Total nonpositivity of nonsingular matrices

In this paper, nonsingular totally nonpositive matrices are studied and new characterizations are provided in terms of the signs of minors with consecutive initial rows or consecutive initial columns. These characterizations extend an existing characterization that uses some restrictive hypotheses.     

A forbidden structure of ray nonsingular matrices

A complex square matrix is called a ray nonsingular matrix (RNS matrix) if its ray pattern implies that it is nonsingular. In this paper, a necessary condition for RNS matrices is provided by showing that if A=I−A(D)$A=I-A(D)$ is ray nonsingular, then the arc weighted digraph D contains no forbidden cycle chains.     

Some classes of nonsingular matrices and applications

Motivated by conditions that arise from results on mean first passage times matrices in Markov chains, we consider here two classes of real matrices whose elements satisfy some of these conditions, or variation thereof, and which result in the nonsingularity of their elements. The conditions are quite distinct from Ger?gorin circles-type conditions. Our results lead to a sufficient condition for matrices to have 1 as their unique positive eigenvalue.     

Counting nonsingular matrices with primitive row vectors

We give an asymptotic expression for the number of nonsingular integer $n\times n$ -matrices with primitive row vectors, determinant $k$ , and Euclidean matrix norm less than $T$ , as $T\rightarrow \infty $ . We also investigate the density of matrices with primitive rows in the space of matrices with determinant $k$ , and determine its asymptotics for large $k$ .     

Minimum deviation, quasi-LU factorization of nonsingular matrices

Not all matrices enjoy the existence of an LU factorization. For those that do not, a number of “repairs” are possible. For nonsingular matrices we offer here a permutation-free repair in which the matrix is factored , with and collectively as near as possible to lower and upper triangular (in a natural sense defined herein). Such factorization is not generally unique in any sense. In the process, we investigate further the structure of matrices without LU factorization and permutations that produce an LU factorization.     

The sparsity of Bruhat decomposition factors of nonsingular matrices

The paper analyzes the sparsity pattern of triangular factors of the reduced Bruhat decomposition of a non-singular matrix over a field, which is an alternative to the commonly used LU decomposition. Bounds for the length of the Bruhat permutation of a matrix providing upper bounds for the number of nonzero entries in the reduced triagular factor of its Bruhat decomposition are also presented. Bibliography: 6 titles. Translated by L. Yu. Kolotilina. Translated fromZapiski Nauchnykh Seminarov POMI, Vol. 202, 1992, pp. 5–17.     

Required nonzero patterns for nonsingular sign regular matrices

An n×n real matrix is called sign regular if, for each k(1?k?n), all its minors of order k have the same nonstrict sign. The zero entries which can appear in a nonsingular sign regular matrix depend on its signature because the signature can imply that certain entries are necessarily nonzero. The patterns for the required nonzero entries of nonsingular sign regular matrices are analyzed.     

Linear maps that preserve singular and nonsingular matrices

Let M (n,K) be the algebra of n × n matrices over an algebraically closed field K and T:M (n,K)→M (n,K) a linear transformation with the property that T maps nonsingular (singular) matrices to nonsingular (singular) matrices. Using some elementary facts from commutative algebra we show that T is nonsingular and maps singular matrices to singular matrices (T is nonsingular or T maps all matrices to singular matrices). Using these results we obtain Marcus and Moyl's characterization [T(x) = UXVorU^tXV for fixed U and V] from a result of Dieudonné's. Examples are given to show the hypothesis of algebraic closure in necessary.     

Structured preconditioners for nonsingular matrices of block two-by-two structures

For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of practical and efficient structured preconditioners through matrix transformation and matrix approximations. For the specific versions such as modified block Jacobi-type, modified block Gauss-Seidel-type, and modified block unsymmetric (symmetric) Gauss-Seidel-type preconditioners, we precisely describe their concrete expressions and deliberately analyze eigenvalue distributions and positive definiteness of the preconditioned matrices. Also, we show that when these structured preconditioners are employed to precondition the Krylov subspace methods such as GMRES and restarted GMRES, fast and effective iteration solvers can be obtained for the large sparse systems of linear equations with block two-by-two coefficient matrices. In particular, these structured preconditioners can lead to efficient and high-quality preconditioning matrices for some typical matrices from the real-world applications.

