Branching programs with bounded repetitions and flow formulas

A. Sofronova, Dmitry Sokolov
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引用次数: 1

Abstract

Restricted branching programs capture various complexity measures like space in Turing machines or length of proofs in proof systems. In this paper, we focus on the application in the proof complexity that was discovered by Lovasz et al. [14] who showed the equivalence between regular Resolution and read-once branching programs for "unsatisfied clause search problem" (Searchφ). This connection is widely used, in particular, in the recent breakthrough result about the Clique problem in regular Resolution by Atserias et al. [5]. We study the branching programs with bounded repetitions, so-called (1, +k)-BPs (Sieling [21]) in application to the Searchφ problem. On the one hand, it is a natural generalization of read-once branching programs. On the other hand, this model gives a powerful proof system that can efficiently certify the unsatisfiability of a wide class of formulas that is hard for Resolution (Knop [13]). We deal with Searchφ that is "relatively easy" compared to all known hard examples for the (1, +k)-BPs. We introduce the first technique for proving exponential lower bounds for the (1, +k)-BPs on Searchφ. To do it we combine a well-known technique for proving lower bounds on the size of branching programs [12,21,22] with the modification of the "closure" technique [1,3]. In contrast with most Resolution lower bounds, our technique uses not only "local" properties of the formula, but also a "global" structure. Our hard examples are based on the Flow formulas introduced in [3].
具有有界重复和流公式的分支程序
受限分支程序捕获各种复杂性度量,如图灵机中的空间或证明系统中的证明长度。在本文中,我们重点研究了Lovasz等人[14]发现的在证明复杂度方面的应用,他们证明了“不满足子句搜索问题”(Searchφ)的正则解析和读一次分支程序之间的等价性。这种联系被广泛应用,特别是最近Atserias等人关于正则解中的团问题的突破性成果[5]。我们研究了具有有界重复的分支规划,即所谓的(1,+k)- bp (Sieling[21])在Searchφ问题中的应用。一方面,它是一次读取分支程序的自然泛化。另一方面,该模型提供了一个强大的证明系统,可以有效地证明大量难以解决的公式的不满足性(Knop[13])。与所有已知的(1,+k)- bp的困难示例相比,我们处理的Searchφ“相对容易”。我们介绍了证明Searchφ上(1,+k)- bp的指数下界的第一种技术。为了做到这一点,我们将一种众所周知的证明分支程序大小下界的技术[12,21,22]与“闭包”技术的修改[1,3]结合起来。与大多数分辨率下界相比,我们的技术不仅使用公式的“局部”属性,而且还使用“全局”结构。我们的硬示例基于[3]中介绍的Flow公式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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