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The convergence of inexact Newton methods is studied for solving generalized equations on Riemannian manifolds by using the metric regularity property, which is also explored. Under appropriate conditions and without any additional…

Numerical Analysis · Mathematics 2024-09-25 Mauricio S. Louzeiro , Gilson N. Silva , Jinyun Yuan , Daoping Zhang

We deal with two dynamical systems associated with a Riemannian manifold with boundary. The first one is a system governed by the scalar wave equation, the second is governed by the Maxwell equations. Both of the systems are controlled from…

Mathematical Physics · Physics 2015-06-19 M. I. Belishev , M. N. Demchenko

We consider the inverse problem to determine a smooth compact Riemannian manifold with boundary $(M, g)$ from a restriction $\Lambda_{\Src, \Rec}$ of the Dirichlet-to-Neumann operator for the wave equation on the manifold. Here $\Src$ and…

Analysis of PDEs · Mathematics 2015-01-14 Matti Lassas , Lauri Oksanen

In this paper, an inexact Newton method for solving real-valued nonlinear eigenvalue problems with eigenvector dependency (NEPv) is introduced that is able to solve the problem on a matrix level. Our main contribution is to derive a variant…

Numerical Analysis · Mathematics 2024-09-04 Tom Werner

We present and compare three constructive methods for realizing non-real spectra with three nonzero elements in the nonnegative inverse eigenvalue problem. We also provide some necessary conditions for realizability and numerical examples.…

Rings and Algebras · Mathematics 2017-01-18 Anthony Cronin

For numerous parameter and state estimation problems, assimilating new data as they become available can help produce accurate and fast inference of unknown quantities. While most existing algorithms for solving those kind of ill-posed…

Numerical Analysis · Mathematics 2022-07-28 Neil K. Chada , Marco A. Iglesias , Shuai Lu , Frank Werner

Conjugate gradient (CG) methods are widely acknowledged as efficient for minimizing continuously differentiable functions in Euclidean spaces. In recent years, various CG methods have been extended to Riemannian manifold optimization, but…

Optimization and Control · Mathematics 2026-05-26 Chunming Tang , Shaohui Liang , Huangyue Chen

We develop the first stochastic incremental method for calculating the Moore-Penrose pseudoinverse of a real matrix. By leveraging three alternative characterizations of pseudoinverse matrices, we design three methods for calculating the…

Numerical Analysis · Mathematics 2019-05-02 Robert M. Gower , Peter Richtárik

This paper proposes direct and inverse results for the Dirichlet and Dirichlet to Neumann problems for complex curves with nodal type singularities. As an application, we give a method to reconstruct the conformal structure of a compact…

Complex Variables · Mathematics 2015-06-12 Gennadi Henkin , Vincent Michel

We propose a inexact Newton method for solving inverse eigenvalue problems (IEP). This method is globalized by employing the classical backtracking techniques. A global convergence analysis of this method is provided and the R-order…

Numerical Analysis · Mathematics 2013-04-24 Yonghui Ling , Xiubin Xu

We use the method of higher order linearization to study an inverse boundary value problem for the minimal surface equation on a Riemannian manifold $(\mathbb{R}^n,g)$, where the metric $g$ is conformally Euclidean. In particular we show…

Analysis of PDEs · Mathematics 2022-11-03 Janne Nurminen

This paper is devoted to the inverse problem of recovering simultaneously a potential and a point source in a Shr\"odinger equation from the associated nonlinear Dirichlet to Neumann map. The uniqueness of the inversion is proved and…

Analysis of PDEs · Mathematics 2020-02-24 Gang Bao , Yuantong Liu , Faouzi Triki

The doubly nonnegative (DNN) cone, being the set of all positive semidefinite matrices whose elements are nonnegative, is a popular approximation of the computationally intractable completely positive cone. The major difficulty for…

Optimization and Control · Mathematics 2021-09-02 Ying Cui , Ling Liang , Defeng Sun , Kim-Chuan Toh

The main of this work is to use the unit lower triangular matrices for solving inverse eigenvalue problem of nonnegative matrices and present the easier method to solve this problem.

Numerical Analysis · Mathematics 2018-05-22 Alimohammad Nazari , Atiyeh Nezami

We study a nonlinear decomposition of a positive definite matrix into two components: the inverse of another positive definite matrix and a symmetric matrix constrained to lie in a prescribed linear subspace. Equivalently, the inverse…

Optimization and Control · Mathematics 2026-01-27 Yan Dolinsky , Or Zuk

We consider the dynamical system with boundary control for the vector Schr\"odinger equation on the interval with a non-self-adjoint matrix potential. For this system, we study the inverse problem of recovering the matrix potential from the…

Analysis of PDEs · Mathematics 2025-05-12 Sergei Avdonin , Alexander Mikhaylov , Victor Mikhaylov , Jeff Park

This paper aims at the efficient numerical solution of stochastic eigenvalue problems. Such problems often lead to prohibitively high dimensional systems with tensor product structure when discretized with the stochastic Galerkin method.…

Numerical Analysis · Mathematics 2018-09-28 Peter Benner , Akwum Onwunta , Martin Stoll

The inverse eigenvalue problem studies the possible spectra among matrices whose off-diagonal entries have their zero-nonzero patterns described by the adjacency of a graph $G$. In this paper, we refer to the $i$-nullity pair of a matrix…

Combinatorics · Mathematics 2023-10-24 Aida Abiad , Bryan A. Curtis , Mary Flagg , H. Tracy Hall , Jephian C. -H. Lin , Bryan Shader

We solve a spectral and an inverse spectral problem arising in the computation of peakon solutions to the two-component PDE derived by Geng and Xue as a generalization of the Novikov and Degasperis-Procesi equations. Like the spectral…

Spectral Theory · Mathematics 2017-01-25 Hans Lundmark , Jacek Szmigielski

Recently, a Riemannian proximal Newton method has been developed for optimizing problems in the form of $\min_{x\in\mathcal{M}} f(x) + \mu \|x\|_1$, where $\mathcal{M}$ is a compact embedded submanifold and $f(x)$ is smooth. Although this…

Optimization and Control · Mathematics 2025-03-25 Wen Huang , Wutao Si