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We give a new proof for an equality of certain max-min and min-max approximation problems involving normal matrices. The previously published proofs of this equality apply tools from matrix theory, (analytic) optimization theory and…

Numerical Analysis · Mathematics 2013-10-23 Jörg Liesen , Petr Tichý

Spectral clustering is a technique that clusters elements using the top few eigenvectors of their (possibly normalized) similarity matrix. The quality of spectral clustering is closely tied to the convergence properties of these principal…

Machine Learning · Statistics 2017-09-05 Purnamrita Sarkar , Peter J. Bickel

In the first part of this paper, the main concern is with smoothness properties of the boundary of the pseudospectrum of a matrix polynomial. In the second part, results are obtained concerning the number of connected components of…

Spectral Theory · Mathematics 2007-05-23 Lyonell Boulton , Peter Lancaster , Panayiotis Psarrakos

A seminal result due to Wall states that if $x$ is normal to a given base $b$ then so is $rx+s$ for any rational numbers $r,s$ with $r\neq 0$. We show that a stronger result is true for normality with respect to the continued fraction…

Number Theory · Mathematics 2019-02-20 Joseph Vandehey

W.E. Roth (1952) proved that the matrix equation $AX-XB=C$ has a solution if and only if the matrices $\left[\begin{matrix}A&C\\0&B\end{matrix}\right]$ and $\left[\begin{matrix}A&0\\0&B\end{matrix}\right]$ are similar. A. Dmytryshyn and B.…

Representation Theory · Mathematics 2017-04-18 Andrii Dmytryshyn , Vyacheslav Futorny , Tetiana Klymchuk , Vladimir V. Sergeichuk

In this short note, we propose to extend differentiability (with respect to a multidimensional parameter) of a normalized eigenfunction associated to the simple, dominating eigenvalue of the weighted transfer operator for a uniformly…

Dynamical Systems · Mathematics 2018-10-12 Julien Sedro

Consider an $n \times n$ matrix polynomial $P(\lambda)$. An upper bound for a spectral norm distance from $P(\lambda)$ to the set of $n \times n$ matrix polynomials that have a given scalar $\mu\in\mathbb{C}$ as a multiple eigenvalue was…

Numerical Analysis · Mathematics 2014-10-14 E. Kokabifar , G. B. Loghmani , P. J. Psarrakos

The conditions determining that two triangles are congruent play a basic role in planimetry. By comparing not congruent triangles with respect to given sets of corresponding elements it is important to discover if they have any common…

History and Overview · Mathematics 2015-12-18 Vesselka Mihova , Julia Ninova

Let $A$ and $B$ be two -non necessarily bounded- normal operators. We give new conditions making their product normal. We also generalize a result by Deutsch et al on normal products of matrices.

Functional Analysis · Mathematics 2012-05-28 Mohammed Hichem Mortad , Khaldia Madani

This paper establishes a variant of Stewart's theorem (Theorem~6.4 of Stewart, {\em SIAM Rev.}, 15:727--764, 1973) for the singular subspaces associated with the SVD of a matrix subject to perturbations. Stewart's original version uses both…

Numerical Analysis · Mathematics 2024-06-12 Ren-Cang Li , Ninoslav Truhar , Lei-Hong Zhang

The standard theorem for regular stochastic matrices is generalized to matrices with no sign restriction on the entries. The condition that column sums be equal to 1 is kept, but the regularity condition is replaced by a condition on the…

Rings and Algebras · Mathematics 2007-09-05 Branko Ćurgus , Robert I. Jewett

We give an efficient algorithm which can obtain a relative error approximation to the spectral norm of a matrix, combining the power iteration method with some techniques from matrix reconstruction which use random sampling.

Data Structures and Algorithms · Computer Science 2011-04-13 Malik Magdon-Ismail

A new sufficient condition for a list of real numbers to be the spectrum of a symmetric doubly stochastic matrix is presented; this is a contribution to the classical spectral inverse problem for symmetric doubly stochastic matrices that is…

Spectral Theory · Mathematics 2020-01-27 Michal Gnacik , Tomasz Kania

Almost-commuting matrices with respect to the normalized Hilbert-Schmidt norm are considered. Normal almost commuting matrices are proved to be near commuting.

Algebraic Geometry · Mathematics 2010-02-17 Lev Glebsky

In quant-ph/0205017 v1 Chen, Wu and Yang formulated a necessary separability criterion based on a realignment method for matrices. This note is to point out that this criterion is identical to the necessary cross norm criterion previously…

Quantum Physics · Physics 2007-05-23 Oliver Rudolph

In 2003, van Dam and Haemers posed a fundamental question in spectral graph theory: does there exist a ``sensible'' matrix whose spectrum determines a random graph up to isomorphism? This paper introduces the class of {\em natural graph…

Combinatorics · Mathematics 2026-02-03 Ziqing Xiang

In this paper we investigate the spectral norm for circulant matrices, whose entries are modified Fibonacci numbers and Lucas numbers. We obtain the identity estimations for the spectral norms. Some numerical test results are listed to…

Numerical Analysis · Mathematics 2026-05-29 Jianwei Zhou , Zhaolin Jiang

It is known that any symmetric matrix $M$ with entries in $\R[x]$ and which is positive semi-definite for any substitution of $x\in\R$, has a Smith normal form whose diagonal coefficients are constant sign polynomials in $\R[x]$. We…

Rings and Algebras · Mathematics 2009-09-09 Ronan Quarez

We investigate conditions for "simultaneous normalizability" of a family of reduced schemes, i.e., the normalization of the total space normalizes, fiber by fiber, each member of the family. The main result (under more general conditions)…

Algebraic Geometry · Mathematics 2007-06-13 Hung-Jen Chiang-Hsieh , Joseph Lipman

The normalized distance Laplacian matrix $\mathcal{D}^{\mathcal{L}}(G)$ of a graph $G$ is a natural generalization of the normalized Laplacian matrix, arising from the matrix of pairwise distances between vertices rather than the adjacency…

Combinatorics · Mathematics 2025-03-17 John Byrne , Jacob Johnston , Carl Schildkraut , Michael Tait
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