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We calculate the eigenvalues of some two-dimensional non-Hermitian Hamiltonians by means of a pseudospectral method and straightforward diagonalization of the Hamiltonian matrix in a suitable basis set. Both sets of results agree remarkably…

Quantum Physics · Physics 2014-03-19 Paolo Amore , Francisco M. Fernández , Javier Garcia

We consider computing the $k$-th eigenvalue and its corresponding eigenvector of a generalized Hermitian eigenvalue problem of $n\times n$ large sparse matrices. In electronic structure calculations, several properties of materials, such as…

Numerical Analysis · Mathematics 2018-08-01 Dongjin Lee , Takeo Hoshi , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

We compare two approaches to compute a portion of the spectrum of dense symmetric definite generalized eigenproblems: one is based on the reduction to tridiagonal form, and the other on the Krylov-subspace iteration. Two large-scale…

Quantum phase estimation provides a path to quantum computation of solutions to Hermitian eigenvalue problems $Hv = \lambda v$, such as those occurring in quantum chemistry. It is natural to ask whether the same technique can be applied to…

Quantum Physics · Physics 2020-08-28 Jeffrey B. Parker , Ilon Joseph

Such problems as computation of spectra of spin chains and vibrational spectra of molecules can be written as high-dimensional eigenvalue problems, i.e., when the eigenvector can be naturally represented as a multidimensional tensor. Tensor…

Numerical Analysis · Mathematics 2019-09-04 Maxim Rakhuba , Alexander Novikov , Ivan Oseledets

We propose a multigrid correction scheme to solve a new Steklov eigenvalue problem in inverse scattering. With this scheme, solving an eigenvalue problem in a fine finite element space is reduced to solve a series of boundary value problems…

Numerical Analysis · Mathematics 2018-06-18 Yu Zhang , Hai Bi , Yidu Yang

Large-scale eigenvalue problems pose a significant challenge to classical computers. While there are efficient quantum algorithms for unitary or Hermitian matrices, eigenvalue problems for non-normal matrices remain open in quantum…

Quantum Physics · Physics 2026-03-25 Honghong Lin , Yun Shang

We generalize and analyse the method for computing lower bounds of the principal eigenvalue proposed in our previous paper (I. Sebestova, T. Vejchodsky, SIAM J. Numer. Anal. 2014). This method is suitable for symmetric elliptic eigenvalue…

Numerical Analysis · Mathematics 2016-06-07 Ivana Sebestova , Tomas Vejchodsky

Polynomial filtering can provide a highly effective means of computing all eigenvalues of a real symmetric (or complex Hermitian) matrix that are located in a given interval, anywhere in the spectrum. This paper describes a technique for…

Numerical Analysis · Mathematics 2015-12-29 Ruipeng Li , Yuanzhe Xi , Eugene Vecharynski , Chao Yang , Yousef Saad

We discuss the eigenvalue problem for 2x2 and 3x3 octonionic Hermitian matrices. In both cases, we give the general solution for real eigenvalues, and we show there are also solutions with non-real eigenvalues.

Rings and Algebras · Mathematics 2007-05-23 Tevian Dray , Corinne A. Manogue

In Parts I and II of this series of papers, three new methods for the computation of eigenvalues of singular pencils were developed: rank-completing perturbations, rank-projections, and augmentation. It was observed that a straightforward…

Numerical Analysis · Mathematics 2024-06-12 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak

In this paper, a spectral method based on conformal mappings is proposed to solve Steklov eigenvalue problems and their related shape optimization problems in two dimensions. To apply spectral methods, we first reformulate the Steklov…

Numerical Analysis · Mathematics 2018-05-08 Weaam Alhejaili , Chiu-Yen Kao

We report an efficient program for computing the eigenvalues and symmetry-adapted eigenvectors of very large quaternionic (or Hermitian skew-Hamiltonian) matrices, using which structure-preserving diagonalization of matrices of dimension N…

Chemical Physics · Physics 2017-03-20 Toru Shiozaki

We present $TimeEvolver$, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix $i H$, where $H$…

Quantum Physics · Physics 2022-06-01 Marco Michel , Sebastian Zell

This paper proposes an efficient method for computing selected generalized eigenpairs of a sparse Hermitian definite matrix pencil $(A,B)$. Based on Zolotarev's best rational function approximations of the signum function and conformal…

Numerical Analysis · Mathematics 2021-01-01 Yingzhou Li , Haizhao Yang

Optimization of convex functions subject to eigenvalue constraints is intriguing because of peculiar analytical properties of eigenvalues, and is of practical interest because of wide range of applications in fields such as structural…

Numerical Analysis · Mathematics 2013-10-08 Emre Mengi

Starting from the Kirchhoff-Huygens representation and Duhamel's principle of time-domain wave equations, we propose novel butterfly-compressed Hadamard integrators for self-adjoint wave equations in both time and frequency domain in an…

Numerical Analysis · Mathematics 2024-06-06 Yuxiao Wei , Jin Cheng , Shingyu Leung , Robert Burridge , Jianliang Qian

Recently, a new eigenvalue problem, called the transmission eigenvalue problem, has attracted many researchers. The problem arose in inverse scattering theory for inhomogeneous media and has important applications in a variety of inverse…

Numerical Analysis · Mathematics 2016-11-23 Ruihao Huang , Allan A. Struthers , Jiguang Sun , Ruming Zhang

We develop the Euclidean time method of the variational quantum eigensolver for solving the generalized eigenvalue equation $A \ket{\phi_n} = \lambda_n B \ket{\phi_n}$, where $A$ and $B$ are hermitian operators, and $\ket{\phi_n}$ and…

Quantum Physics · Physics 2024-04-23 Mi-Ra Hwang , Eylee Jung , Museong Kim , DaeKil Park

We study Chebyshev filter diagonalization as a tool for the computation of many interior eigenvalues of very large sparse symmetric matrices. In this technique the subspace projection onto the target space of wanted eigenvectors is…