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arXiv 2011.04778cs.CC
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图同态多项式:算法与复杂性

Graph Homomorphism Polynomials: Algorithms and Complexity

Balagopal Komarath, Anurag Pandey, C. S. Rahul

摘要:

我们研究同态多项式,这是多项式,枚举所有同态从模式图$H$到$n$ -顶点图。这些多项式最近受到了很多关注,因为它们在计算和检测图模式的几个新算法中起着至关重要的作用,并且还用于获得代数复杂性类$\mathsf{VBP}$、$\mathsf{VP}$和$\mathsf{VNP}$的完备自然多项式族。我们发现,在单调设置,公式的复杂性,ABP复杂性,电路复杂性的多项式族的确切特征分别由树深,路径宽度,树宽的模式图。此外,我们建立了一个单一的,统一的框架,使用我们的表征,收集几个已知的结果,通过不同的方法独立获得。例如,我们达到超多项式分离电路,ABPs,和公式在单调设置,其中多项式家庭分离类都对应于充分研究的组合问题。此外,我们的证明重新发现这些模型之间的细粒度分离的常次数多项式。此外,产生新的空间-时间有效的算法的几个模式检测和计数问题的表征。

英文摘要:

We study homomorphism polynomials, which are polynomials that enumerate all homomorphisms from a pattern graph $H$ to $n$-vertex graphs. These polynomials have received a lot of attention recently for their crucial role in several new algorithms for counting and detecting graph patterns, and also for obtaining natural polynomial families which are complete for algebraic complexity classes $\mathsf{VBP}$, $\mathsf{VP}$, and $\mathsf{VNP}$. We discover that, in the monotone setting, the formula complexity, the ABP complexity, and the circuit complexity of such polynomial families are exactly characterized by the treedepth, the pathwidth, and the treewidth of the pattern graph respectively. Furthermore, we establish a single, unified framework, using our characterization, to collect several known results that were obtained independently via different methods. For instance, we attain superpolynomial separations between circuits, ABPs, and formulas in the monotone setting, where the polynomial families separating the classes all correspond to well-studied combinatorial problems. Moreover, our proofs rediscover fine-grained separations between these models for constant-degree polynomials. The characterization additionally yields new space-time efficient algorithms for several pattern detection and counting problems.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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