Direct Sum Theorems From Fortification

TL;DR

This paper introduces a generalized fortification lemma to analyze direct sum questions in communication complexity, providing new bounds on resource requirements for combined problems and improving understanding of protocol size behavior.

Contribution

It extends fortification techniques to sub-additive measures, derives a dual form called delta-fooling set, and proves new direct sum theorems for cover number and protocol size.

Findings

Reproves classic cover number direct sum theorem with a simple argument.

Establishes a new direct sum theorem for protocol size with improved bounds.

Introduces delta-fooling set as a generalized fooling set for communication complexity.

Abstract

We revisit the direct sum questions in communication complexity which asks whether the resource needed to solve $n$ communication problems together is (approximately) the sum of resources needed to solve these problems separately. Our work starts with the observation that Dinur and Meir's fortification lemma can be generalized to a general fortification lemma for a sub-additive measure over set. By applying this lemma to the case of cover number, we obtain a dual form of cover number, called "$\delta$-fooling set" which is a generalized fooling set. Any rectangle which contains enough number of elements from a $\delta$-fooling set can not be monochromatic. With this fact, we are able to reprove the classic direct sum theorem of cover number with a simple double counting argument. Formally, let $S \subseteq (A\times B) \times O$ and $T \subseteq (P\times Q) \times Z$ be two communication problems, $ \log \mathsf{Cov}\left(S\times T\right) \geq \log \mathsf{Cov}\left(S\right) + \log\mathsf{Cov}(T) -\log\log|P||Q|-4.$ where $\mathsf{Cov}$ denotes the cover number. One issue of current deterministic direct sum theorems about communication complexity is that they provide no information when $n$ is small, especially when $n=2$. In this work, we prove a new direct sum theorem about protocol size which imply a better direct sum theorem for two functions in terms of protocol size. Formally, let $\mathsf{L}$ denotes complexity of the protocol size of a communication problem, given a communication problem $F:A \times B \rightarrow \{0,1\}$, $ \log\mathsf{L}\left(F\times F\right)\geq \log \mathsf{L}\left(F\right) +\Omega\left(\sqrt{\log\mathsf{L}\left(F\right)}\right)-\log\log|A||B| -4$. All our results are obtained in a similar way using the $\delta$-fooling set to construct a hardcore for the direct sum problem.