Invariants of quantum programs: characterisations and generation

M. Ying, Shenggang Ying, Xiaodi Wu
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引用次数: 40

Abstract

Program invariant is a fundamental notion widely used in program verification and analysis. The aim of this paper is twofold: (i) find an appropriate definition of invariants for quantum programs; and (ii) develop an effective technique of invariant generation for verification and analysis of quantum programs. Interestingly, the notion of invariant can be defined for quantum programs in two different ways -- additive invariants and multiplicative invariants -- corresponding to two interpretations of implication in a continuous valued logic: the Lukasiewicz implication and the Godel implication. It is shown that both of them can be used to establish partial correctness of quantum programs. The problem of generating additive invariants of quantum programs is addressed by reducing it to an SDP (Semidefinite Programming) problem. This approach is applied with an SDP solver to generate invariants of two important quantum algorithms -- quantum walk and quantum Metropolis sampling. Our examples show that the generated invariants can be used to verify correctness of these algorithms and are helpful in optimising quantum Metropolis sampling. To our knowledge, this paper is the first attempt to define the notion of invariant and to develop a method of invariant generation for quantum programs.
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量子程序的不变量:表征和生成
程序不变性是一个广泛应用于程序验证和分析的基本概念。本文的目的是双重的:(i)找到量子程序的不变量的适当定义;(ii)开发一种有效的不变量生成技术,用于量子程序的验证和分析。有趣的是,对于量子程序,不变量的概念可以用两种不同的方式定义——加性不变量和乘性不变量——对应于连续值逻辑中蕴涵的两种解释:Lukasiewicz蕴涵和哥德尔蕴涵。结果表明,这两种方法都可以用来建立量子程序的部分正确性。将量子规划的可加不变量的生成问题简化为半定规划问题。该方法与SDP求解器一起用于生成两种重要的量子算法——量子行走和量子Metropolis抽样的不变量。我们的例子表明,所生成的不变量可以用来验证这些算法的正确性,并有助于优化量子Metropolis采样。据我们所知,本文是第一次尝试定义不变量的概念,并开发一种量子程序的不变量生成方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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