Measurement disturbance tradeoffs in three-qubit unsupervised quantum classification

Spencer-Wood, Hector and Jeffers, John and Croke, Sarah (2022) Measurement disturbance tradeoffs in three-qubit unsupervised quantum classification. Physical Review A, 105 (6). 062447. ISSN 1050-2947 (https://doi.org/10.1103/PhysRevA.105.062447)

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Abstract

We consider measurement disturbance tradeoffs in quantum machine learning protocols which seek to learn about quantum data. We study the simplest example of a binary classification task in the unsupervised regime. Specifically, we investigate how a classification of two qubits, that can each be in one of two unknown states, affects our ability to perform a subsequent classification on three qubits when a third is added. Surprisingly, we find a range of strategies in which a nontrivial first classification does not affect the success rate of the second classification. There is, however, a nontrivial measurement disturbance tradeoff between the success rate of the first and second classifications, and we fully characterize this tradeoff analytically.

ORCID iDs

Spencer-Wood, Hector, Jeffers, John ORCID logoORCID: https://orcid.org/0000-0002-8573-1675 and Croke, Sarah;
  • Item type:Article
    ID code:81076
    Dates:
    Date
    Event
    27 June 2022
    Published
    10 June 2022
    Accepted
    8 February 2022
    Submitted
    Subjects:Science > Physics
    Department:Faculty of Science > Physics
    Depositing user: Pure Administrator
    Date deposited:14 Jun 2022 08:50
    Last modified:11 Nov 2024 13:31
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/81076
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