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The Cayley-Hamilton problem of expressing functions of matrices in terms of only their eigenvalues is well-known to simplify to finding the inverse of the confluent Vandermonde matrix. Here, we give a highly compact formula for the inverse…

Quantum Physics · Physics 2017-09-18 Samuel R. Hedemann

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

This thesis reviews recent progress on products of random matrices from the perspective of exactly solved Gaussian random matrix models. We derive exact formulae for the correlation functions for the eigen- and singular values at arbitrary…

Mathematical Physics · Physics 2015-10-22 J. R. Ipsen

We present a simple, accurate method for solving consistent, rank-deficient linear systems, with or without addi- tional rank-completing constraints. Such problems arise in a variety of applications, such as the computation of the…

Numerical Analysis · Mathematics 2014-01-15 Josef Sifuentes , Zydrunas Gimbutas , Leslie Greengard

We study an eigenvalue problem for the Laplacian on a compact K\"{a}hler manifold. Considering the $k$-th eigenvalue $\lambda_{k}$ as a functional on the space of K\"{a}hler metrics with fixed volume on a compact complex manifold, we…

Differential Geometry · Mathematics 2024-11-27 Kazumasa Narita

In this article we are interested for the numerical study of nonlinear eigenvalue problems. We begin with a review of theoretical results obtained by functional analysis methods, especially for the Schrodinger pencils. Some recall are given…

Numerical Analysis · Mathematics 2016-08-24 Fatima Aboud , Francois Jauberteau , Guy Moebs , Didier Robert

Preconditioned iterative methods for numerical solution of large matrix eigenvalue problems are increasingly gaining importance in various application areas, ranging from material sciences to data mining. Some of them, e.g., those using…

Numerical Analysis · Mathematics 2017-05-12 Merico E. Argentati , Andrew V. Knyazev , Klaus Neymeyr , Evgueni E. Ovtchinnikov , Ming Zhou

The nonlinear eigenvalue problem of a class of second order semi-transcendental differential equations is studied. A nonlinear eigenvalue is defined as the initial condition which gives rise a separatrix solution. A semi-transcendental…

Mathematical Physics · Physics 2020-07-27 Qing-hai Wang

We endow a recently devised algorithm for generating exact eigensolutions of large matrices with an importance sampling, which is in control of the extent and accuracy of the truncation of their dimensions. We made several tests on typical…

Nuclear Theory · Physics 2008-11-26 F. Andreozzi , N. Lo Iudice , A. Porrino

Exact solutions are derived for an n-dimensional radial wave equation with a general power nonlinearity. The method, which is applicable more generally to other nonlinear PDEs, involves an ansatz technique to solve a first-order PDE system…

Mathematical Physics · Physics 2007-05-23 Stephen C. Anco , Sheng Liu

In this paper, we discuss the solution of certain matrix-valued partial differential equations. Such PDEs arise, for example, when constructing a Riemannian contraction metric for a dynamical system given by an autonomous ODE. We develop…

Numerical Analysis · Mathematics 2017-06-29 Peter Giesl , Holger Wendland

We present a finite element algorithm that computes eigenvalues and eigenfunctions of the Laplace operator for two-dimensional problems with homogeneous Neumann or Dirichlet boundary conditions or combinations of either for different parts…

Chaotic Dynamics · Physics 2007-05-23 G. Baez , F. Leyvraz , R. A. Mendez-Sanchez , T. H. Seligman

We consider an ensemble of self-dual matrices with arbitrary complex entries. This ensemble is closely related to a previously defined ensemble of anti-symmetric matrices with arbitrary complex entries. We study the two-level correlation…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. B. Hastings

We develop an accelerated gradient descent algorithm on the Grassmann manifold to compute the subspace spanned by a number of leading eigenvectors of a symmetric positive semi-definite matrix. This has a constant cost per iteration and a…

Optimization and Control · Mathematics 2024-06-27 Foivos Alimisis , Simon Vary , Bart Vandereycken

Intertwining analysis, algebra, numerical analysis and optimization, computing conjugate co-gradients of real-valued quotients gives rise to eigenvalue problems. In the linear Hermitian case, by inspecting optimal quotients in terms of…

Spectral Theory · Mathematics 2022-11-14 Marko Huhtanen , Olavi Nevanlinna

Applications related to artificial intelligence, machine learning, and system identification simulations essentially use eigenvectors. Calculating eigenvectors for very large matrices using conventional methods is compute-intensive and…

Performance · Computer Science 2020-06-17 Shrey Dabhi , Manojkumar Parmar

The spectrum of the normalized complex Laplacian for electrical networks is analyzed. We show that eigenvalues lie in a larger region compared to the case of the real Laplacian. We show the existence of eigenvalues with negative real part…

Spectral Theory · Mathematics 2020-12-24 Anna Muranova , Robert Schippa

This paper is concerned with the nonnegative inverse eigenvalue problem of finding a nonnegative matrix such that its spectrum is the prescribed self-conjugate set of complex numbers. We first reformulate the nonnegative inverse eigenvalue…

Numerical Analysis · Mathematics 2017-06-13 Zhi Zhao , Zheng-Jian Bai , Xiao-Qing Jin

It is well known that the set of all $ n \times n $ matrices with distinct eigenvalues is a dense subset of the set of all real or complex $ n \times n $ matrices. In [Hartfiel, D. J. Dense sets of diagonalizable matrices. Proc. Amer. Math.…

Functional Analysis · Mathematics 2020-03-31 Himadri Lal Das , M. Rajesh Kannan

We propose a technique for calculating and understanding the eigenvalue distribution of sums of random matrices from the known distribution of the summands. The exact problem is formidably hard. One extreme approximation to the true density…

Quantum Physics · Physics 2017-10-27 Ramis Movassagh , Alan Edelman
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