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The alternating direction method of multipliers (ADMM) were extensively investigated in the past decades for solving separable convex optimization problems. Fewer researchers focused on exploring its convergence properties for the nonconvex…

Numerical Analysis · Mathematics 2019-07-02 Jianchao Bai , Junli Liang , Ke Guo , Yang Jing

Beamforming is an essential step in the ultrasound image formation pipeline and has recently attracted growing interest. An important goal of beamforming is to increase the image spatial resolution, or in other words to narrow down the…

Image and Video Processing · Electrical Eng. & Systems 2022-09-01 Sobhan Goudarzi , Adrian Basarab , Hassan Rivaz

The authors study the spectral theory of self-adjoint operators that are subject to certain types of perturbations. An iterative introduction of infinitely many randomly coupled rank-one perturbations is one of our settings. Spectral…

Spectral Theory · Mathematics 2019-02-08 Dale Frymark , Constanze Liaw

It is significant and challenging to solve eigenvalue problems of partial differential operators when many highly accurate eigenpair approximations are required. The adaptive finite element discretization based parallel orbital-updating…

Numerical Analysis · Mathematics 2025-09-24 Xiaoying Dai , Yan Li , Bin Yang , Aihui Zhou

Approaches to automated grouping in singular spectrum analysis are considered. A new method for the identification of periodic components is proposed. The possibilities of extensions to multivariate time series and images are discussed.

Methodology · Statistics 2023-02-20 Nina Golyandina , Polina Zhornikova

The spectral and localization properties of $\mathcal{PT}$-symmetric optical superlattices, either infinitely extended or truncated at one side, are theoretically investigated, and the criteria that ensure a real energy spectrum are…

Quantum Physics · Physics 2015-06-18 Stefano Longhi

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

Gradient descent algorithms perform well in convex optimization but can get tied for finding local minima in non-convex optimization. A robust method that combines a spectral approach with nonmonotone line search strategy for solving…

Optimization and Control · Mathematics 2025-01-07 Oday Hazaimah

We explore the applicability of splitting methods involving complex coefficients to solve numerically the time-dependent Schr\"odinger equation. We prove that a particular class of integrators are conjugate to unitary methods for…

Numerical Analysis · Mathematics 2021-09-16 S. Blanes , F. Casas , A. Escorihuela-Tomàs

The ultraspherical spectral method features high accuracy and fast solution. In this article, we determine the sources of error arising from the ultraspherical spectral method and derive its effective condition number, which explains why…

Numerical Analysis · Mathematics 2024-05-21 Lu Cheng , Kuan Xu

In this paper, we present a mathematically rigorous quantum-mechanical treatment of a one-dimensional motion of a particle in the Calogero potential $\alpha x^{-2}$. Although the problem is quite old and well-studied, we believe that our…

Quantum Physics · Physics 2015-05-13 D. M. Gitman , I. V. Tyutin , B. L. Voronov

Spectral embedding uses eigenfunctions of the discrete Laplacian on a weighted graph to obtain coordinates for an embedding of an abstract data set into Euclidean space. We propose a new pre-processing step of first using the eigenfunctions…

Machine Learning · Statistics 2016-07-18 Alexander Cloninger , Stefan Steinerberger

We introduce a novel spectral element method based on the ultraspherical spectral method and the hierarchical Poincar\'{e}-Steklov scheme for solving second-order linear partial differential equations on polygonal domains with unstructured…

Numerical Analysis · Mathematics 2021-05-19 Daniel Fortunato , Nicholas Hale , Alex Townsend

In this note, we solve an inverse spectral problem for a class of finite band symmetric matrices. We provide necessary and sufficient conditions for a matrix valued function to be a spectral function of the operator corresponding to a…

Mathematical Physics · Physics 2017-11-02 Mikhail Kudryavtsev , Sergio Palafox , Luis O. Silva

In this paper, we analyze the convergence of several discretize-then-optimize algorithms, based on either a second-order or a fourth-order finite difference discretization, for solving elliptic PDE-constrained optimization or optimal…

Numerical Analysis · Mathematics 2018-08-14 Jun Liu , Zhu Wang

This paper describes a new algorithm for determining all discrete contact symmetries of any differential equation whose Lie contact symmetries are known. The method is constructive and is easy to use. It is based upon the observation that…

Dynamical Systems · Mathematics 2015-06-26 Peter E. Hydon

Mirror symmetry of a wave system imposes corresponding even or odd parity on its eigenmodes. For a discrete system, eigenmode parity on a specific subset of sites may also originate from so-called latent symmetry. This symmetry is hidden,…

Classical Physics · Physics 2023-03-01 Malte Röntgen , Christian V. Morfonios , Peter Schmelcher , Vincent Pagneux

Quasi-equilibrium approximation is a widely used closure approximation approach for model reduction with applications in complex fluids, materials science, etc. It is based on the maximum entropy principle and leads to thermodynamically…

Numerical Analysis · Mathematics 2021-10-19 Shan Jiang , Haijun Yu

This paper reports on recent work to compute the asymptotic solution of a n-th order ordinary differential equation. Symbolic methods are used to compute the asymptotics over a large region. Application is made to the computation of the…

Spectral Theory · Mathematics 2025-10-20 B. M. Brown , M. S. P. Eastham , D. K. R. McCormack , W. D. Evans

This work unifies the analysis of various randomized methods for solving linear and nonlinear inverse problems by framing the problem in a stochastic optimization setting. By doing so, we show that many randomized methods are variants of a…

Numerical Analysis · Mathematics 2023-06-21 Jonathan Wittmer , C. G. Krishnanunni , Hai V. Nguyen , Tan Bui-Thanh