Measurement-based Verification of Quantum Markov Chains
Ji Guan, Yuan Feng, Andrea Turrini, Mingsheng Ying

TL;DR
This paper introduces a measurement-based quantum temporal logic MLTL for verifying quantitative properties of quantum Markov chains, extending classical techniques to quantum systems with efficient algorithms.
Contribution
It proposes MLTL, a new quantum temporal logic, and extends symbolic dynamics techniques for model checking quantum Markov chains efficiently.
Findings
Verified quantum and classical random walks simultaneously
Confirmed advantages of quantum walks over classical ones
Discovered new phenomena unique to quantum walks
Abstract
Model-checking techniques have been extended to analyze quantum programs and communication protocols represented as quantum Markov chains, an extension of classical Markov chains. To specify qualitative temporal properties, a subspace-based quantum temporal logic is used, which is built on Birkhoff-von Neumann atomic propositions. These propositions determine whether a quantum state is within a subspace of the entire state space. In this paper, we propose the measurement-based linear-time temporal logic MLTL to check quantitative properties. MLTL builds upon classical linear-time temporal logic (LTL) but introduces quantum atomic propositions that reason about the probability distribution after measuring a quantum state. To facilitate verification, we extend the symbolic dynamics-based techniques for stochastic matrices described by Agrawal et al. (JACM 2015) to handle more general…
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Taxonomy
TopicsData Quality and Management · Bayesian Modeling and Causal Inference
