Quantum algorithms for testing properties of distributions

Sergey Bravyi, Aram W. Harrow, Avinatan Hassidim

Research output: Contribution to journalArticlepeer-review

Abstract

Suppose one has access to oracles generating samples from two unknown probability distributions p and q on some n -element set. How many samples does one need to test whether the two distributions are close or far from each other in the L1-norm? This and related questions have been extensively studied during the last years in the field of property testing. In the present paper we study quantum algorithms for testing properties of distributions. It is shown that the L1-distance ∥ p-q ∥1 can be estimated with a constant precision using only O(N1/2) queries in the quantum settings, whereas classical computers need Ω(N1-o(1)) queries. We also describe quantum algorithms for testing uniformity and orthogonality with query complexity O(N1/3). The classical query complexity of these problems is known to be Ω(N1/2).

Original languageEnglish
Article number5773032
Pages (from-to)3971-3981
Number of pages11
JournalIEEE Transactions on Information Theory
Volume57
Issue number6
DOIs
StatePublished - Jun 2011
Externally publishedYes

Keywords

  • Property testing
  • quantum information
  • query complexity
  • sampling
  • statistical distance

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Fingerprint

Dive into the research topics of 'Quantum algorithms for testing properties of distributions'. Together they form a unique fingerprint.

Cite this