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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

The Koopman operator provides a linear framework to study nonlinear dynamical systems. Its spectra offer valuable insights into system dynamics, but the operator can exhibit both discrete and continuous spectra, complicating direct…

Dynamical Systems · Mathematics 2025-05-02 Jonghyeon Lee , Boumediene Hamzi , Boya Hou , Houman Owhadi , Gabriele Santin , Umesh Vaidya

In this paper, we study convergence and superconvergence theory of integer and fractional derivatives of the one-point and the two-point Hermite interpolations. When considering the integer-order derivative, exponential decay of the error…

Numerical Analysis · Mathematics 2018-03-22 Beichuan Deng , Jiwei Zhang , Zhimin Zhang

Reproducing kernel Hilbert spaces (RKHSs) are key elements of many non-parametric tools successfully used in signal processing, statistics, and machine learning. In this work, we aim to address three issues of the classical RKHS based…

Signal Processing · Electrical Eng. & Systems 2019-05-09 Maria Peifer , Luiz. F. O. Chamon , Santiago Paternain , Alejandro Ribeiro

In this paper, we are concerned with a shape design problem, in which our target is to design, up to rigid transformations and scaling, the shape of an object given either its polarization tensor at multiple contrasts or the partial…

Optimization and Control · Mathematics 2013-10-24 Habib Ammari , Yat Tin Chow , Keji Liu , Jun Zou

Eigenvalue problems are fundamental to mathematics and science. We present a simple algorithm for determining eigenvalues and eigenfunctions of the Laplace--Beltrami operator on rather general curved surfaces. Our algorithm, which is based…

Numerical Analysis · Mathematics 2011-09-13 Colin B. Macdonald , Jeremy Brandman , Steven J. Ruuth

Eigenmaps are important in analysis, geometry, and machine learning, especially in nonlinear dimension reduction. Approximation of the eigenmaps of a Laplace operator depends crucially on the scaling parameter $\epsilon$. If $\epsilon$ is…

An approach is developed for constructing simple analytical formulae accurately approximating solutions to eigenvalue problems of quantum mechanics. This approach is based on self-similar approximation theory. In order to derive…

Condensed Matter · Physics 2009-10-31 V. I. Yukalov , E. P. Yukalova , S. Gluzman

The parameter imbedding method for the Fredholm equation converts it into an initial value problem in its parameter $\lambda$. We establish the method for general operator equations of the form $[I + \hat{f}(\lambda)]\psi = \phi $. It is…

Functional Analysis · Mathematics 2007-05-23 Cheng Geng , T. K. Kuo

The problem of estimating sparse eigenvectors of a symmetric matrix attracts a lot of attention in many applications, especially those with high dimensional data set. While classical eigenvectors can be obtained as the solution of a…

Machine Learning · Statistics 2016-11-03 Konstantinos Benidis , Ying Sun , Prabhu Babu , Daniel P. Palomar

Solutions of Fredholm integral equations of the second kind with oscillatory kernels likely exhibit oscillation. Standard numerical methods applied to solving equations of this type have poor numerical performance due to the influence of…

Numerical Analysis · Mathematics 2015-12-08 Yinkun Wang , Yuesheng Xu

Quantum mechanical calculations for material modelling using Kohn-Sham density functional theory (DFT) involve the solution of a nonlinear eigenvalue problem for $N$ smallest eigenvector-eigenvalue pairs with $N$ proportional to the number…

Computational Physics · Physics 2023-09-26 Sameer Khadatkar , Phani Motamarri

We consider radial complex scaling/perfectly matched layer methods for scalar resonance problems in homogeneous exterior domains. We introduce a new abstract framework to analyze the convergence of domain truncations and discretizations.…

Numerical Analysis · Mathematics 2020-07-21 Martin Halla

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…

We develop a stochastic approximation framework for learning nonlinear operators between infinite-dimensional spaces utilizing general Mercer operator-valued kernels. Our framework encompasses two key classes: (i) compact kernels, which…

Machine Learning · Statistics 2026-01-13 Jia-Qi Yang , Lei Shi

We present two algorithms for constructing orthonormal bases of rational function vectors with respect to a discrete inner product, and discuss how to use them for a rational approximation problem. Building on the pencil-based formulation…

Numerical Analysis · Mathematics 2026-01-21 Robbe Vermeiren

This paper concerns Fredholm theory in several variables, and its applications to Hilbert spaces of analytic functions. One feature is the introduction of ideas from commutative algebra to operator theory. Specifically, we introduce a…

Functional Analysis · Mathematics 2007-05-23 Xiang Fang

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

We investigate the pseudospectrum of the Kerr black hole, which indicates the instability of the spectrum of quasinormal modes (QNMs) of the Kerr black hole. Methodologically, we use the hyperboloidal framework to cast the QNM problem into…

General Relativity and Quantum Cosmology · Physics 2025-03-13 Rong-Gen Cai , Li-Ming Cao , Jia-Ning Chen , Zong-Kuan Guo , Liang-Bi Wu , Yu-Sen Zhou

This paper derives rates of convergence of certain approximations of the Koopman operators that are associated with discrete, deterministic, continuous semiflows on a complete metric space $(X,d_X)$. Approximations are constructed in terms…

Dynamical Systems · Mathematics 2020-04-14 Sai Tej Paruchuri , Jia Guo , Michael Kepler , Tim Ryan , Haoran Wang , Andrew J. Kurdila , Daniel Stilwell