{
  "annotation_id": "640dad32-c37c-487a-a109-69ea532c3656",
  "date_created": "2026-03-02T18:02:41.734000Z",
  "date_modified": "2026-03-02T18:02:41.734000Z",
  "file_hash": "6ed5b07bbe6ad2a4250360051f73054d52bc454e25c45d7598cd074eaa8a1be7",
  "private": false,
  "record": {
    "abstract": "The most powerful technique known at present for bounding the size of quantum\ncodes of prescribed minimum distance is the quantum linear programming bound.\nUnlike the classical linear programming bound, it is not immediately obvious\nthat if the quantum linear programming constraints are satisfiable for\ndimension K, that the constraints can be satisfied for all lower dimensions. We\nshow that the quantum linear programming bound is indeed monotonic in this\nsense, and give an explicitly monotonic reformulation.",
    "arxiv_id": "quant-ph/9802070",
    "authors": [
      "Eric M. Rains"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Monotonicity of the quantum linear programming bound",
    "url": "https://arxiv.org/abs/quant-ph/9802070"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "b84728db-51f4-4162-93e5-040939beec30",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}