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In this note we investigate the existence of flat orthogonal matrices, i.e. real orthogonal matrices with all entries having absolute value close to $\frac{1}{\sqrt{n}}$. Entries of $\pm \frac{1}{\sqrt{n}}$ correspond to Hadamard matrices,…

Combinatorics · Mathematics 2015-05-15 Philippe Jaming , Mate Matolcsi

Let $K$ be a field, $R=K[x, y]$ the polynomial ring and $\mathcal{M}(K)$ the set of all pairs of square matrices of the same size over $K.$ Pairs $P_1=(A_1,B_1)$ and $P_2=(A_2,B_2)$ from $\mathcal{M}(K)$ are called similar if…

Representation Theory · Mathematics 2024-08-09 Vitaliy Bondarenko , Anatoliy Petravchuk , Maryna Styopochkina

The aim of this work is to develop a fast algorithm for approximating the matrix function $f(A)$ of a square matrix $A$ that is symmetric and has hierarchically semiseparable (HSS) structure. Appearing in a wide variety of applications,…

Numerical Analysis · Mathematics 2024-02-28 Angelo A. Casulli , Daniel Kressner , Leonardo Robol

A real symmetric matrix (resp., tensor) is said to be copositive if the associated quadratic (resp., homogeneous) form is greater than or equal to zero over the nonnegative orthant. The problem of detecting their copositivity is NP-hard.…

Optimization and Control · Mathematics 2017-11-13 Jiawang Nie , Zi Yang , Xinzhen Zhang

Weak similarities form a special class of mappings between semimetric spaces. Two semimetric spaces $X$ and $Y$ are weakly similar if there exists a weak similarity $\Phi\colon X\to Y$. We find a structural characteristic of finite…

General Topology · Mathematics 2024-12-31 Evgeniy Petrov

In this note, we define a Gaussian probability distribution over matrices. We prove some useful properties of this distribution, namely, the fact that marginalization, conditioning, and affine transformations preserve the matrix Gaussian…

Probability · Mathematics 2018-06-22 Shane Barratt

Let $A$ be an $m\times m$ positive semidefinite block matrix with each block being $n$-square. We write $\mathrm{tr}_1$ and $\mathrm{tr}_2$ for the first and second partial trace, respectively. In this paper, we prove the following…

Functional Analysis · Mathematics 2021-12-23 Yongtao Li , Weijun Liu , Yang Huang

The integral version of the fractional Laplacian on a bounded domain is discretized by a Galerkin approximation based on piecewise linear functions on a quasi-uniform mesh. We show that the inverse of the associated stiffness matrix can be…

Numerical Analysis · Mathematics 2024-07-25 Michael Karkulik , Jens Markus Melenk

In this paper we consider the decomposition of positive semidefinite matrices as a sum of rank one matrices. We introduce and investigate the properties of various measures of optimality of such decompositions. For some classes of positive…

Functional Analysis · Mathematics 2022-02-03 Radu Balan , Kasso A. Okoudjou , Michael Rawson , Yang Wang , Rui Zhang

We study an elementary inequality supporting the classical Hermite-Hadamard inequality in the matrix setting. This leads to a number of interesting matrix inequalities such new Schatten p-norm estimates and new majorization

Functional Analysis · Mathematics 2022-01-05 Jean-Christophe Bourin , Eun-Young Lee

Matrix-valued polynomials in any finite number of freely noncommuting variables that enjoy certain canonical partial convexity properties are characterized, via an algebraic certificate, in terms of Linear Matrix Inequalities and Bilinear…

Functional Analysis · Mathematics 2023-03-01 Sriram Balasubramanian , Neha Hotwani , Scott McCullough

We describe the recursive algorithmic procedure to compute the stabilizers of the group of complex orthogonal matrices with respect to the action of similarity on the set of all symmetric matrices. Futhermore, lower bounds for dimensions of…

Algebraic Geometry · Mathematics 2020-09-23 Tadej Starčič

We define and study a new family of polytopes which are formed as convex hulls of partial alternating sign matrices. We determine the inequality descriptions, number of facets, and face lattices of these polytopes. We also study partial…

Combinatorics · Mathematics 2022-03-09 Dylan Heuer , Jessica Striker

A matrix-compression algorithm is derived from a novel isogenic block decomposition for square matrices. The resulting compression and inflation operations possess strong functorial and spectral-permanence properties. The basic observation…

Rings and Algebras · Mathematics 2022-11-01 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

We propose an algorithm for low rank matrix completion for matrices with binary entries which obtains explicit binary factors. Our algorithm, which we call TBMC (\emph{Tiling for Binary Matrix Completion}), gives interpretable output in the…

Numerical Analysis · Mathematics 2020-06-23 Melanie Beckerleg , Andrew Thompson

We offer a new proof of uniform convexity inequalities for the Finsler manifold of nonpositive curvature taken on the space of positive-semidefinite matrices with the weighted matrix geometric mean defining the geodesic between two points.…

Functional Analysis · Mathematics 2022-10-20 Victoria M Chayes

When a matrix A with n columns is known to be well approximated by a linear combination of basis matrices B_1,..., B_p, we can apply A to a random vector and solve a linear system to recover this linear combination. The same technique can…

Numerical Analysis · Mathematics 2011-10-20 Jiawei Chiu , Laurent Demanet

The main goal of this article is to present new types of inequalities refining and reversing inequalities of the harmonic mean of scalars and matrices. Furthermore, implementing the spectral decomposition of positive matrices, we present a…

Functional Analysis · Mathematics 2018-05-18 Mohammad Sababheh

We propose a numerical integrator for determining low-rank approximations to solutions of large-scale matrix differential equations. The considered differential equations are semilinear and stiff. Our method consists of first splitting the…

Numerical Analysis · Mathematics 2019-06-03 Alexander Ostermann , Chiara Piazzola , Hanna Walach

We present a conceptually simple and intuitive method to calculate and to measure the dissimilarities among 2D shapes. Several methods to interpret and to visualize the resulting dissimilarity matrix are presented and compared.

Computer Vision and Pattern Recognition · Computer Science 2022-11-10 Karel Zimmermann