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Partitioning for load balancing is a crucial first step to parallelize any type of computation. In this work, we propose SGORP, a new spatial partitioning method based on Subgradient Optimization, to solve the $d$-dimensional Rectilinear…

Data Structures and Algorithms · Computer Science 2023-10-05 Muhammed Fatih Balin , Xiaojing An , Abdurrahman Yaşar , Ümit V. Çatalyürek

An efficient direct solver for solving the Lippmann-Schwinger integral equation modeling acoustic scattering in the plane is presented. For a problem with $N$ degrees of freedom, the solver constructs an approximate inverse in…

Numerical Analysis · Mathematics 2020-07-28 Abinand Gopal , Per-Gunnar Martinsson

This paper presents a new finite difference algorithm for solving the 2D one-way wave equation with a preliminary approximation of a pseudo-differential operator by a system of partial differential equations. As opposed to the existing…

Numerical Analysis · Mathematics 2017-03-02 Andrew V. Terekhov

Gradient compression is of growing interests for solving constrained optimization problems including compressed sensing, noisy recovery and matrix completion under limited communication resources and storage costs. Convergence analysis of…

Optimization and Control · Mathematics 2024-10-30 Zhaoyue Xia , Jun Du , Chunxiao Jiang , H. Vincent Poor , Yong Ren

This paper presents a universal numerical scheme tailored for tackling linear integral, integro-differential, and both initial and boundary value problems of ordinary differential equations. The numerical scheme is readily adapted for…

General Mathematics · Mathematics 2026-01-23 Vladimir Kryzhniy

This paper considers the approximation of partial differential equations with a point collocation framework based on high-order local maximum-entropy schemes (HOLMES). In this approach, smooth basis functions are computed through an…

Computational Engineering, Finance, and Science · Computer Science 2020-11-02 F. Greco , M. Arroyo

Several tensor eigenpair definitions have been put forth in the past decade, but these can all be unified under generalized tensor eigenpair framework, introduced by Chang, Pearson, and Zhang (2009). Given mth-order, n-dimensional…

Numerical Analysis · Mathematics 2014-12-22 Tamara G. Kolda , Jackson R. Mayo

For the numerical solution of the Lippmann-Schwinger equation, while the pre-corrected trapezoidal rule converges with high-order for smooth compactly supported densities, it exhibits only the linear convergence in the case of discontinuity…

Numerical Analysis · Mathematics 2020-07-14 Ambuj Pandey , Akash Anand

This paper addresses the efficient solution of linear systems arising from curl-conforming finite element discretizations of $H(\mathrm{curl})$ elliptic problems with heterogeneous coefficients. We first employ the discrete form of a…

Numerical Analysis · Mathematics 2025-06-10 Chupeng Ma , Yongwei Zhang

We propose a high-order adaptive numerical solver for the semilinear elliptic boundary value problem modelling magnetic plasma equilibrium in axisymmetric confinement devices. In the fixed boundary case, the equation is posed on curved…

Computational Physics · Physics 2021-05-28 Tonatiuh Sánchez-Vizuet , Manuel E. Solano , Antoine J. Cerfon

We focus here on a class of fourth-order parabolic equations that can be written as a system of second-order equations by introducing an auxiliary variable. We design a novel second-order fully discrete mixed finite element method to…

Numerical Analysis · Mathematics 2020-08-28 Sana Keita , Abdelaziz Beljadid , Yves Bourgault

A version of the Dynamical Systems Method (DSM) for solving ill-posed nonlinear equations with monotone operators in a Hilbert space is studied in this paper. An a posteriori stopping rule, based on a discrepancy-type principle is proposed…

Numerical Analysis · Mathematics 2015-05-13 N. S. Hoang , A. G. Ramm

PDDSparse is a new hybrid parallelisation scheme for solving large-scale elliptic boundary value problems on supercomputers, which can be described as a Feynman-Kac formula for domain decomposition. At its core lies a stochastic linear,…

Numerical Analysis · Mathematics 2023-12-08 Francisco Bernal , Jorge Morón-Vidal

We propose a fast algorithm for computing the GMM estimator in the BLP demand model (Berry, Levinsohn, and Pakes, 1995). Inspired by nested pseudo-likelihood methods for dynamic discrete choice models, our approach avoids repeatedly solving…

Econometrics · Economics 2026-02-09 Victor Aguirregabiria , Hui Liu , Yao Luo

We propose a unified derivative-free proximal Newton-type algorithm framework for solving composite optimization problems formulated as the sum of a black-box function and a known regularization term. We establish the iteration and oracle…

Optimization and Control · Mathematics 2026-05-08 Zekun Liu , Jinyan Fan

This paper examines inverse Cauchy problems that are governed by a kind of elliptic partial differential equation. The inverse problems involve recovering the missing data on an inaccessible boundary from the measured data on an accessible…

Numerical Analysis · Mathematics 2023-12-01 Rongfang Gong , Min Wang , Qin Huang , Ye Zhang

In this paper, we develop a class of high-order conservative methods for simulating non-equilibrium radiation diffusion problems. Numerically, this system poses significant challenges due to strong nonlinearity within the stiff source terms…

Numerical Analysis · Mathematics 2024-01-30 Shaoqin Zheng , Min Tang , Qiang Zhang , Tao Xiong

A nonlinear Helmholtz (NLH) equation with high frequencies and corner singularities is discretized by the linear finite element method (FEM). After deriving some wave-number-explicit stability estimates and the singularity decomposition for…

Numerical Analysis · Mathematics 2024-05-28 Run Jiang , Haijun Wu , Yifeng Xu , Jun Zou

The generalized eigenvalue problem (GEP) serves as a cornerstone in a wide range of applications in numerical linear algebra and scientific computing. However, traditional approaches that aim to maximize the classical Rayleigh quotient…

Optimization and Control · Mathematics 2025-07-04 Xiaozhi Liu , Yong Xia

In this paper we generalize the Interior Point-Proximal Method of Multipliers (IP-PMM) presented in [An Interior Point-Proximal Method of Multipliers for Convex Quadratic Programming, Computational Optimization and Applications, 78,…

Optimization and Control · Mathematics 2021-09-09 Spyridon Pougkakiotis , Jacek Gondzio
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