首页> 外文会议>27th Biennial Mechanisms and Robotics Conference >EIGENVALUE AND EIGENVECTOR INFORMATION OF GRAPHS AND THEIR VALIDITY IN DETECTION OF GRAPH ISOMORPHISM
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EIGENVALUE AND EIGENVECTOR INFORMATION OF GRAPHS AND THEIR VALIDITY IN DETECTION OF GRAPH ISOMORPHISM

机译:图的特征值和特征向量信息及其在图形同构检测中的有效性

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Detection of graph isomorphism (GI) has been widely used in many fields in science and engineering. Currently, a potential application of GI detection could be in molecular structure design for microelectromechanical systems and nano-systems. In this paper, we discuss the relationship between graphs and their eigenvalues as well as unique eigenvectors. We prove that the graphs having all distinct eigenvalues are isomorphic if and only if they have the same graph spectrum and the equivalent eigenvectors. The graphs having coincident eigenvalues might be isomorphic if they have the same graph spectrum and the equivalent unique eigenvectors. Further, a convergent recursive procedure is given to subdivide a group-to-group mapping once appeared in the graphs having coincident eigenvalues to seek potential one-to-one mappings so as to determining if the graphs are isomorphic.
机译:图同构(GI)的检测已在科学和工程学的许多领域中广泛使用。当前,GI检测的潜在应用可能是在微机电系统和纳米系统的分子结构设计中。在本文中,我们讨论了图与其特征值以及唯一特征向量之间的关系。我们证明了具有所有不同特征值的图是同构的,当且仅当它们具有相同的图谱和等效的特征向量时。具有一致特征值的图如果具有相同的图谱和等效的唯一特征向量,则可能是同构的。此外,给出收敛递归过程以细分曾经出现在具有一致特征值的图中的组到组映射,以寻找潜在的一对一映射,从而确定这些图是否是同构的。

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