The quantum communication complexity of sampling

Andris Ambainis, Leonard J. Schulman, Amnon Ta-Shma, Umesh Vazirani, Avi Wigderson

Research output: Contribution to journalArticlepeer-review

Abstract

Sampling is an important primitive in probabilistic and quantum algorithms. In the spirit of communication complexity, given a function f: X×Y→{0, 1} and a probability distribution D over X×Y, we define the sampling complexity of (f, D] as the minimum number of bits that Alice and Bob must communicate for Alice to pick x∈X and Bob to pick y∈Y as well as a value z such that the resulting distribution of (x, y, z) is close to the distribution (D, f(D)). In this paper we initiate the study of sampling complexity, in both the classical and quantum models. We give several variants of a definition. We completely characterize some of these variants and give upper and lower bounds on others. In particular, this allows us to establish an exponential gap between quantum and classical sampling complexity for the set-disjointness function.

Original languageEnglish
Pages (from-to)1570-1585
Number of pages16
JournalSIAM Journal on Computing
Volume32
Issue number6
DOIs
StatePublished - Sep 2003

Keywords

  • Communication complexity
  • Quantum communication complexity
  • Quantum information theory
  • Set-disjointness
  • The log-rank conjecture in communication complexity

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