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arXiv 1406.2271math.CO
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关于固定Laplacian矩阵的最小Eigenvalue

On the Smallest Eigenvalue of Grounded Laplacian Matrices

Mohammad Pirani, Shreyas Sundaram

摘要:

我们提供了上界和下界上的最小特征值的接地拉普拉斯矩阵(这是通过删除特定的行和列的拉普拉斯矩阵的给定图获得的矩阵)。上界和下界之间的间隙取决于与接地拉普拉斯算子的最小特征值相对应的特征向量的最小和最大分量的比率。我们提供了一个图论上的这个比率的界限,并随后获得了严格的特征值的最小特征值的某些类别的图。具体来说,对于Erdos Renyi随机图,我们表明,当一个(足够小)集$S$的行和列从拉普拉斯算子,并添加一个边缘的概率$p$是足够大的,接地拉普拉斯算子的最小特征值渐近几乎肯定接近$|S|p$。我们还表明,随机$d$ -正则图与一个单一的行和列删除,最小的特征值是$Θ(\frac{d}{n})$。我们的边界有应用程序的收敛速度在连续时间和离散时间的一致性动力学与顽固或领导节点的研究。

英文摘要:

We provide upper and lower bounds on the smallest eigenvalue of grounded Laplacian matrices (which are matrices obtained by removing certain rows and columns of the Laplacian matrix of a given graph). The gap between the upper and lower bounds depends on the ratio of the smallest and largest components of the eigenvector corresponding to the smallest eigenvalue of the grounded Laplacian. We provide a graph-theoretic bound on this ratio, and subsequently obtain a tight characterization of the smallest eigenvalue for certain classes of graphs. Specifically, for Erdos-Renyi random graphs, we show that when a (sufficiently small) set $S$ of rows and columns is removed from the Laplacian, and the probability $p$ of adding an edge is sufficiently large, the smallest eigenvalue of the grounded Laplacian asymptotically almost surely approaches $|S|p$. We also show that for random $d$-regular graphs with a single row and column removed, the smallest eigenvalue is $Θ(\frac{d}{n})$. Our bounds have applications to the study of the convergence rate in continuous-time and discrete-time consensus dynamics with stubborn or leader nodes.

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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