad9e-67bf-415e-a378-6f35fb7ae371",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}