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arXiv 0912.0336math.FA
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矩阵的截范数与谱

Cut-norms and spectra of matrices

Vladimir Nikiforov

摘要:

本文的目的之一是解决Lovasz关于图的谱与割距之间关系的一个公开问题。本文从任意复矩阵的两种割范数与两个最大奇异值之间的几个不等式出发,推广了著名的图论Expander混合引理,并给出了它的一个迄今未知的逆引理,然后定义了埃尔米特矩阵的割距离,并分别定义了任意复矩阵的割距离;利用这些推广,我们给出了两个矩阵的相应特征值和奇异值之差的上界,从而解决了Lovasz问题。最后,我们推导出一个谱抽样定理,它非正式地指出,几乎所有的主子矩阵的实对称矩阵是谱相似的。

英文摘要:

One of the aims of this paper is to solve an open problem of Lovasz about relations between graph spectra and cut-distance. The paper starts with several inequalities between two versions of the cut-norm and the two largest singular values of arbitrary complex matrices, exteding, in particular, the well-known graph-theoretical Expander Mixing Lemma and giving a hitherto unknown converse of it. Next, cut-distance is defined for Hermitian matrices, and, separately, for arbitrary complex matrices; using these extensions, we give upper bounds on the difference of corresponding eigenvalues and singular values of two matrices, thus solving the problem of Lovasz. Finally, we deduce a spectral sampling theorem, which informally states that almost all principal submatrices of a real symmetric matrix are spectrally similar to it.

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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