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The notion of the eigenvalue problem in the Fock space with polynomial eigenfunctions is introduced. This problem is classified by using the finite-dimensional representations of the $\mathfrak{sl}(2)$-algebra in Fock space. In the complex…

Mathematical Physics · Physics 2025-09-17 A. V. Turbiner , N. L. Vasilevski

We develop an accelerated gradient descent algorithm on the Grassmann manifold to compute the subspace spanned by a number of leading eigenvectors of a symmetric positive semi-definite matrix. This has a constant cost per iteration and a…

Optimization and Control · Mathematics 2024-06-27 Foivos Alimisis , Simon Vary , Bart Vandereycken

In this paper, we study the first eigenvalue of a nonlinear elliptic system involving $p$-Laplacian as the differential operator. The principal eigenvalue of the system and the corresponding eigenfunction are investigated both analytically…

Numerical Analysis · Mathematics 2019-05-30 Farid Bozorgnia , Seyyed Abbas Mohammadi , Tomas Vejchodsky

Given a nonconvex function that is an average of $n$ smooth functions, we design stochastic first-order methods to find its approximate stationary points. The convergence of our new methods depends on the smallest (negative) eigenvalue…

Optimization and Control · Mathematics 2018-09-28 Zeyuan Allen-Zhu

This paper introduces a method for computing eigenvalues and eigenvectors of a generalized Hermitian, matrix eigenvalue problem. The work is focused on large scale eigenvalue problems, where the application of a direct inverse is out of…

Numerical Analysis · Mathematics 2024-02-14 Lothar Nannen , Markus Wess

In this paper, we aim to study non-convex minimization problems via second-order (in-time) dynamics, including a non-vanishing viscous damping and a geometric Hessian-driven damping. Second-order systems that only rely on a viscous damping…

Optimization and Control · Mathematics 2025-06-06 Rodrigo Maulen-Soto , Jalal Fadili , Peter Ochs

We study an indefinite spectral problem for a second-order self-adjoint elliptic operator in an asymptotically thin cylinder. The operator coefficients and the spectral density function are assumed to be locally periodic in the axial…

Analysis of PDEs · Mathematics 2025-07-01 Srinivasan Aiyappan , Aditi Chattaraj , Irina Pettersson

In this paper we extend classical criteria for determining lower bounds for the least point of the essential spectrum of second-order elliptic differential operators on domains $\Omega\subset\R^n$ allowing for degeneracy of the coefficients…

Spectral Theory · Mathematics 2011-03-08 Roger T. Lewis

We derive a concavity inequality for $k$-Hessian operators under the semi-convexity condition. As an application, we establish interior estimates for semi-convex solutions of the $k$-Hessian equations with vanishing Dirichlet boundary and…

Analysis of PDEs · Mathematics 2025-02-18 Ruijia Zhang

We present a finite difference method to compute the principal eigenvalue and the corresponding eigenfunction for a large class of second order elliptic operators including notably linear operators in nondivergence form and fully nonlinear…

Numerical Analysis · Mathematics 2016-02-18 Isabeau Birindelli , Fabio Camilli , Italo Capuzzo Dolcetta

This work is concerned with the convex analysis of functions defined on (not necessarily finite-dimensional) Hilbert spaces whose values depend solely on a certain ``spectrum'' of the arguments, a class we term ``spectral functions.'' We…

Optimization and Control · Mathematics 2026-03-11 Hòa T. Bùi , Minh N. Bùi , Christian Clason

In this paper, we consider the eigenvalue problem for Hodge-Laplacian on a Riemannian manifold $M$ isometrically immersed into another Riemannian manifold $\bar M$ for arbitrary codimension. We first assume the pull back Weitzenb\"{o}ck…

Differential Geometry · Mathematics 2017-12-18 Qing Cui , Linlin Sun

We study the seismic inverse problem for the recovery of subsurface properties in acoustic media. In order to reduce the ill-posedness of the problem, the heterogeneous wave speed parameter to be recovered is represented using a limited…

Analysis of PDEs · Mathematics 2020-09-10 Florian Faucher , Otmar Scherzer , Hélène Barucq

A numerical method for variable coefficient elliptic problems on two dimensional domains is described. The method is based on high-order spectral approximations and is designed for problems with smooth solutions. The resulting system of…

Numerical Analysis · Mathematics 2015-06-04 P. G. Martinsson

We consider computing the $k$-th eigenvalue and its corresponding eigenvector of a generalized Hermitian eigenvalue problem of $n\times n$ large sparse matrices. In electronic structure calculations, several properties of materials, such as…

Numerical Analysis · Mathematics 2018-08-01 Dongjin Lee , Takeo Hoshi , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

This paper studies the eigenvalue problem $K \psi = \lambda \psi$ associated with a Fredholm integral operator $K$ defined by a smooth kernel. The focus is on analyzing the convergence behaviour of numerical approximations to eigenvalues…

Numerical Analysis · Mathematics 2026-03-27 Shashank K. Shukla

Let $\Omega$ be an open, simply connected, and bounded region in $\mathbb{R}^{d}$, $d\geq2$, and assume its boundary $\partial\Omega$ is smooth. Consider solving the eigenvalue problem $Lu=\lambda u$ for an elliptic partial differential…

Numerical Analysis · Mathematics 2011-06-20 Kendall Atkinson , Olaf Hansen

In this article, we propose and analyze an effective Hessian recovery strategy for the Lagrangian finite element of arbitrary order $k$. We prove that the proposed Hessian recovery preserves polynomials of degree $k+1$ on general…

Numerical Analysis · Mathematics 2014-09-30 Hailong Guo , Zhimin Zhang , Ren Zhao

We introduce a simple, general, and convergent scheme to compute generalized eigenfunctions of self-adjoint operators with continuous spectra on rigged Hilbert spaces. Our approach does not require prior knowledge about the eigenfunctions,…

Numerical Analysis · Mathematics 2024-10-14 Matthew J. Colbrook , Andrew Horning , Tianyiwa Xie

We focus in this work on the estimation of the first $k$ eigenvectors of any graph Laplacian using filtering of Gaussian random signals. We prove that we only need $k$ such signals to be able to exactly recover as many of the smallest…

Data Structures and Algorithms · Computer Science 2016-11-07 Johan Paratte , Lionel Martin
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