{
  "id": "1610.03714",
  "version": "v1",
  "published": "2016-10-12T13:57:06.000Z",
  "updated": "2016-10-12T13:57:06.000Z",
  "title": "Quantum state estimation when qubits are lost: A no-data-left-behind approach",
  "authors": [
    "Brian P. Williams",
    "Pavel Lougovski"
  ],
  "comment": "28 pages",
  "categories": [
    "quant-ph"
  ],
  "abstract": "We present an approach to Bayesian mean estimation of quantum states using hyperspherical parametrization and an experiment-specific likelihood which allows utilization of all available data, even when qubits are lost. With this method, we report the first closed-form Bayesian mean and maximum likelihood estimates for the ideal single qubit. Due to computational constraints, we utilize numerical sampling to determine the Bayesian mean estimate for a photonic two-qubit experiment in which our novel analysis reduces burdens associated with experimental asymmetries and inefficiencies. This method can be applied to quantum states of any dimension and experimental complexity.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2016-10-12T13:57:06.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "quantum state estimation",
      "no-data-left-behind approach",
      "novel analysis reduces burdens",
      "first closed-form bayesian mean",
      "maximum likelihood estimates"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 28,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}