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In the present paper, we consider large-scale differential Lyapunov matrix equations having a low rank constant term. We present two new approaches for the numerical resolution of such differential matrix equations. The first approach is…

Numerical Analysis · Mathematics 2017-05-30 M. Hached , K. Jbilou

This paper deals with the numerical approximation of the biharmonic inverse source problem in an abstract setting in which the measurement data is finite-dimensional. This unified framework in particular covers the conforming and…

Numerical Analysis · Mathematics 2021-06-15 Devika Shylaja , M. T. Nair

In this paper, we develop a numerical algorithm for an inverse problem on determining fractional orders of time derivatives simultaneously in a coupled subdiffusion system. Following the theoretical uniqueness, we reformulate the order…

Numerical Analysis · Mathematics 2025-08-19 Yikan Liu

As has been shown in our previous work, the parallel-in-time direct inverse (ParaDIn) method introduced by Yamaleev and Paudel in (arXiv: 2406.00878v1, 2024) imposes some constraint on the maximum number of time levels, $N_t$, that can be…

Numerical Analysis · Mathematics 2025-06-13 Subhash Paudel , Nail K. Yamaleev

In this paper, we propose a numerical method for turning point problems in one dimension based on Petrov-Galerkin finite element method (PGFEM). We first give a priori estimate for the turning point problem with a single boundary turning…

Numerical Analysis · Mathematics 2022-08-09 Li Feng , Zhongyi Huang

This paper can be seen as an attempt of rethinking the {\em Extra-Gradient Philosophy} for solving Variational Inequality Problems. We show that the properly defined {\em Reduced Gradients} can be used instead for finding approximate…

Optimization and Control · Mathematics 2023-12-05 Yurii Nesterov

This paper presents a numerical framework for the low-rank approximation of the solution to three-dimensional parabolic problems. The key contribution of this work is the tensorization process based on a tensor-train reformulation of the…

Numerical Analysis · Mathematics 2025-09-15 Gianmarco Manzini , Tommaso Sorgente

In this article, for a fourth-order parabolic equation which is closely related for example to the Cahn-Hilliard equation, we study an inverse source problem by interior data and the continuation of solution from lateral Cauchy data. Our…

Analysis of PDEs · Mathematics 2020-09-25 O. Yu. Imanuvilov , M. Yamamoto

The solution of sequences of shifted linear systems is a classic problem in numerical linear algebra, and a variety of efficient methods have been proposed over the years. Nevertheless, there still exist challenging scenarios witnessing a…

Numerical Analysis · Mathematics 2026-01-28 Hussam Al Daas , Davide Palitta

In this paper, we develop an ensemble-based time-stepping algorithm to efficiently find numerical solutions to a group of linear, second-order parabolic partial differential equations (PDEs). Particularly, the PDE models in the group could…

Numerical Analysis · Mathematics 2017-10-18 Yan Luo , Zhu Wang

A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the…

Numerical Analysis · Mathematics 2018-02-19 Yan Luo , Zhu Wang

In the present paper, we investigate the initial-boundary value problem for fractional order parabolic equation on a metric star graph in Sobolev spaces. First, we prove the existence and uniqueness results of strong solutions which are…

Analysis of PDEs · Mathematics 2024-09-02 R. R. Ashurov , Z. A Sobirov , A. A. Turemuratova

We propose a fast collocation method based on Krylov subspace iterative solver on general nonuniform grids for the fractional Laplacian problem, in which the fractional operator is presented in a singular integral formulation. The method is…

Numerical Analysis · Mathematics 2025-11-13 Meijie Kong , Hongfei Fu

Iterative Krylov projection methods have become widely used for solving large-scale linear inverse problems. However, methods based on orthogonality include the computation of inner-products, which become costly when the number of…

Numerical Analysis · Mathematics 2025-02-06 Malena Sabaté Landman , Ariana N. Brown , Julianne Chung , James G. Nagy

Inverse problems are pervasive mathematical methods in inferring knowledge from observational and experimental data by leveraging simulations and models. Unlike direct inference methods, inverse problem approaches typically require many…

Computational Physics · Physics 2019-12-20 Sheroze Sheriffdeen , Jean C. Ragusa , Jim E. Morel , Marvin L. Adams , Tan Bui-Thanh

This paper provides a new regularization method which is particularly suitable for linear exponentially ill-posed problems. Under logarithmic source conditions (which have a natural interpretation in terms of Sobolev spaces in the…

Numerical Analysis · Mathematics 2020-07-08 Walter Cedric Simo Tao Lee

To solve optimization problems with parabolic PDE constraints, often methods working on the reduced objective functional are used. They are computationally expensive due to the necessity of solving both the state equation and a…

Optimization and Control · Mathematics 2019-12-17 Sebastian Götschel , Michael L. Minion

In this paper, we develop a straightforward $C^0$ linear finite element method for sixth-order elliptic equations. The basic idea is to use gradient recovery techniques to generate higher-order numerical derivatives from a $C^0$ linear…

Numerical Analysis · Mathematics 2018-04-17 Hailong Guo , Zhimin Zhang , Qingsong Zou

When an iterative method is applied to solve the linear equation system in interior point methods (IPMs), the attention is usually placed on accelerating their convergence by designing appropriate preconditioners, but the linear solver is…

Optimization and Control · Mathematics 2023-04-28 Filippo Zanetti , Jacek Gondzio

A fundamental task in numerical computation is the solution of large linear systems. The conjugate gradient method is an iterative method which offers rapid convergence to the solution, particularly when an effective preconditioner is…

Methodology · Statistics 2018-12-18 Jon Cockayne , Chris Oates , Ilse Ipsen , Mark Girolami