Quantum Communication Complexity of Distributed Set Joins
Stacey Jeffery, Fran\c{c}ois Le Gall

TL;DR
This paper explores the quantum communication complexity of distributed set joins, presenting a quantum protocol that outperforms classical methods for sparse matrix products and establishing bounds for matrix multiplication over finite fields.
Contribution
It introduces a quantum protocol for distributed Boolean matrix multiplication with improved communication bounds and relates set join complexity to direct product theorems in communication complexity.
Findings
Quantum protocol reduces communication for sparse matrix multiplication.
Quantum lower bounds match classical upper bounds over finite fields.
Connections established between set join complexity and direct product theorems.
Abstract
Computing set joins of two inputs is a common task in database theory. Recently, Van Gucht, Williams, Woodruff and Zhang [PODS 2015] considered the complexity of such problems in the natural model of (classical) two-party communication complexity and obtained tight bounds for the complexity of several important distributed set joins. In this paper we initiate the study of the *quantum* communication complexity of distributed set joins. We design a quantum protocol for distributed Boolean matrix multiplication, which corresponds to computing the composition join of two databases, showing that the product of two Boolean matrices, each owned by one of two respective parties, can be computed with qubits of communication, where denotes the number of non-zero entries of the product. Since Van Gucht et al. showed that the classical…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Cryptography and Data Security