     

A problem of Mirsky concerning nonsingular doubly stochastic matrices

The paper presents a new constructive proof of a theorem of Hardy, Littlewood, and Polya relating vector majorization and doubly stochastic matrices. Conditions on the vectors which guarantee that the corresponding matrices will be direct sums are given. These two results are applied to solve the problem, posed by Mirsky, of characterizing those majorization relations for which there is a corresponding doubly stochastic matrix which is nonsingular.     

Relatively prime polynomials and nonsingular Hankel matrices over finite fields

The probability for two monic polynomials of a positive degree n with coefficients in the finite field Fq to be relatively prime turns out to be identical with the probability for an n×n Hankel matrix over Fq to be nonsingular. Motivated by this, we give an explicit map from pairs of coprime polynomials to nonsingular Hankel matrices that explains this connection. A basic tool used here is the classical notion of Bezoutian of two polynomials. Moreover, we give simpler and direct proofs of the general formulae for the number of m-tuples of relatively prime polynomials over Fq of given degrees and for the number of n×n Hankel matrices over Fq of a given rank.     

Spectral norm of random matrices

In this paper, we present a new upper bound for the spectral norm of symmetric random matrices with independent (but not necessarily identical) entries. Our results improve an earlier result of Füredi and Komlós. Research supported by an NSF CAREER award and by an Alfred P. Sloan fellowship.     

Limit distributions of random matrices

We study limit distributions of independent random matrices as well as limit joint distributions of their blocks under normalized partial traces composed with classical expectation. In particular, we are concerned with the ensemble of symmetric blocks of independent Hermitian random matrices which are asymptotically free, asymptotically free from diagonal deterministic matrices, and whose norms are uniformly bounded almost surely. This class contains symmetric blocks of unitarily invariant Hermitian random matrices whose asymptotic distributions are compactly supported probability measures on the real line. Our approach is based on the concept of matricial freeness which is a generalization of freeness in free probability. We show that the associated matricially free Gaussian operators provide a unified framework for studying the limit distributions of sums and products of independent rectangular random matrices, including non-Hermitian Gaussian matrices and matrices of Wishart type.     

Invertibility of symmetric random matrices

We study symmetric random matrices H, possibly discrete, with iid above‐diagonal entries. We show that H is singular with probability at most , and . Furthermore, the spectrum of H is delocalized on the optimal scale . These results improve upon a polynomial singularity bound due to Costello, Tao and Vu, and they generalize, up to constant factors, results of Tao and Vu, and Erdös, Schlein and Yau.Copyright © 2012 Wiley Periodicals, Inc. Random Struct. Alg., 44, 135‐182, 2014     

Eigenvalues of Euclidean random matrices

We study the spectral measure of large Euclidean random matrices. The entries of these matrices are determined by the relative position of n random points in a compact set Ω_n of ?^d. Under various assumptions, we establish the almost sure convergence of the limiting spectral measure as the number of points goes to infinity. The moments of the limiting distribution are computed, and we prove that the limit of this limiting distribution as the density of points goes to infinity has a nice expression. We apply our results to the adjacency matrix of the geometric graph. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008     

Second order freeness and fluctuations of random matrices: II. Unitary random matrices

We extend the relation between random matrices and free probability theory from the level of expectations to the level of fluctuations. We show how the concept of “second order freeness”, which was introduced in Part I, allows one to understand global fluctuations of Haar distributed unitary random matrices. In particular, independence between the unitary ensemble and another ensemble goes in the large N limit over into asymptotic second order freeness. Two important consequences of our general theory are: (i) we obtain a natural generalization of a theorem of Diaconis and Shahshahani to the case of several independent unitary matrices; (ii) we can show that global fluctuations in unitarily invariant multi-matrix models are not universal.     

Non-intersecting paths, random tilings and random matrices

 We investigate certain measures induced by families of non-intersecting paths in domino tilings of the Aztec diamond, rhombus tilings of an abc-hexagon, a dimer model on a cylindrical brick lattice and a growth model. The measures obtained, e.g. the Krawtchouk and Hahn ensembles, have the same structure as the eigenvalue measures in random matrix theory like GUE, which can in fact can be obtained from non-intersecting Brownian motions. The derivations of the measures are based on the Karlin-McGregor or Lindstr?m-Gessel-Viennot method. We use the measures to show some asymptotic results for the models. Received: 1 December 2000 / Revised version: 20 May 2001 / Published online: 17 May 2002