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Optimization of convex functions subject to eigenvalue constraints is intriguing because of peculiar analytical properties of eigenvalues, and is of practical interest because of wide range of applications in fields such as structural…

Numerical Analysis · Mathematics 2013-10-08 Emre Mengi

We describe properties of a Hermitian square matrix M in M_n(C) equivalent to that of having minimal quotient norm in the following sense: ||M|| <= ||M+D|| for all real diagonal matrices D in M_n(C) and || || the operator norm. These…

Operator Algebras · Mathematics 2011-04-20 Esteban Andruchow , Gabriel Larotonda , Lázaro Recht , Alejandro Varela

Let $\mathcal{H}$ be the Hermitian curve defined over a finite field $\mathbb{F}_{q^2}$. In this paper we complete the geometrical characterization of the supports of the minimum-weight codewords of the algebraic-geometry codes over…

Commutative Algebra · Mathematics 2018-12-18 Chiara Marcolla , Margherita Roggero

We study functions defined on the vertices of the Hamming graphs $H(n,q)$. The adjacency matrix of $H(n,q)$ has $n+1$ distinct eigenvalues $n(q-1)-q\cdot i$ with corresponding eigenspaces $U_{i}(n,q)$ for $0\leq i\leq n$. In this work, we…

Combinatorics · Mathematics 2021-11-29 Alexandr Valyuzhenich , Konstantin Vorob'ev

We study the minimality of $n\times n$ Hermitian matrices $A$ respect to a $C^*$-subalgebra $\mathcal{B}$ of $M_n(\mathbb{C})$ in the spectral norm, that is \[\|A\|\leq \|A+B\|,\ \text{ for every } B\in \mathcal{B}.\] We generalize the…

Functional Analysis · Mathematics 2026-04-20 Tamara Bottazzi , Alejandro Varela

For a given class of structured matrices $\mathbb S$, we find necessary and sufficient conditions on vectors $x,w\in \C^{n+m}$ and $y,z \in \C^{n}$ for which there exists $\Delta=[\Delta_1~\Delta_2]$ with $\Delta_1 \in \mathbb S$ and…

Optimization and Control · Mathematics 2022-08-29 Mohit Kumar Baghel , Punit Sharma

Subspace iterations are used to minimise a generalised Ritz functional of a large, sparse Hermitean matrix. In this way, the lowest $m$ eigenvalues are determined. Tests with $1 \leq m \leq 32$ demonstrate that the computational cost (no.…

High Energy Physics - Lattice · Physics 2009-10-28 B. Bunk

Nondegenerate covariance, correlation and spectral density matrices are necessarily symmetric or Hermitian and positive definite. The main contribution of this paper is the development of statistical data depths for collections of Hermitian…

Methodology · Statistics 2019-11-12 Joris Chau , Hernando Ombao , Rainer von Sachs

The halfspace depth is a well studied tool of nonparametric statistics in multivariate spaces, naturally inducing a multivariate generalisation of quantiles. The halfspace depth of a point with respect to a measure is defined as the infimum…

Methodology · Statistics 2024-09-30 Dušan Pokorný , Petra Laketa , Stanislav Nagy

Given a diagonalizable $N\times N$ matrix $H$, whose non-degenerate spectrum consists of $p$ pairs of complex conjugate eigenvalues and additional $N-2p$ real eigenvalues, we determine all metrics $M$, of all possible signatures, with…

Mathematical Physics · Physics 2022-01-20 Joshua Feinberg , Miloslav Znojil

We consider the minimization or maximization of the $J$th largest eigenvalue of an analytic and Hermitian matrix-valued function, and build on Mengi et al. (2014, SIAM J. Matrix Anal. Appl., 35, 699-724). This work addresses the setting…

Numerical Analysis · Mathematics 2017-06-19 Fatih Kangal , Karl Meerbergen , Emre Mengi , Wim Michiels

In this work, our aim is to obtain conditions to assure polynomial approximation in Hilbert spaces $L^{2}(\mu)$, with $\mu$ a compactly supported measure in the complex plane, in terms of properties of the associated moment matrix to the…

Functional Analysis · Mathematics 2019-10-28 Carmen Escribano , Raquel Gonzalo , Emilio Torrano

We show that the class of Lipschitz-free spaces over closed subsets of any complete metric space $M$ is closed under arbitrary intersections, improving upon the previously known finite-diameter case. This allows us to formulate a general…

Functional Analysis · Mathematics 2022-03-16 Ramón J. Aliaga , Eva Pernecká , Colin Petitjean , Antonín Procházka

Given a nonlinear matrix-valued function $F(\lambda)$ and approximate eigenpairs $(\lambda_i, v_i)$, we discuss how to determine the smallest perturbation $\delta F$ such that $[F + \delta F](\lambda_i) v_i = 0$; we call the distance…

Numerical Analysis · Mathematics 2025-02-27 Miryam Gnazzo , Leonardo Robol

In this paper we discuss the geometry of homogeneous spaces witch are almost Hermitian submanifolds of flag manifolds. We prove that such spaces are necessarily minimal submanifolds and in the case where these submanifolds are also flag…

Differential Geometry · Mathematics 2024-06-19 Neiton Pereira da Silva

We consider the uniform approximation of the smallest eigenvalue of a large parameter-dependent Hermitian matrix by that of a smaller counterpart obtained through projections. The projection subspaces are constructed iteratively by means of…

Numerical Analysis · Mathematics 2026-01-16 Mattia Manucci , Emre Mengi , Nicola Guglielmi

We first consider the problem of approximating a few eigenvalues of a rational matrix-valued function closest to a prescribed target. It is assumed that the proper rational part of the rational matrix-valued function is expressed in the…

Numerical Analysis · Mathematics 2022-01-10 Rifqi Aziz , Emre Mengi , Matthias Voigt

Conjugation covariants of matrices are applied to study the real algebraic variety consisting of complex Hermitian matrices with a bounded number of distinct eigenvalues. A minimal generating system of the vanishing ideal of degenerate…

Representation Theory · Mathematics 2013-02-22 M. Domokos

In this paper, we formally investigate two mathematical aspects of Hermite splines which translate to features that are relevant to their practical applications. We first demonstrate that Hermite splines are maximally localized in the sense…

Numerical Analysis · Mathematics 2019-02-11 Julien Fageot , Shayan Aziznejad , Michael Unser , Virginie Uhlmann

A flag is a sequence of nested subspaces. Flags are ubiquitous in numerical analysis, arising in finite elements, multigrid, spectral, and pseudospectral methods for numerical PDE; they arise in the form of Krylov subspaces in matrix…

Optimization and Control · Mathematics 2019-08-08 Ke Ye , Ken Sze-Wai Wong , Lek-Heng Lim
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