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In this paper, we focus on solving a sequence of linear systems with an identical (or similar) coefficient matrix. For this type of problems, we investigate the subspace correction and deflation methods, which use an auxiliary matrix…

Numerical Analysis · Mathematics 2022-03-17 Takeshi Iwashita , Kota Ikehara , Takeshi Fukaya , Takeshi Mifune

The linear conjugate gradient method is widely used in physical simulation, particularly for solving large-scale linear systems derived from Newton's method. The nonlinear conjugate gradient method generalizes the conjugate gradient method…

Optimization and Control · Mathematics 2024-05-15 Xing Shen , Runyuan Cai , Mengxiao Bi , Tangjie Lv

We formulate the manifold learning problem as the problem of finding an operator that maps any point to a close neighbor that lies on a ``hidden'' $k$-dimensional manifold. We call this operator the correcting function. Under this…

Machine Learning · Computer Science 2023-06-27 Rustem Takhanov , Y. Sultan Abylkairov , Maxat Tezekbayev

We describe inexact proximal Newton-like methods for solving degenerate regularized optimization problems and for the broader problem of finding a zero of a generalized equation that is the sum of a continuous map and a maximal monotone…

Optimization and Control · Mathematics 2026-02-12 Ching-pei Lee , Stephen J. Wright

A methodology to analyze the properties of the first (largest) eigenvalue and its eigenvector is developed for large symmetric random sparse matrices utilizing the cavity method of statistical mechanics. Under a tree approximation, which is…

Optimization and Control · Mathematics 2015-05-18 Yoshiyuki Kabashima , Hisanao Takahashi , Osamu Watanabe

We present a novel numerical method, called {\tt Jacobi-predictor-corrector approach}, for the numerical solution of fractional ordinary differential equations based on the polynomial interpolation and the Gauss-Lobatto quadrature w.r.t.…

Numerical Analysis · Mathematics 2014-01-30 Lijing Zhao , Weihua Deng

For compact self-adjoint operators in Hilbert spaces, two algorithms are proposed to provide fully computable a posteriori error estimate for eigenfunction approximation. Both algorithms apply well to the case of tight clusters and multiple…

Numerical Analysis · Mathematics 2022-07-19 Xuefeng Liu , Tomáš Vejchodský

For a general third-order tensor $\mathcal{A}\in\mathbb{R}^{n\times n\times n}$ the paper studies two closely related problems, an SVD-like tensor decomposition and an (approximate) tensor diagonalization. We develop a Jacobi-type algorithm…

Numerical Analysis · Mathematics 2024-03-20 Erna Begovic

The Eberlein method is a Jacobi-type process for solving the eigenvalue problem of an arbitrary matrix. In each iteration two transformations are applied on the underlying matrix, a plane rotation and a non-unitary elementary…

Numerical Analysis · Mathematics 2024-07-12 Erna Begovic , Ana Perkovic

The Kaczmarz method is an algorithm for finding the solution to an overdetermined consistent system of linear equations Ax=b by iteratively projecting onto the solution spaces. The randomized version put forth by Strohmer and Vershynin…

Numerical Analysis · Mathematics 2011-02-15 Yonina C. Eldar , Deanna Needell

The classical theory of Kosambi-Cartan-Chern (KCC) developed in differential geometry provides a powerful method for analyzing the behaviors of dynamical systems. In the KCC theory, the properties of a dynamical system are described in…

Symbolic Computation · Computer Science 2024-06-18 Bo Huang , Dongming Wang , Jing Yang

The Jacobi equation for geodesic deviation describes finite size effects due to the gravitational tidal forces. In this paper we show how one can integrate the Jacobi equation in any spacetime admitting completely integrable geodesics.…

General Relativity and Quantum Cosmology · Physics 2019-01-14 Marco Cariglia , Tsuyoshi Houri , Pavel Krtous , David Kubiznak

Solving complex optimization problems in engineering and the physical sciences requires repetitive computation of multi-dimensional function derivatives. Commonly, this requires computationally-demanding numerical differentiation such as…

Numerical Analysis · Mathematics 2021-05-12 Danny Smyl , Tyler N. Tallman , Dong Liu , Andreas Hauptmann

A sequential quadratic optimization algorithm is proposed for solving smooth nonlinear equality constrained optimization problems in which the objective function is defined by an expectation of a stochastic function. The algorithmic…

Optimization and Control · Mathematics 2023-03-17 Albert S. Berahas , Frank E. Curtis , Michael J. O'Neill , Daniel P. Robinson

The numerical solution of singular eigenvalue problems is complicated by the fact that small perturbations of the coefficients may have an arbitrarily bad effect on eigenvalue accuracy. However, it has been known for a long time that such…

Numerical Analysis · Mathematics 2023-01-10 Daniel Kressner , Ivana Šain Glibić

We consider the uniform approximation of the smallest eigenvalue of a large parameter-dependent Hermitian matrix by that of a smaller counterpart obtained through projections. The projection subspaces are constructed iteratively by means of…

Numerical Analysis · Mathematics 2026-01-16 Mattia Manucci , Emre Mengi , Nicola Guglielmi

The generalized Jacobi equation is a differential equation in local coordinates that describes the behavior of infinitesimally close geodesics with an arbitrary relative velocity. In this note we study some transformation properties for…

Mathematical Physics · Physics 2012-05-22 Matias F. Dahl , Ricardo Gallego Torromé

The discrete spectrum of complex Jacobi matrices that are compact perturbations of the discrete laplacian is under consideration. The rate of stabilization for the the matrix entries which provides finiteness of the discrete spectrum and is…

Spectral Theory · Mathematics 2007-05-23 I. Egorova , L. Golinskii

A common challenge faced in quantum physics is finding the extremal eigenvalues and eigenvectors of a Hamiltonian matrix in a vector space so large that linear algebra operations on general vectors are not possible. There are numerous…

Nuclear Theory · Physics 2018-07-18 Dillon Frame , Rongzheng He , Ilse Ipsen , Daniel Lee , Dean Lee , Ermal Rrapaj

We consider the problem of enabling robust range estimation of eigenvalue decomposition (EVD) algorithm for a reliable fixed-point design. The simplicity of fixed-point circuitry has always been so tempting to implement EVD algo- rithms in…

Numerical Analysis · Computer Science 2017-11-30 Bibek Kabi , Anand S Sahadevan , Tapan Pradhan
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