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The First Two Largest Eigenvalues of Laplacian, Spectral Gap Problem and Cheeger Constant of Graphs

机译:拉普拉斯的前两个最大特征值,光谱差距问题和图形的Cheeger常数

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We show how the first two largest eigenvalues of Laplacian of a graph or smooth surface can be used to estimate the Cheeger constant of the graph. Particularly, we consider the problem of separating the graph into two large components of approximately equal volumes by making a small cut. This is the idea of Cheeger constant of a graph, which we want to relate to the spectral gap (the difference between the moduli of the first two largest eigenvalues of a Laplacian). We shall use Rayleigh variational characterization of the eigenvalues of the Laplacian to obtain the first two largest eigenvalues. The study reveals that spectral gap of a graph Γ correlates with the Cheeger constant h_r of the graph. All our results are illustrated by some simple examples to give a clear insight of the concepts.
机译:我们展示了图形或光滑表面的拉普拉斯的前两个最大特征值如何用于估计图表的杂交常数。特别是,我们考虑通过制造小切割将图形分成两种大量成分的问题。这是一个图形的ineger常数的想法,我们希望与光谱间隙(Laplacian的前两个最大特征值的模数之间的差异有关。我们将使用拉普利亚人的特征值的瑞利变分特征来获得前两个最大的特征值。该研究表明,曲线图γ的光谱间隙与图形的夹簧常数H_R相关。我们的所有结果都是通过一些简单的例子来说明的,以便清楚地了解概念。

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