Time- and Query-optimal Quantum Algorithms Based on Decision Trees

Salman Beigi, Leila Taghavi, Artin Tajdini
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引用次数: 2

Abstract

It has recently been shown that starting with a classical query algorithm (decision tree) and a guessing algorithm that tries to predict the query answers, we can design a quantum algorithm with query complexity O(√ GT where T is the query complexity of the classical algorithm (depth of the decision tree) and G is the maximum number of wrong answers by the guessing algorithm [3, 14]. In this article, we show that, given some constraints on the classical algorithms, this quantum algorithm can be implemented in time Õ(√ GT). Our algorithm is based on non-binary span programs and their efficient implementation. We conclude that various graph-theoretic problems including bipartiteness, cycle detection, and topological sort can be solved in time O(n3/2log2n) and with O(n3/2) quantum queries. Moreover, finding a maximal matching can be solved with O(n3/2) quantum queries in time O(n3/2log2n), and maximum bipartite matching can be solved in time O(n2log2n).
基于决策树的时间和查询最优量子算法
最近有研究表明,从经典查询算法(决策树)和尝试预测查询答案的猜测算法开始,我们可以设计一个查询复杂度为O(√GT)的量子算法,其中T为经典算法(决策树深度)的查询复杂度,G为猜测算法的最大错误答案数[3,14]。在本文中,我们证明了在给定经典算法的一些约束条件下,该量子算法可以在Õ(√GT)时间内实现。我们的算法基于非二进制跨度程序及其高效实现。我们得出结论,各种图论问题,包括双分性、循环检测和拓扑排序,可以在O(n3/2log2n)时间内用O(n3/2)个量子查询解决。在O(n3/2log2n)时间内,可以用O(n3/2log2n)个量子查询求解最大匹配,在O(n2log2n)时间内求解最大二部匹配。
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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