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An Additive Combinatorics Approach Relating Rank to Communication Complexity

机译:将等级与通信复杂性相关的加法组合方法

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For a ${0, 1}$-valued matrix $M$ let $cc(M)$ denote the deterministic communication complexity of the boolean function associated with $M$. It is well-known since the work of Mehlhorn and Schmidt [STOC 1982] that $cc(M)$ is bounded from above by $rnk(M)$ and from below by $log rnk(M)$ where $rnk(M)$ denotes the rank of $M$ over the field of real numbers. Determining where in this range lies the true worst-case value of $cc(M)$ is a fundamental open problem in communication complexity. The state of the art is [log^{1.631} rnk(M)leq cc(M) leq 0.415 rnk(M), ] the lower bound is by Kushilevitz [unpublished, 1995] and the upper bound is due to Kotlov [Journal of Graph Theory, 1996]. Lov'{a}sz and Saks [FOCS 1988] conjecture that $cc(M)$ is closer to the lower bound, i.e., $cc(M)leq log^c(rnk(M))$ for some absolute constant $c$ -- this is the famous ``log-rank conjecture'' -- but so far there has been no evidence to support it, even giving a slightly non-trivial ($o(rnk(M))$) upper bound on the communication complexity. Our main result is that, assuming the Polynomial Freiman-Ruzsa (PFR) conjecture in additive combinatorics, there exists a universal constant $c$ such that [cc(M)leq c cdot rnk(M)/log rnk(M).] Although our bound is stated using the rank of $M$ over the reals, our proof goes by studying the problem over the finite field of size $2$, and there we bring to bear a number of new tools from additive combinatorics which we hope will facilitate further progress on this perplexing question. In more detail, our proof is based on the study of the ``approximate duality conjecture'' which was suggested by Ben-Sasson and Zewi [STOC 2011] and studied there in connection to the PFR conjecture. First we improve the bounds on approximate duality assuming the PFR conjecture. Then we use the approximate duality conjecture (with improved bounds) to get our upper bound on the communication complexity of low-rank martices.
机译:对于$ {0,1} $值矩阵$ M $,令$ cc(M)$表示与$ M $相关的布尔函数的确定性通信复杂度。自Mehlhorn和Schmidt [STOC 1982]的工作以来,众​​所周知,$ cc(M)$由上限定为$ rnk(M)$,而下限定为$ log rnk(M)$,其中$ rnk(M )$表示$ M $在实数字段中的排名。确定此范围内真正的最坏情况下的值cc(M)$是通信复杂性的根本性开放问题。现有技术水平为[log ^ {1.631} rnk(M)leq cc(M)leq 0.415 rnk(M),]下限由Kushilevitz [未出版,1995],上限由Kotlov [期刊]图论研究,1996]。 Lov'{a} sz和Saks [FOCS 1988]推测$ cc(M)$接近下限,即对于某个绝对常数$,$ cc(M)leq log ^ c(rnk(M))$ c $-这是著名的``对数秩猜想''-但到目前为止,没有证据支持它,甚至给出了一个稍微平凡的($ o(rnk(M))$)上限关于通信的复杂性。我们的主要结果是,假设加法组合中的多项式Freiman-Ruzsa(PFR)猜想,存在一个通用常数$ c $,使得[cc(M)leq c cdot rnk(M)/ log rnk(M)。尽管我们使用$ M $的实数来表示边界,但我们的证明是通过研究$ 2 $有限域上的问题来进行的,在那里,我们带来了加法组合函数学中的许多新工具,希望我们能促进这个令人困惑的问题的进一步发展。更详细地讲,我们的证明基于Ben-Sasson和Zewi提出的``近似对偶猜想''[STOC 2011]的研究,并在那里进行了PFR猜想的研究。首先,我们假设PFR猜想会改善近似对偶性的边界。然后,我们使用近似对偶猜想(具有改进的边界)来获得低阶mar通信的通信复杂度的上限。

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