关于一次读AC^0公式的通信复杂度

T. S. Jayram, Swastik Kopparty, P. Raghavendra
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引用次数: 16

摘要

研究了一次读AC0公式的两方随机通信复杂度。对于具有n个输入和深度d的平衡and -OR树T,我们表明函数f(x, y) = T(x \circ y)的通信复杂度为\Omega(n/4^d),其中(x \circ y)被定义为使所得到的树也具有与或门的交替电平。对于x \circ y的每一位,运算\circ是与还是或取决于它作为输入的T中的门。利用这一点,我们证明了对于具有n个输入和深度d的一般and或树T, f (x \circ y)的通信复杂度为n/2^{\O(d log d)}。这些结果推广了集不连接的通信复杂性的经典结果[1],[2](其中T是一个OR门)和最近关于TRIBES函数的通信复杂性的结果[3](其中T是一个深度2读取一次公式)。我们的技术建立并扩展了信息复杂性方法[4],[5],[3],用于证明随机通信复杂性的下界。我们对深度d树的分析分两步进行:(1)约简到测量二叉深度d树的信息复杂度,(2)证明二叉树信息复杂度的下界。为了执行这个程序,我们仔细地构造了输入分布,使这两个步骤可以同时执行。我们相信,我们开发的工具将在进一步研究信息复杂性,特别是通信复杂性方面被证明是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Communication Complexity of Read-Once AC^0 Formulae
We study the 2-party randomized communication complexity of read-once AC0 formulae. For balanced AND-OR trees T with n inputs and depth d, we show that the communication complexity of the function f(x, y) = T(x \circ y) is \Omega(n/4^d) where (x \circ y) is defined so that the resulting tree also has alternating levels of AND and OR gates. For each bit of x \circ y, the operation \circ is either AND or OR depending on the gate in T to which it is an input. Using this, we show that for general AND-OR trees T with n inputs and depth d, the communication complexity of f (x \circ y) is n/2^{\O(d log d)}. These results generalize classical results on the communication complexity of set-disjointness [1], [2] (where T is an OR -gate) and recent results on the communication complexity of the TRIBES functions [3] (where T is a depth-2 read-once formula). Our techniques build on and extend the information complexity methodology [4], [5], [3] for proving lower bounds on randomized communication complexity. Our analysis for trees of depth d proceeds in two steps: (1) reduction to measuring the information complexity of binary depth-d trees, and (2) proving lower bounds on the information complexity of binary trees. In order to execute this program, we carefully construct input distributions under which both these steps can be carried out simultaneously. We believe the tools we develop will prove useful in further studies of information complexity in particular, and communication complexity in general.
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