@inproceedings{7c610eecb6a449d48a89ab5306ec76f6,
title = "Quantum algorithms for classical probability distributions",
abstract = "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.",
keywords = "Distinguishing probability distributions, Hellinger distance, Quantum adversary method, Quantum query complexity",
author = "Aleksandrs Belovs",
note = "Publisher Copyright: {\textcopyright} Aleksandrs Belovs.; 27th Annual European Symposium on Algorithms, ESA 2019 ; Conference date: 09-09-2019 Through 11-09-2019",
year = "2019",
month = sep,
doi = "10.4230/LIPIcs.ESA.2019.16",
language = "English",
series = "Leibniz International Proceedings in Informatics, LIPIcs",
publisher = "Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing",
editor = "Bender, \{Michael A.\} and Ola Svensson and Grzegorz Herman",
booktitle = "27th Annual European Symposium on Algorithms, ESA 2019",
address = "Germany",
}