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We provide a solution to the problem of simultaneous $diagonalization$ $via$ $congruence$ of a given set of $m$ complex symmetric $n\times n$ matrices $\{A_{1},\ldots,A_{m}\}$, by showing that it can be reduced to a possibly…

Optimization and Control · Mathematics 2021-02-10 Miguel D. Bustamante , Pauline Mellon , M. Victoria Velasco

This paper proposes new proximal Newton-type methods with a diagonal metric for solving composite optimization problems whose objective function is the sum of a twice continuously differentiable function and a proper closed directionally…

Optimization and Control · Mathematics 2023-10-11 Shotaro Yagishita , Shummin Nakayama

Finding a Z-eigenpair of a symmetric tensor is equivalent to finding a KKT point of a sphere constrained minimization problem. Based on this equivalency, in this paper, we first propose a class of iterative methods to get a Z-eigenpair of a…

Optimization and Control · Mathematics 2022-03-15 Dong-hui Li , Xueli Bai , Jiefeng Xu

We investigate the use of piecewise linear systems, whose coefficient matrix is a piecewise constant function of the solution itself. Such systems arise, for example, from the numerical solution of linear complementarity problems and in the…

Numerical Analysis · Mathematics 2012-06-21 Luigi Brugnano , Alessandra Sestini

We develop a randomized Newton's method for solving differential equations, based on a fully connected neural network discretization. In particular, the randomized Newton's method randomly chooses equations from the overdetermined nonlinear…

Numerical Analysis · Mathematics 2019-12-09 Qipin Chen , Wenrui Hao

We present a modification of Newton's method to restore quadratic convergence for isolated singular solutions of polynomial systems. Our method is symbolic-numeric: we produce a new polynomial system which has the original multiple solution…

Numerical Analysis · Mathematics 2007-05-23 Anton Leykin , Jan Verschelde , Ailing Zhao

We study a semismooth Newton-type method for the nearest doubly stochastic matrix problem where both differentiability and nonsingularity of the Jacobian can fail. The optimality conditions for this problem are formulated as a system of…

Optimization and Control · Mathematics 2021-07-21 Hao Hu , Haesol Im , Xinxin Li , Henry Wolkowicz

The joint approximate diagonalization of non-commuting symmetric matrices is an important process in independent component analysis. This problem can be formulated as an optimization problem on the Stiefel manifold that can be solved using…

Optimization and Control · Mathematics 2022-02-28 Hiroyuki Sato

We present a matrix version of a known method of constructing common eigenvectors of two diagonalizable commuting matrices, thus enabling their simultaneous diagonalization. The matrices may have simple eigenvalues of multiplicity greater…

General Mathematics · Mathematics 2020-07-01 Ronald P. Nordgren

When studying the multilinear PageRank problem, a system of polynomial equations needs to be solved. In this paper, we develop convergence theory for a modified Newton method in a particular parameter regime. The sequence of vectors…

Numerical Analysis · Mathematics 2017-01-23 Pei-Chang Guo

An iterative formula based on Newton Method alone is presented for the iterative solutions of equations that ensures convergence in cases where the traditional Newton Method may fail to converge to the desired root. In addition, the method…

Numerical Analysis · Mathematics 2012-10-30 Ababu Teklemariam Tiruneh

This paper focuses on discussing Newton's method and its hybrid with machine learning for the steady state Navier-Stokes Darcy model discretized by mixed element methods. First, a Newton iterative method is introduced for solving the…

Numerical Analysis · Mathematics 2024-03-07 Jianguo Huang , Hui Peng , Haohao Wu

Real eigenpairs of symmetric tensors play an important role in multiple applications. In this paper we propose and analyze a fast iterative Newton-based method to compute real eigenpairs of symmetric tensors. We derive sufficient conditions…

Numerical Analysis · Mathematics 2018-03-06 Ariel Jaffe , Roi Weiss , Boaz Nadler

In this paper, a novel multigrid method based on Newton iteration is proposed to solve nonlinear eigenvalue problems. Instead of handling the eigenvalue $\lambda$ and eigenfunction $u$ separately, we treat the eigenpair $(\lambda, u)$ as…

Numerical Analysis · Mathematics 2024-04-30 Fei Xu , Manting Xie , Meiling Yue

A hermitian matrix can be parametrized by a set consisting of its determinant and the eigenvalues of its submatrices. We established a group of equations which connect these variables with the mixing parameters of diagonalization. These…

High Energy Physics - Phenomenology · Physics 2024-10-03 S. H. Chiu , T. K. Kuo

We consider a set of N linearly coupled harmonic oscillators and show that the diagonalization of this problem can be put in geometrical terms. The matrix techniques developed here allowed for solutions in both the classical and quantum…

Quantum Physics · Physics 2009-11-11 A. R. Bosco de Magalhães , C. H. d'Ávila Fonseca , M. C. Nemes

This paper is concerned with the convergence of a two-step modified Newton method for solving the nonlinear system arising from the minimal nonnegative solution of nonsymmetric algebraic Riccati equations from neutron transport theory. We…

Numerical Analysis · Mathematics 2025-07-22 Juan Liang , Yonghui Ling

The nonlinear eigen-problem $ Ax+F(x)=\lambda x$ is studied where $A$ is an $n\times n$ irreducible Stieltjes matrix. Under certain conditions, this problem has a unique positive solution. We show that, starting from a multiple of the…

Numerical Analysis · Mathematics 2022-01-11 Peichang Guo

In this paper we present in detail Newton's method and its modification, based on the Continuous analog of Newton's method for computing periodic orbits of the planar three-body problem. The linear system at each step of the method is…

Chaotic Dynamics · Physics 2021-11-23 I. Hristov , R. Hristova , I. Puzynin , T. Puzynina , Z. Sharipov , Z. Tukhliev

Newton's method may exhibit slower convergence than vanilla Gradient Descent in its initial phase on strongly convex problems. Classical Newton-type multilevel methods mitigate this but, like Gradient Descent, achieve only linear…

Optimization and Control · Mathematics 2026-02-25 Nick Tsipinakis , Panos Parpas , Matthias Voigt
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