子空间夹角、Ritz值和图拉普拉斯谱变化的主化关系
Majorization for Changes in Angles Between Subspaces, Ritz Values, and Graph Laplacian Spectra
AI总结:
本文利用弱(次)主化不等式统一描述子空间夹角、Ritz值和图拉普拉斯谱的变化关系,并证明了两图拉普拉斯谱差的绝对值和不超过边差异数乘以顶点数。
摘要:
许多实向量之间的不等式关系可以简洁地表示为“弱(次)主化”关系。我们解释这些概念并将其应用于几个领域:子空间夹角、Ritz值以及图拉普拉斯谱,这些领域被证明具有惊人的关联性……基于将给定图的边拉普拉斯算子的特征值解释为完全图边拉普拉斯算子的Ritz值的可能性,我们提出了一个利用Ritz值弱主化结果进行拉普拉斯图谱比较的应用。我们证明$\sum_k |\lambda1_k - \lambda2_k| \leq n l$,其中$\lambda1_k$和$\lambda2_k$是两个具有相同$n$个顶点且边差异数为$l$的图的拉普拉斯谱的所有有序元素。
英文摘要:
Many inequality relations between real vector quantities can be succinctly expressed as "weak (sub)majorization" relations. We explain these ideas and apply them in several areas: angles between subspaces, Ritz values, and graph Laplacian spectra, which we show are all surprisingly related... An application of our Ritz values weak majorization result for Laplacian graph spectra comparison is suggested, based on the possibility to interpret eigenvalues of the edge Laplacian of a given graph as Ritz values of the edge Laplacian of the complete graph. We prove that $ \sum_k |\lambda1_k - \lambda2_k| \leq n l,$ where $\lambda1_k$ and $\lambda2_k$ are all ordered elements of the Laplacian spectra of two graphs with the same $n$ vertices and with $l$ equal to the number of differing edges.
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。