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A unified approach, for solving a wide class of single and many-body quantum problems, commonly encountered in literature is developed based on a recently proposed method for finding solutions of linear differential equations. Apart from…

Quantum Physics · Physics 2007-05-23 N. Gurappa , Prasanta K. Panigrahi , R. Atre , T. Shreecharan

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

We present the reduced basis method as a tool for developing emulators for equations with tunable parameters within the context of the nuclear many-body problem. The method uses a basis expansion informed by a set of solutions for a few…

Nuclear Theory · Physics 2022-11-30 Edgard Bonilla , Pablo Giuliani , Kyle Godbey , Dean Lee

Many quantal many-body methods that aim at the description of self-bound nuclear or mesoscopic electronic systems make use of auxiliary wave functions that break one or several of the symmetries of the Hamiltonian in order to include…

Nuclear Theory · Physics 2021-02-16 Benjamin Bally , Michael Bender

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to…

This article is a brief introduction to quantum algorithms for the eigenvalue problem in quantum many-body systems. Rather than a broad survey of topics, we focus on providing a conceptual understanding of several quantum algorithms that…

Quantum Physics · Physics 2024-06-10 Dean Lee

We propose an algorithm for general nonlinear eigenvalue problems to compute physically relevant eigenvalues within a chosen contour. Eigenvalue information is explored by contour integration incorporating different weight functions. The…

Computational Physics · Physics 2020-11-19 Felix Binkowski , Lin Zschiedrich , Sven Burger

The eigenvalue problem of quantum many-body systems is a fundamental and challenging subject in condensed matter physics, since the dimension of the Hilbert space (and hence the required computational memory and time) grows exponentially as…

Disordered Systems and Neural Networks · Physics 2021-05-12 Chen-Yu Liu , Daw-Wei Wang

Eigensolvers involving complex moments can determine all the eigenvalues in a given region in the complex plane and the corresponding eigenvectors of a regular linear matrix pencil. The complex moment acts as a filter for extracting…

Numerical Analysis · Mathematics 2021-09-22 Keiichi Morikuni

We propose a new type of multilevel method for solving eigenvalue problems based on Newton iteration. With the proposed iteration method, solving eigenvalue problem on the finest finite element space is replaced by solving a small scale…

Numerical Analysis · Mathematics 2015-11-13 Yunhui He , Yu Li , Hehu Xie

This paper is to give a new understanding and applications of the subspace projection method for selfadjoint eigenvalue problems. A new error estimate in the energy norm, which is induced by the stiff matrix, of the subspace projection…

Numerical Analysis · Mathematics 2017-08-24 Yunhui He , Qichen Hong , Hehu Xie , Meiling Yue , Chunguang You

Eigenvector continuation is a computational method for parametric eigenvalue problems that uses subspace projection with a basis derived from eigenvector snapshots from different parameter sets. It is part of a broader class of…

Nuclear Theory · Physics 2024-08-15 Thomas Duguet , Andreas Ekström , Richard J. Furnstahl , Sebastian König , Dean Lee

This paper presents a method for computing eigenvalues and eigenvectors for some types of nonlinear eigenvalue problems. The main idea is to approximate the functions involved in the eigenvalue problem by rational functions and then apply a…

Numerical Analysis · Mathematics 2020-06-11 Yousef Saad , Mohamed El-Guide , Agnieszka Międlar

Solving the generalized eigenvalue problem is a useful method for finding energy eigenstates of large quantum systems. It uses projection onto a set of basis states which are typically not orthogonal. One needs to invert a matrix whose…

Nuclear Theory · Physics 2023-04-05 Caleb Hicks , Dean Lee

The aim of this paper is to develop an algebraic multigrid method to solve eigenvalue problems based on the combination of the multilevel correction scheme and the algebraic multigrid method for linear equations. Our approach uses the…

Numerical Analysis · Mathematics 2020-03-02 Ning Zhang , Xiaole Han , Yunhui He , Hehu Xie , Chun'guang You

In this paper, we propose a spectral framework that embeds 1D and 2D quasiperiodic Helmholtz eigenvalue problems into higher-dimensional (2D and 4D) periodic spaces via the projection method \cite{jiang2014numerical, jiang2024numerical}. To…

Numerical Analysis · Mathematics 2026-05-28 Teng-Chao Sun , Tiexiang Li , Wen-Wei Lin , Xing-Long Lyu

Recently, contour integral-based methods have been actively studied for solving interior eigenvalue problems that find all eigenvalues located in a certain region and their corresponding eigenvectors. In this paper, we reconsider the…

Numerical Analysis · Mathematics 2021-09-10 Akira Imakura , Lei Du , Tetsuya Sakurai

The aim of this paper is to propose an efficient adaptive finite element method for eigenvalue problems based on the multilevel correction scheme and inverse power method. This method involves solving associated boundary value problems on…

Numerical Analysis · Mathematics 2022-02-25 Qichen Hong , Hehu Xie , Fei Xu

We derive an exact equation of motion for the reduced density matrices of individual subsystems of quantum many-body systems of any lattice dimension and arbitrary system size. Our projection operator based theory yields a highly efficient…

Quantum Physics · Physics 2014-06-13 Peter Degenfeld-Schonburg , Michael J. Hartmann

We propose an eigensolver and the corresponding package, GCGE, for solving large scale eigenvalue problems. This method is the combination of damping idea, subspace projection method and inverse power method with dynamic shifts. To reduce…

Numerical Analysis · Mathematics 2021-11-15 Yu Li , Zijing Wang , Hehu Xie
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