文章基本信息

标题：Quantum Algorithms for Classical Probability Distributions
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作者：Aleksandrs Belovs
期刊名称：LIPIcs : Leibniz International Proceedings in Informatics
电子版ISSN：1868-8969
出版年度：2019
卷号：144
页码：1-11
DOI：10.4230/LIPIcs.ESA.2019.16
出版社：Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
摘要：We study quantum algorithms working on classical probability distributions. We formulate four different models for accessing a classical probability distribution on a quantum computer, which are derived from previous work on the topic, and study their mutual relationships. Additionally, we prove that quantum query complexity of distinguishing two probability distributions is given by their inverse Hellinger distance, which gives a quadratic improvement over classical query complexity for any pair of distributions. The results are obtained by using the adversary method for state-generating input oracles and for distinguishing probability distributions on input strings.
关键词：quantum query complexity; quantum adversary method; distinguishing probability distributions; Hellinger distance