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We develop an efficient quantum implementation of an important signal processing algorithm for line spectral estimation: the matrix pencil method, which determines the frequencies and damping factors of signals consisting of finite sums of…

Quantum Physics · Physics 2017-04-05 A. Steffens , P. Rebentrost , I. Marvian , J. Eisert , S. Lloyd

The matrix pencil method is an eigenvalue based approach for the parameter identification of sparse exponential sums. We derive a reconstruction algorithm for multivariate exponential sums that is based on simultaneous diagonalization.…

Numerical Analysis · Mathematics 2018-05-17 Martin Ehler , Stefan Kunis , Thomas Peter , Christian Richter

We give a self-contained randomized algorithm based on shifted inverse iteration which provably computes the eigenvalues of an arbitrary matrix $M\in\mathbb{C}^{n\times n}$ up to backward error $\delta\|M\|$ in…

Numerical Analysis · Mathematics 2022-05-16 Jess Banks , Jorge Garza-Vargas , Nikhil Srivastava

Our aim in this paper is two-fold: First, for computing zeros of a linear time-invariant (LTI) system $\Sigma$ in {\em state-space form}, we introduce a "trimmed structured linearization", which we refer to as {\em Rosenbrock…

Numerical Analysis · Mathematics 2015-05-15 Rafikul Alam , Namita Behera

A generalized eigenvalue algorithm for tridiagonal matrix pencils is presented. The algorithm appears as the time evolution equation of a nonautonomous discrete integrable system associated with a polynomial sequence which has some…

Numerical Analysis · Mathematics 2016-01-19 Kazuki Maeda , Satoshi Tsujimoto

The large systems of complex linear equations that are generated in QCD problems often have multiple right-hand sides (for multiple sources) and multiple shifts (for multiple masses). Deflated GMRES methods have previously been developed…

High Energy Physics - Lattice · Physics 2008-11-26 Abdou Abdel-Rehim , Ronald B. Morgan , Walter Wilcox

We study the sign problem in the Hubbard model on the hexagonal lattice away from half-filling using the Lefschetz thimbles method. We identify the saddle points, reduce their amount, and perform quantum Monte Carlo (QMC) simulations using…

Strongly Correlated Electrons · Physics 2019-06-13 Maksim Ulybyshev , Christopher Winterowd , Savvas Zafeiropoulos

The seminal work by Mackey et al. in 2006 (reference [21] of the article) introduced vector spaces of matrix pencils, with the property that almost all the pencils in the spaces are strong linearizations of a given square regular matrix…

Numerical Analysis · Mathematics 2018-08-03 Biswajit Das , Shreemayee Bora

We present a randomized, inverse-free algorithm for producing an approximate diagonalization of any $n \times n$ matrix pencil $(A,B)$. The bulk of the algorithm rests on a randomized divide-and-conquer eigensolver for the generalized…

Numerical Analysis · Mathematics 2024-12-11 James Demmel , Ioana Dumitriu , Ryan Schneider

We consider the problem of extracting a few desired eigenpairs of the buckling eigenvalue problem $Kx = \lambda K_Gx$, where $K$ is symmetric positive semi-definite, $K_G$ is symmetric indefinite, and the pencil $K - \lambda K_G$ is…

Numerical Analysis · Mathematics 2019-10-22 Chao-Ping Lin , Huiqing Xie , Roger Grimes , Zhaojun Bai

This paper builds and extends on the authors' previous work related to the algorithmic tool, Cylindrical Algebraic Decomposition (CAD), and one of its core applications, Real Quantifier Elimination (QE). These topics are at the heart of…

Symbolic Computation · Computer Science 2025-11-20 James H. Davenport , Matthew England , Scott McCallum , Ali K. Uncu

A popular method for solving large sparse regular eigenvalue problem is the shift-and-invert Arnoldi method. This paper aims to use the method for large sparse singular pencils. In three recent papers, {\em Hochstenbach, Mehl, and…

Numerical Analysis · Mathematics 2026-05-20 Karl Meerbergen , Zhijun Wang

A new approach is discussed for solving large nonsymmetric systems of linear equations with multiple right-hand sides. The first system is solved with a deflated GMRES method that generates eigenvector information at the same time that the…

Mathematical Physics · Physics 2007-07-05 Ronald B. Morgan , Walter Wilcox

We consider the quantum implementations of the two classical iterative solvers for a system of linear equations, including the Kaczmarz method which uses a row of coefficient matrix in each iteration step, and the coordinate descent method…

Quantum Physics · Physics 2020-02-26 Changpeng Shao , Hua Xiang

Quantum phase estimation is the flagship algorithm for quantum simulation on fault-tolerant quantum computers. We demonstrate that an \emph{off-grid} compressed sensing protocol, combined with a state-of-the-art signal classification…

Quantum Physics · Physics 2025-07-17 Davide Castaldo , Stefano Corni

In this paper we present several additions to the quaternion QR algorithm, including algorithms for eigenvector computation and eigenvalue reordering. A key outcome of the eigenvalue reordering algorithm is that the aggressive early…

Numerical Analysis · Mathematics 2025-11-05 Zhigang Jia , Meiyue Shao , Yanjun Shao

We present an implementation of the fast multipole method for computing coulombic electrostatic and polarization forces from polarizable force-fields based on induced point dipole moments. We demonstrate the expected $O(N)$ scaling of that…

Chemical Physics · Physics 2015-06-22 Jonathan P. Coles , Michel Masella

Recently, a kind of eigensolvers based on contour integral were developed for computing the eigenvalues inside a given region in the complex plane. The CIRR method is a classic example among this kind of methods. In this paper, we propose a…

Numerical Analysis · Mathematics 2015-08-19 Guojian Yin

We present an efficient matrix-free geometric multigrid method for the elastic Helmholtz equation, and a suitable discretization. Many discretization methods had been considered in the literature for the Helmholtz equations, as well as many…

Numerical Analysis · Mathematics 2023-12-05 Rachel Yovel , Eran Treister

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou