Ultimate limits for quickest quantum change-point detection
Marco Fanizza, Christoph Hirche, John Calsamiglia

TL;DR
This paper establishes the fundamental quantum limits for quickest change-point detection in quantum data streams, providing lower bounds and optimal strategies that attain these bounds, and discusses extensions to quantum channels.
Contribution
It introduces the quantum counterpart of change-point detection, derives the ultimate quantum limit, and proposes strategies that asymptotically achieve this bound.
Findings
Derived the lower bound on mean minimum delay for quantum change detection.
Proposed measurement strategies that attain the quantum limit asymptotically.
Extended the discussion to online change detection in quantum channels.
Abstract
Detecting abrupt changes in data streams is crucial because they are often triggered by events that have important consequences if left unattended. Quickest change point detection has become a vital sequential analysis primitive that aims at designing procedures that minimize the expected detection delay of a change subject to a bounded expected false alarm time. We put forward the quantum counterpart of this fundamental primitive on streams of quantum data. We give a lower-bound on the mean minimum delay when the expected time of a false alarm is asymptotically large, under the most general quantum detection strategy, which is given by a sequence of adaptive collective (potentially weak) measurements on the growing string of quantum data. In addition, we give particular strategies based on repeated measurements on independent blocks of samples, that asymptotically attain the…
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Taxonomy
TopicsQuantum Information and Cryptography · Quantum Mechanics and Applications · Quantum Computing Algorithms and Architecture
