English
Related papers

Related papers: Rational and real positive semidefinite rank can b…

200 papers

The paper proves sum-of-square-of-rational-function based representations (shortly, sosrf-based representations) of polynomial matrices that are positive semidefinite on some special sets: $\mathbb{R}^n;$ $\mathbb{R}$ and its intervals…

Optimization and Control · Mathematics 2019-03-29 Thanh-Hieu Le , Nhat-Thien Pham

This paper considers a restriction to non-negative matrix factorization in which at least one matrix factor is stochastic. That is, the elements of the matrix factors are non-negative and the columns of one matrix factor sum to 1. This…

Machine Learning · Statistics 2016-09-20 Christopher Adams

We investigate rank revealing factorizations of $m \times n$ polynomial matrices $P(\lambda)$ into products of three, $P(\lambda) = L(\lambda) E(\lambda) R(\lambda)$, or two, $P(\lambda) = L(\lambda) R(\lambda)$, polynomial matrices. Among…

Numerical Analysis · Mathematics 2024-10-04 Andrii Dmytryshyn , Froilán Dopico , Paul Van Dooren

We study linear PDE with constant coefficients. The constant rank condition on a system of linear PDEs with constant coefficients is often used in the theory of compensated compactness. While this is a purely linear algebraic condition, the…

Analysis of PDEs · Mathematics 2024-01-05 Marc Härkönen , Lisa Nicklasson , Bogdan Raiţă

Let \psi(x) be a polynomial with rational coefficients. Suppose that \psi has the positive leading coefficient and zero constant term. Let A be a set of positive integers with the positive upper density. Then there exist x,y\in A and a…

Number Theory · Mathematics 2007-11-08 Hongze Li , Hao Pan

We investigate compressibility of the dimension of positive semidefinite matrices while approximately preserving their pairwise inner products. This can either be regarded as compression of positive semidefinite factorizations of…

Quantum Physics · Physics 2016-05-06 Cyril J. Stark , Aram W. Harrow

Finite dimensional linear spaces (both complex and real) with indefinite scalar product [.,.] are considered. Upper and lower bounds are given for the size of an indecomposable matrix that is normal with respect to this scalar product in…

Functional Analysis · Mathematics 2007-05-23 Olga Holtz

Fixed-point logic with rank (FPR) is an extension of fixed-point logic with counting (FPC) with operators for computing the rank of a matrix over a finite field. The expressive power of FPR properly extends that of FPC and is contained in…

Computational Complexity · Computer Science 2020-08-20 Anuj Dawar , Gregory Wilsenach

The minimum rank problem for a (simple) graph $G$ is to determine the smallest possible rank over all real symmetric matrices whose $ij$th entry (for $i\neq j$) is nonzero whenever $\{i,j\}$ is an edge in $G$ and is zero otherwise. This…

Combinatorics · Mathematics 2014-10-09 Shaun Fallat , Leslie Hogben

Matrices of rank at most k are defined by the vanishing of polynomials of degree k + 1 in their entries (namely, their (k + 1)-times-(k + 1)-subdeterminants), regardless of the size of the matrix. We prove a qualitative analogue of this…

Algebraic Geometry · Mathematics 2015-01-14 Jan Draisma , Jochen Kuttler

In this article we study forbidden loci and typical ranks of forms with respect to the embeddings of $\mathbb P^1\times \mathbb P^1$ given by the line bundles $(2,2d)$. We introduce the Ranestad-Schreyer locus corresponding to supports of…

Algebraic Geometry · Mathematics 2018-03-16 Emanuele Ventura

We initiate the study of the binary and Boolean rank of $0,1$ matrices that have a small rank over the reals. The relationship between these three rank functions is an important open question, and here we prove that when the real rank $d$…

Combinatorics · Mathematics 2025-07-15 Michal Parnas , Adi Shraibman

The higher rank numerical range is closely connected to the construction of quantum error correction code for a noisy quantum channel. It is known that if a normal matrix $A \in M_n$ has eigenvalues $a_1, \..., a_n$, then its higher rank…

Functional Analysis · Mathematics 2011-02-10 Hwa-Long Gau , Chi-Kwong Li , Yiu-Tung Poon , Nung-Sing Sze

Conic linear programs, among them semidefinite programs, often behave pathologically: the optimal values of the primal and dual programs may differ, and may not be attained. We present a novel analysis of these pathological behaviors. We…

Optimization and Control · Mathematics 2017-02-22 Gabor Pataki

The paper explores the concept of the rank of a bicomplex matrix, delving into four distinct types of ranks and investigating conditions under which these ranks are equivalent. It also defines and analyzes the concept of idempotent row…

Rings and Algebras · Mathematics 2024-12-10 Amita , Mamta Amol Wagh , Suman Kumar , Akhil Prakash

The girth of a matrix is the least number of linearly dependent columns, in contrast to the rank which is the largest number of linearly independent columns. This paper considers the construction of {\it high-girth} matrices, whose…

Information Theory · Computer Science 2015-02-06 Emmanuel Abbe , Yuval Wigderson

The problem of finding a rank-one solution to a system of linear matrix equations arises from many practical applications. Given a system of linear matrix equations, however, such a low-rank solution does not always exist. In this paper, we…

Optimization and Control · Mathematics 2012-11-12 Yunbin Zhao , Masao Fukushima

We consider the following problem: Given a rational matrix $A \in \setQ^{m \times n}$ and a rational polyhedron $Q \subseteq\setR^{m+p}$, decide if for all vectors $b \in \setR^m$, for which there exists an integral $z \in \setZ^p$ such…

Optimization and Control · Mathematics 2008-01-29 Friedrich Eisenbrand , Gennady Shmonin

We study the problem of estimating a low-rank positive semidefinite (PSD) matrix from a set of rank-one measurements using sensing vectors composed of i.i.d. standard Gaussian entries, which are possibly corrupted by arbitrary outliers.…

Information Theory · Computer Science 2016-12-21 Yuanxin Li , Yue Sun , Yuejie Chi

We show how to compute a relative-error low-rank approximation to any positive semidefinite (PSD) matrix in sublinear time, i.e., for any $n \times n$ PSD matrix $A$, in $\tilde O(n \cdot poly(k/\epsilon))$ time we output a rank-$k$ matrix…

Data Structures and Algorithms · Computer Science 2019-01-04 Cameron Musco , David P. Woodruff