Asymptotically Optimal Quantum Universal Quickest Change Detection

📅 2026-02-03
📈 Citations: 1
Influential: 1
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🤖 AI Summary
This work addresses the problem of rapid change detection in quantum systems when the post-change state is unknown. The authors propose a two-stage approach: first, quantum information is converted into classical data via a block positive operator-valued measure (POVM) that preserves quantum relative entropy; then, a windowed CUSUM algorithm is applied to detect changes in the resulting classical sequence. This study represents the first extension of the classical universal quickest change detection framework to the quantum setting. Under the general assumption of an unknown post-change quantum state, the proposed method is proven to be asymptotically optimal in terms of worst-case average detection delay, thereby achieving a theoretical breakthrough and establishing performance optimality in quantum quickest change detection.

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📝 Abstract
This paper investigates the quickest change detection of quantum states in a universal setting: specifically, where the post-change quantum state is not known a priori. We establish the asymptotic optimality of a two-stage approach in terms of worst average delay to detection. The first stage employs block POVMs with classical outputs that preserve quantum relative entropy to arbitrary precision. The second stage leverages a recently proposed windowed-CUSUM algorithm that is known to be asymptotically optimal for quickest change detection with an unknown post-change distribution in the classical setting.
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Research questions and friction points this paper is trying to address.

quantum quickest change detection
unknown post-change state
universal detection
asymptotic optimality
Innovation

Methods, ideas, or system contributions that make the work stand out.

quantum quickest change detection
universal setting
block POVMs
quantum relative entropy
windowed-CUSUM
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