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Uniform Circuits, Lower Bounds, and QBF Algorithms

机译:均匀电路,下界和QBF算法

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We explore the relationships between circuit complexity, the complexity of generating circuits, and circuit-analysis algorithms. Our results can be roughly divided into three parts: 1. Lower Bounds Against Medium-Uniform Circuits. Informally, a circuit class is ``medium uniform'' if it can be generated by an algorithmic process that is somewhat complex but not infeasible. We prove several unconditional lower bounds against medium uniform circuit classes, including - For every k, PP -uniform SIZE(nk). Namely, for any k, there is some language LP such that if size O(nk) circuits for L exist, they take super-polynomial time to generate. - For every k, LOGSPACE does not have LOGSPACE-uniform branching programs of size nk. - For every k, NP does not have PNP-uniform circuits of size nk. - For every k, either P does not have non-uniform circuits of size nk, or QBF (the language of true quantified Boolean formulae) does not have P-uniform branching programs of size 2no(1). 2. Eliminating Non-Uniformity. We complement these results by proving a ``uniformization'' lemma for NC1, showing that any simulation of NC1 in ACC0poly or TC0poly can be transformed into a uniform simulation using small advice. This lemma can be used to simplify part of the proof that faster SAT algorithms imply NEXP circuit lower bounds, and show that a nondeterministic 2n?(logn)-time algorithm for the following promise problem suffices for proving NEXP lower bounds against TC0: 'given a TC0 circuit C of nO(1) size which is promised to either be unsatisfiable or have at least 2n?1 satisfying assignments, determine which is the case.' We also use this lemma to prove that if NC1ACC0poly , then for all kc0 , the validity of quantified Boolean formulas (QBF) of size nk on n variables can be decided in deterministic time O(2nnc) . 3. The complexity of QBF. Finally, we study the time complexity of QBF itself, and its application to lower bounds. As a partial converse to the above results, we show that if for each kc0 , the validity of quantified Boolean CNFs of size nk with at most klogn alternations can be decided in time 2nnc , then NEXPNC1poly . We also show that the exponential time complexities of quantified k-CNF and quantified (unrestricted) formulas are essentially identical. As a consequence, if quantified 3CNF formulas of n variables and poly(n) size can be decided in 2n?n12+ time deterministically (for some 0) then NEXPNC1poly . (Compare with the 3SAT problem, where 14n-time deterministic algorithms are known.) This extends the recent connections of Williams between SAT algorithms and circuit lower bounds, to QBF algorithms.
机译:我们探讨了电路复杂性,生成电路的复杂性和电路分析算法之间的关系。我们的结果可以大致分为三个部分:1.降低中等均匀电路的边界。非正式地,如果可以通过某种程度上复杂但并非不可行的算法过程来生成电路类别,则该电路类别为``中等统一''类别。我们证明了针对中等均匀电路类别的几个无条件下界,包括-对于每个k,PP-均匀SIZE(nk)。即,对于任何k,都有某种语言LP,使得如果存在L的大小O(nk)电路,它们将花费超多项式时间来生成。 -对于每k,LOGSPACE没有大小为nk的LOGSPACE统一分支程序。 -对于每k,NP没有大小为nk的PNP均匀电路。 -对于每k,P都不具有大小为nk的非均匀电路,或者QBF(真量化布尔表达式的语言)不具有大小为2no(1)的P均匀分支程序。 2.消除不均匀性。我们通过证明NC1的``均匀化''引理来补充这些结果,表明在ACC0poly或TC0poly中对NC1的任何模拟都可以使用少量建议转换为统一模拟。该引理可用于简化证明较快的SAT算法隐含NEXP电路下限的部分证明,并证明针对以下承诺问题的不确定2n?(logn)-时间算法足以证明NEXP针对TC0的下界:一个nO(1)大小的TC0电路C可能不满足要求,或者至少满足2n?1个令人满意的分配,确定是哪种情况。我们还使用该引理证明,如果NC1ACC0poly,则对于所有kc0,可以在确定的时间O(2nnc)中确定n个变量上大小为nk的量化布尔公式(QBF)的有效性。 3. QBF的复杂性。最后,我们研究了QBF本身的时间复杂度及其在下界的应用。作为与上述结果的部分相反的结果,我们表明,对于每个kc0,可以在2nnc的时间内确定大小为nk且最多klogn交替的布尔布尔CNF的有效性,然后确定NEXPNC1poly。我们还表明,量化的k-CNF和量化的(无限制的)公式的指数时间复杂度基本相同。结果,如果可以在2n?n12 +时间中确定性地(对于0)确定n个变量和poly(n)大小的量化3CNF公式,则NEXPNC1poly。 (与3SAT问题比较,已知14n次确定性算法。)这将Williams在SAT算法和电路下限之间的最新联系扩展到QBF算法。

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