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Broyden's method is a general method commonly used for nonlinear systems of equations, when very little information is available about the problem. We develop an approach based on Broyden's method for nonlinear eigenvalue problems. Our…

Numerical Analysis · Mathematics 2018-02-22 Elias Jarlebring

We study non-convex Hamilton-Jacobi equations in the presence of gradient constraints and produce new, optimal, regularity results for the solutions. A distinctive feature of those equations regards the existence of a lower bound to the…

Analysis of PDEs · Mathematics 2020-10-27 Héctor A. Chang-Lara , Edgard A. Pimentel

We consider the forward problem of uncertainty quantification for the generalised Dirichlet eigenvalue problem for a coercive second order partial differential operator with random coefficients, motivated by problems in structural…

Numerical Analysis · Mathematics 2019-05-20 Alexander D. Gilbert , Ivan G. Graham , Frances Y. Kuo , Robert Scheichl , Ian H. Sloan

Non-smoothness at optimal points is a common phenomenon in many eigenvalue optimization problems. We consider two recent algorithms to minimize the largest eigenvalue of a Hermitian matrix dependent on one parameter, both proven to be…

Numerical Analysis · Mathematics 2018-05-14 Fatih Kangal , Emre Mengi

We present an efficient method for preparing the initial state required by the eigenvalue approximation quantum algorithm of Abrams and Lloyd. Our method can be applied when solving continuous Hermitian eigenproblems, e.g., the Schroedinger…

Quantum Physics · Physics 2009-11-10 Peter Jaksch , Anargyros Papageorgiou

We discuss the problems arising when computing eigenvalues of self-adjoint operators which lie in a gap between two parts of the essential spectrum. Spectral pollution, i.e. the apparent existence of eigenvalues in numerical computations,…

Spectral Theory · Mathematics 2007-05-23 E B Davies , M Plum

We consider the problem of approximating the set of eigenvalues of the covariance matrix of a multivariate distribution (equivalently, the problem of approximating the "population spectrum"), given access to samples drawn from the…

Machine Learning · Computer Science 2017-07-18 Weihao Kong , Gregory Valiant

A type of parallel augmented subspace scheme for eigenvalue problems is proposed by using coarse space in the multigrid method. With the help of coarse space in multigrid method, solving the eigenvalue problem in the finest space is…

Numerical Analysis · Mathematics 2020-08-19 Fei Xu , Hehu Xie , Ning Zhang

We consider the eigenvalue problem for one-dimensional linear Schr\"odinger lattices (tight-binding) with an embedded few-sites linear or nonlinear, Hamiltonian or non-conservative defect (an oligomer). Such a problem arises when…

Pattern Formation and Solitons · Physics 2015-06-12 J. D'Ambroise , P. G. Kevrekidis , S. Lepri

The Jacobian elliptic functions are generalized and applied to a nonlinear eigenvalue problem with $p$-Laplacian. The eigenvalue and the corresponding eigenfunction are represented in terms of common parameters, and a complete description…

Analysis of PDEs · Mathematics 2019-03-12 Shingo Takeuchi

Quantum canonical transformations of the second kind and the non-Hermitian realizations of the basic canonical commutation relations are investigated with a special interest in the generalization of the conventional ladder operators. The…

High Energy Physics - Theory · Physics 2009-10-28 W. S. l'Yi

In this paper matrix orthogonal polynomials in the real line are described in terms of a Riemann--Hilbert problem. This approach provides an easy derivation of discrete equations for the corresponding matrix recursion coefficients. The…

Classical Analysis and ODEs · Mathematics 2013-11-07 Giovanni A. Cassatella-Contra , Manuel Manas

Computing more than one eigenvalue for (large sparse) one-parameter polynomial and general nonlinear eigenproblems, as well as for multiparameter linear and nonlinear eigenproblems, is a much harder task than for standard eigenvalue…

Numerical Analysis · Mathematics 2021-10-19 Michiel E. Hochstenbach , Bor Plestenjak

We establish a gradient estimate for a very weak solution to a quasilinear elliptic equation with a nonstandard growth condition, which is a natural generalization of the $p$-Laplace equation. We investigate the maximum extent for the…

Analysis of PDEs · Mathematics 2022-02-14 Sun-Sig Byun , Minkyu Lim

For Hermitian positive definite linear systems and eigenvalue problems, the eigCG algorithm is a memory efficient algorithm that solves the linear system and simultaneously computes some of its eigenvalues. The algorithm is based on the…

High Energy Physics - Lattice · Physics 2010-02-19 Abdou Abdel-Rehim , Kostas Orginos , Andreas Stathopoulos

In this paper, we investigate the gradient estimates for solutions to the perfect conductivity problem with two closely spaced perfect conductors embedded in a homogeneous matrix, modeled by $p$-Laplacian elliptic equations. We first prove…

Analysis of PDEs · Mathematics 2026-01-15 Hongjie Dong , Longjuan Xu

Homogenization of a spectral problem in a bounded domain with a high contrast in both stiffness and density is considered. For a special critical scaling, two-scale asymptotic expansions for eigenvalues and eigenfunctions are constructed.…

Spectral Theory · Mathematics 2007-11-16 Natalia O. Babych , Ilia V. Kamotski , Valery P. Smyshlyaev

We prove explicit and sharp eigenvalue estimates for Neumann $p$-Laplace eigenvalues in domains that admit a representation in Fermi coordinates. More precisely, if $\gamma$ denotes a non-closed curve in $\mathbb{R}^2$ symmetric with…

Analysis of PDEs · Mathematics 2024-01-18 Barbara Brandolini , Francesco Chiacchio , Jeffrey J. Langford

In this article we consider a homogeneous eigenvalue problem ruled by the fractional $g-$Laplacian operator whose Euler-Lagrange equation is obtained by minimization of a quotient involving Luxemburg norms. We prove existence of an infinite…

Analysis of PDEs · Mathematics 2022-05-20 Julian Fernandez Bonder , Ariel Salort , Hernan Vivas

Hermitian and unitary matrices are two representatives of the class of normal matrices whose full eigenvalue decomposition can be stably computed in quadratic computing com plexity. Recently, fast and reliable eigensolvers dealing with low…

Numerical Analysis · Mathematics 2019-07-26 Gianna M. Del Corso , Federico Poloni , Leonardo Robol , Raf Vandebril