paper

Composition theorems in communication complexity

arXiv:1003.1443

Abstract

A well-studied class of functions in communication complexity are composed functions of the form $(f \comp g^n)(x,y)=f(g(x^1, y^1),..., g(x^n,y^n))$. This is a rich family of functions which encompasses many of the important examples in the literature. It is thus of great interest to understand what properties of and affect the communication complexity of $(f \comp g^n)$, and in what way. Recently, Sherstov \cite{She09b} and independently Shi-Zhu \cite{SZ09b} developed conditions on the inner function which imply that the quantum communication complexity of $f \comp g^n$ is at least the approximate polynomial degree of . We generalize both of these frameworks. We show that the pattern matrix framework of Sherstov works whenever the inner function is {\em strongly balanced}---we say that is strongly balanced if all rows and columns in the matrix sum to zero. This result strictly generalizes the pattern matrix framework of Sherstov \cite{She09b}, which has been a very useful idea in a variety of settings \cite{She08b,RS08,Cha07,LS09,CA08,BHN09}. Shi-Zhu require that the inner function has small {\em spectral discrepancy}, a somewhat awkward condition to verify. We relax this to the usual notion of discrepancy. We also enhance the framework of composed functions studied so far by considering functions , where the range of is a group . When is Abelian, the analogue of the strongly balanced condition becomes a simple group invariance property of . We are able to formulate a general lower bound on whenever satisfies this property.

19 pages

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Composition theorems in communication complexity · wovepaper