A Generalized Method for Proving Polynomial Calculus Degree Lower Bounds

被引:18
作者
Miksa, Mladen [1 ]
Nordstrom, Jakob [1 ]
机构
[1] KTH Royal Inst Technol, SE-10044 Stockholm, Sweden
来源
30TH CONFERENCE ON COMPUTATIONAL COMPLEXITY (CCC 2015) | 2015年 / 33卷
基金
瑞典研究理事会; 欧洲研究理事会;
关键词
Proof complexity; polynomial calculus; polynomial calculus resolution; PCR; degree; size; functional pigeonhole principle; lower bound; RESOLUTION LOWER BOUNDS; HARD EXAMPLES; COMPLEXITY;
D O I
10.4230/LIPIcs.CCC.2015.467
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We study the problem of obtaining lower bounds for polynomial calculus (PC) and polynomial calculus resolution (PCR) on proof degree, and hence by [Impagliazzo et al. '99] also on proof size. [Alekhnovich and Razborov '03] established that if the clause-variable incidence graph of a CNF formula F is a good enough expander, then proving that F is unsatisfiable requires high PC/PCR degree. We further develop the techniques in [AR03] to show that if one can "cluster" clauses and variables in a way that "respects the structure" of the formula in a certain sense, then it is sufficient that the incidence graph of this clustered version is an expander. As a corollary of this, we prove that the functional pigeonhole principle (FPHP) formulas require high PC/PCR degree when restricted to constant-degree expander graphs. This answers an open question in [Razborov '02], and also implies that the standard CNF encoding of the FPHP formulas require exponential proof size in polynomial calculus resolution. Thus, while Onto-FPHP formulas are easy for polynomial calculus, as shown in [Riis '93], both FPHP and Onto-PHP formulas are hard even when restricted to bounded-degree expanders.
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页码:467 / 487
页数:21
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