We initiate the systematic study of QMA algorithms in the setting of property testing, to which we refer as QMA proofs of proximity (QMAPs). These are quantum query algorithms that receive explicit access to a sublinear-size untrusted proof and are required to accept inputs having a property $\Pi$ and reject inputs that are $\varepsilon$-far from $\Pi$, while only probing a minuscule portion of their input. Our algorithmic results include a general-purpose theorem that enables quantum speedups for testing an expressive class of properties, namely, those that are succinctly decomposable. Furthermore, we show quantum speedups for properties that lie outside of this family, such as graph bipartitneness. We also investigate the complexity landscape of this model, showing that QMAPs can be exponentially stronger than both classical proofs of proximity and quantum testers. To this end, we extend the methodology of Blais, Brody and Matulef (Computational Complexity, 2012) to prove quantum property testing lower bounds via reductions from communication complexity, thereby resolving a problem raised by Montanaro and de Wolf (Theory of Computing, 2016).
翻译:我们开始在财产测试设置中系统研究QMA算法,我们称之为QMA近距离证明(QMAs)。这些量子查询算法是量子查询算法,这些量子查询算法可以明确获取亚线尺寸不可信证据,并且需要接受产权值为$\Pi$的输入,并拒绝远远低于$\Pi$的输入,而只是探测其输入量的微小部分。我们的算法结果包括一个通用理论,使量子加速测试表达式属性类别,即简洁易碎的属性。此外,我们展示了本家族以外属性的量子加速,例如图双分割性。我们还调查了这一模型的复杂性,表明QMAPs比距离值和量子测试的典型证据都大得多。为此,我们扩展了布莱斯、布洛迪和马图利夫(Complicationality,2012年)的方法,以便通过通信复杂性的减少来证明量子属性测试较低的范围,从而解决2016年由蒙特纳和索尔夫公司提出的一个问题。