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We prove upper bounds on the order of convergence of lattice based algorithms for numerical integration in function spaces of dominating mixed smoothness on the unit cube with homogeneous boundary condition. More precisely, we study…

Numerical Analysis · Mathematics 2019-08-15 Josef Dick , Friedrich Pillichshammer , Kosuke Suzuki , Mario Ullrich , Takehito Yoshiki

We show that the maximal determinant D(n) for $n \times n$ ${\pm 1}$-matrices satisfies $R(n) := D(n)/n^{n/2} \ge \kappa_d > 0$. Here $n^{n/2}$ is the Hadamard upper bound, and $\kappa_d$ depends only on $d := n-h$, where $h$ is the maximal…

Combinatorics · Mathematics 2013-05-07 Richard P. Brent , Judy-anne H. Osborn , Warren D. Smith

For an $n\times n$ diagonally dominant matrix $T=(t_{i,j})_{n\times n}$ with positive elements satisfying certain bounding conditions, we propose to use a diagonal matrix $S=(s_{i,j})_{n\times n}$ to approximate the inverse of $T$, where…

Numerical Analysis · Mathematics 2019-02-05 Ting Yan

Consider an $N\times N$ Toeplitz matrix $T_N$ with symbol ${a }(\lambda) := \sum_{\ell=-d_2}^{d_1} a_\ell \lambda^\ell$, perturbed by an additive noise matrix $N^{-\gamma} E_N$, where the entries of $E_N$ are centered i.i.d.~random…

Probability · Mathematics 2020-07-27 Anirban Basak , Ofer Zeitouni

In this paper we develop algorithms for approximating matrix multiplication with respect to the spectral norm. Let A\in{\RR^{n\times m}} and B\in\RR^{n \times p} be two matrices and \eps>0. We approximate the product A^\top B using two…

Data Structures and Algorithms · Computer Science 2010-10-28 Avner Magen , Anastasios Zouzias

The condition number of solutions to full rank linear least-squares problem are shown to be given by an optimization problem that involves nuclear norms of rank 2 matrices. The condition number is with respect to the least-squares…

Numerical Analysis · Mathematics 2015-03-13 Joseph F. Grcar

We analyze a class of estimators based on convex relaxation for solving high-dimensional matrix decomposition problems. The observations are noisy realizations of a linear transformation $\mathfrak{X}$ of the sum of an approximately) low…

Machine Learning · Statistics 2012-08-09 Alekh Agarwal , Sahand N. Negahban , Martin J. Wainwright

Results on matrix canonical forms are used to give a complete description of the higher rank numerical range of matrices arising from the study of quantum error correction. It is shown that the set can be obtained as the intersection of…

Functional Analysis · Mathematics 2011-02-10 Chi-Kwong Li , Nung-Sing Sze

Let $\lambda$ be a complex number in the closed unit disc $\overline{\Bbb D}$, and $\cal H$ be a separable Hilbert space with the orthonormal basis, say, ${\cal E}=\{e_n:n=0,1,2,\cdots\}$. A bounded operator $T$ on $\cal H$ is called a…

Functional Analysis · Mathematics 2014-04-11 Mark C. Ho

We begin by showing that any $n \times n$ matrix can be decomposed into a sum of $n$ circulant matrices with periodic relaxations on the unit circle. This decomposition is orthogonal with respect to a Frobenius inner product, allowing…

Numerical Analysis · Mathematics 2022-09-29 Hariprasad M. , Murugesan Venkatapathi

This paper proposes lower bounds on a quantity called $L^p$-norm joint spectral radius, or in short, $p$-radius, of a finite set of matrices. Despite its wide range of applications to, for example, stability analysis of switched linear…

Optimization and Control · Mathematics 2016-11-04 Masaki Ogura , Victor M. Preciado , Raphaël Jungers

A Toeplitz matrix is one in which the matrix elements are constant along diagonals. The Fisher-Hartwig matrices are much-studied singular matrices in the Toeplitz family. The matrices are defined for all orders, $N$. They are parametrized…

Mathematical Physics · Physics 2015-05-13 Hui Dai , Zachary Geary , Leo P. Kadanoff

We determine the border ranks of tensors that could potentially advance the known upper bound for the exponent $\omega$ of matrix multiplication. The Kronecker square of the small $q=2$ Coppersmith-Winograd tensor equals the $3\times 3$…

Algebraic Geometry · Mathematics 2020-09-25 Austin Conner , Hang Huang , J. M. Landsberg

We show that the top eigenvalue of an $n\times n$ random symmetric Toeplitz matrix, scaled by $\sqrt{2n\log n}$, converges to the square of the $2\to4$ operator norm of the sine kernel.

Probability · Mathematics 2013-12-17 Arnab Sen , Bálint Virág

Very recently, Bai [Linear Algebra Appl., 681:150-186, 2024 \& Appl. Math. Lett., 166:109510, 2025] studied some concrete structures, and obtained essential algebraic and computational properties of the one-dimensional, two-dimensional and…

Rings and Algebras · Mathematics 2025-06-19 Aaisha Be , Nachiketa Mishra , Debasisha Mishra

The solutions of an indeterminate Hamburger moment problem can be parameterised using the Nevanlinna matrix of the problem. The entries of this matrix are entire functions of minimal exponential type, and any growth less than that can…

Classical Analysis and ODEs · Mathematics 2023-07-21 Raphael Pruckner , Jakob Reiffenstein , Harald Woracek

We study the question of finding the maximal determinant of matrices of odd order with entries {-1,1}. The most general upper bound on the maximal determinant, due to Barba, can only be achieved when the order is the sum of two consecutive…

Combinatorics · Mathematics 2007-05-23 William P. Orrick

Obtaining superlinear lower bounds on tensor rank is a major open problem in complexity theory. In this paper we propose a generalization of the approach used by Strassen in the proof of his 3n/2 border rank lower bound. Our approach…

Computational Complexity · Computer Science 2020-07-07 Pascal Koiran

In this work, we consider symmetric random Toeplitz matrices $T_n$ generated by i.i.d. zero mean random variables ${X_k}$ satisfying the moment conditions: $E|X_k|^2=1$ and $\E|X_1|^n \le n^{\sqrt{n}}$ for all $n\ge 3$. We prove that the…

Probability · Mathematics 2013-01-10 Malika Kharouf

This paper studies the problem of selecting a submatrix of a positive definite matrix in order to achieve a desired bound on the smallest eigenvalue of the submatrix. Maximizing this smallest eigenvalue has applications to selecting input…

Systems and Control · Computer Science 2017-09-08 Andrew Clark , Qiqiang Hou , Linda Bushnell , Radha Poovendran