图三角形化问题的一般复杂性

IF 0.2 Q4 MATHEMATICS, APPLIED
A. Rybalov
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引用次数: 0

摘要

2003年,A. Miasnikov, V. Kapovich, P. Schupp和V. Shpilrain提出了算法问题的一般情况方法。这种方法研究算法在典型(几乎所有)输入上的行为,而忽略其他输入。本文研究了图三角剖分问题的一般复杂度。这个问题如下。给定一个有3n个顶点的有限简单图,判断图的顶点是否可以划分为n个三元素集,每个三元素集包含由原始图的边连接的顶点(即三角形)。这个问题的np完备性在1974年由Shaffer证明,并在M. Garey和D. Johnson的经典专著中提到。证明了在P≠NP和P = BPP条件下,不存在多项式强泛型算法。强泛型算法解决的问题不是输入的全部集合,而是频率序列随着大小的增加指数收敛于1的子集。为了证明这个定理,我们使用了一般放大的方法,这种方法允许人们从经典意义上的困难问题构造一般困难问题。该方法的主要组成部分是克隆技术,它将一个问题的输入组合成足够大的等效输入集。等价的理解是,它们的问题以相似的方式解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The generic complexity of the graph triangulation problem
Generic-case approach to algorithmic problems was suggested by A. Miasnikov, V. Kapovich, P. Schupp, and V. Shpilrain in 2003. This approach studies behavior of an algorithm on typical (almost all) inputs and ignores the rest of inputs. In this paper, we study the generic complexity of the graph triangulation problem. This problem is as follows. Given a finite simple graph with 3n vertices, determine whether the vertices of the graph can be divided into n three-element sets, each of which contains vertices connected by edges of the original graph (that is, they are triangles). NP-completeness of this problem was proved by Shaffer in 1974 and is mentioned in the classic monograph by M. Garey and D. Johnson. We prove that under the conditions P ≠ NP and P = BPP there is no polynomial strongly generic algorithm for this problem. A strongly generic algorithm solves a problem not on the whole set of inputs, but on a subset whose frequency sequence converges exponentially to 1 with increasing size. To prove the theorem, we use the method of generic amplification, which allows one to construct generically hard problems from the problems that are hard in the classical sense. The main component of this method is the cloning technique, which combines the inputs of a problem together into sufficiently large sets of equivalent inputs. Equivalence is understood in the sense that the problem for them is solved in a similar way.
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来源期刊
Prikladnaya Diskretnaya Matematika
Prikladnaya Diskretnaya Matematika MATHEMATICS, APPLIED-
CiteScore
0.60
自引率
50.00%
发文量
0
期刊介绍: The scientific journal Prikladnaya Diskretnaya Matematika has been issued since 2008. It was registered by Federal Control Service in the Sphere of Communications and Mass Media (Registration Witness PI № FS 77-33762 in October 16th, in 2008). Prikladnaya Diskretnaya Matematika has been selected for coverage in Clarivate Analytics products and services. It is indexed and abstracted in SCOPUS and WoS Core Collection (Emerging Sources Citation Index). The journal is a quarterly. All the papers to be published in it are obligatorily verified by one or two specialists. The publication in the journal is free of charge and may be in Russian or in English. The topics of the journal are the following: 1.theoretical foundations of applied discrete mathematics – algebraic structures, discrete functions, combinatorial analysis, number theory, mathematical logic, information theory, systems of equations over finite fields and rings; 2.mathematical methods in cryptography – synthesis of cryptosystems, methods for cryptanalysis, pseudorandom generators, appreciation of cryptosystem security, cryptographic protocols, mathematical methods in quantum cryptography; 3.mathematical methods in steganography – synthesis of steganosystems, methods for steganoanalysis, appreciation of steganosystem security; 4.mathematical foundations of computer security – mathematical models for computer system security, mathematical methods for the analysis of the computer system security, mathematical methods for the synthesis of protected computer systems;[...]
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