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Monotone Circuits for the Majority Function

机译:多数功能的单调电路

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摘要

We present a simple randomized construction of size O(n~3) and depth 5.3 log n + O(1) monotone circuits for the majority function on n variables. This result can be viewed as a reduction in the size and a partial derandomization of Valiant's construction of an O(n~(5.3)) monotone formula. On the other hand, compared with the deterministic monotone circuit obtained from the sorting network of Ajtai, Komlos, and Szemeredi, our circuit is much simpler and has depth O(log n) with a small constant. The techniques used in our construction incorporate fairly recent results showing that expansion yields performance guarantee for the belief propagation message passing algorithms for decoding low-density parity-check (LDPC) codes, [3]. As part of the construction, we obtain optimal-depth linear-size monotone circuits for the promise version of the problem, where the number of 1's in the input is promised to be either less than one third, or greater than two thirds. We also extend these improvements to general threshold functions. At last, we show that the size can be further reduced at the expense of increased depth, and obtain a circuit for the majority of size and depth about n~(1+2~(1/2)) and 9.9 log n.
机译:对于n个变量的多数函数,我们提出了大小为O(n〜3)和深度5.3 log n + O(1)单调电路的简单随机构造。这个结果可以看作是O(n〜(5.3))单调公式的Valiant构造的尺寸减小和部分去随机化。另一方面,与从Ajtai,Komlos和Szemeredi的分类网络中获得的确定性单调电路相比,我们的电路要简单得多,并且深度O(log n)且常数较小。我们的构造中使用的技术结合了相当近期的结果,这些结果表明扩展可为解码低密度奇偶校验(LDPC)码的置信传播消息传递算法提供性能保证,[3]。作为构造的一部分,我们为问题的承诺版本获得最佳深度的线性单调电路,其中输入中的1的数量应保证小于三分之一或大于三分之二。我们还将这些改进扩展到一般阈值功能。最后,我们证明了可以以增加深度为代价进一步减小尺寸,并获得了大约n〜(1 + 2〜(1/2))和9.9 log n的大部分尺寸和深度的电路。

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