{
  "annotation_id": "e45275ae-4122-4a48-859b-b155da729376",
  "date_created": "2026-03-02T18:02:06.286000Z",
  "date_modified": "2026-03-02T18:02:06.286000Z",
  "file_hash": "40b6351b7cc6ab5d86767825a7eff9279b6bce0fc73e5b464f2d108331bb45a4",
  "private": false,
  "record": {
    "abstract": "The problem addressed is to design a detector which is maximally sensitive to\nspecific quantum states. Here we concentrate on quantum state detection using\nthe worst-case a posteriori probability of detection as the design criterion.\nThis objective is equivalent to asking the question: if the detector declares\nthat a specific state is present, what is the probability of that state\nactually being present? We show that maximizing this worst-case probability\n(maximizing the smallest possible value of this probability) is a quasiconvex\noptimization over the matrices of the POVM (positive operator valued measure)\nwhich characterize the measurement apparatus. We also show that with a given\nPOVM, the optimization is quasiconvex in the matrix which characterizes the\nKraus operator sum representation (OSR) in a fixed basis. We use Lagrange\nDuality Theory to establish the optimality conditions for both deterministic\nand randomized detection. We also examine the special case of detecting a\nsingle pure state. Numerical aspects of using convex optimization for quantum\nstate detection are also discussed.",
    "arxiv_id": "quant-ph/0403150",
    "authors": [
      "Robert L. Kosut",
      "Ian Walmsley",
      "Yonina Eldar",
      "Herschel Rabitz"
    ],
    "categories": [
      "quant-ph"
    ],
    "title": "Quantum State Detector Design: Optimal Worst-Case a posteriori   Performance",
    "url": "https://arxiv.org/abs/quant-ph/0403150"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e4636848-39bf-461a-84f3-600ec78c18d6",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}