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The convergence of Boltzmann Fokker Planck solution can become arbitrarily slow with iterative procedures like source iteration. This paper derives and investigates a nonlinear diffusion acceleration scheme for the solution of the Boltzmann…

Numerical Analysis · Mathematics 2023-12-06 Japan K. Patel , Barry D. Ganapol , Martha M. Matuszak

In this work, we introduce an iterative linearised finite element method for the solution of Bingham fluid flow problems. The proposed algorithm has the favourable property that a subsequence of the sequence of iterates generated converges…

Numerical Analysis · Mathematics 2021-09-14 Pascal Heid , Endre Süli

In the literature there are several methods for comparing two convergent iterative processes for the same problem. In this note we have in view mostly the one introduced by Berinde in [Picard iteration converges faster than Mann iteration…

Optimization and Control · Mathematics 2025-09-03 C. Zalinescu

Diffusion models have recently attained significant interest within the community owing to their strong performance as generative models. Furthermore, its application to inverse problems have demonstrated state-of-the-art performance.…

Image and Video Processing · Electrical Eng. & Systems 2022-03-22 Hyungjin Chung , Byeongsu Sim , Jong Chul Ye

Iterative algorithms aimed at solving some problems are discussed. For certain problems, such as finding a common point in the intersection of a finite number of convex sets, there often exist iterative algorithms that impose very little…

Optimization and Control · Mathematics 2010-09-28 Y. Censor , R. Davidi , G. T. Herman

This paper presents and analyzes a discontinuous Galerkin method for the incompressible three-phase flow problem in porous media. We use a first order time extrapolation which allows us to solve the equations implicitly and sequentially. We…

Numerical Analysis · Mathematics 2022-01-12 Giselle Sosa Jones , Beatrice Riviere , Loic Cappanera

Diffusion processes are a class of stochastic differential equations (SDEs) providing a rich family of expressive models that arise naturally in dynamic modelling tasks. Probabilistic inference and learning under generative models with…

Machine Learning · Computer Science 2024-02-28 Prakhar Verma , Vincent Adam , Arno Solin

A model for diffusion on a cubic lattice with a random distribution of traps is developed. The traps are redistributed at certain time intervals. Such models are useful for describing systems showing dynamic disorder, such as ion-conducting…

Condensed Matter · Physics 2009-10-31 S. Mandal , R. Dasgupta

The paper presents a comparative analysis of iterative numerical methods of Jacobi and Gauss-Seidel for solving systems of linear algebraic equations (SLAEs) with complex and real matrices. The ranges of convergence for both methods for…

Numerical Analysis · Mathematics 2024-02-19 Pavel Khrapov , Nikita Volkov

Solving linear systems is a ubiquitous task in science and engineering. Because directly inverting a large-scale linear system can be computationally expensive, iterative algorithms are often used to numerically find the inverse. To…

Numerical Analysis · Mathematics 2021-07-20 Zheyuan Zhu , Andrew B. Klein , Guifang Li , Shuo Pang

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when…

Methodology · Statistics 2018-02-14 Daniela Calvetti , Matthew M. Dunlop , Erkki Somersalo , Andrew M. Stuart

In this paper we analyse convergence of projected fixed-point iteration on a Riemannian manifold of matrices with fixed rank. As a retraction method we use `projector splitting scheme'. We prove that the projector splitting scheme converges…

Numerical Analysis · Mathematics 2016-04-08 Denis Kolesnikov , Ivan Oseledets

In this paper, we consider the shift-inverse method with Richardson iteration step for the eigenvalue problems. It will be shown that the convergence speed depends heavily on the eigenvalue gap between the desired eigenvalue and undesired…

Numerical Analysis · Mathematics 2018-04-06 Yunhui He , Hehu Xie

We propose to solve inverse problems involving the temporal evolution of physics systems by leveraging recent advances from diffusion models. Our method moves the system's current state backward in time step by step by combining an…

Machine Learning · Computer Science 2023-12-06 Benjamin J. Holzschuh , Simona Vegetti , Nils Thuerey

We describe a new, faster implicit algorithm for solving the radiation hydrodynamics equations in the flux-limited diffusion approximation for smoothed particle hydrodynamics. This improves on the method elucidated in Whitehouse & Bate by…

Astrophysics · Physics 2009-11-13 Stuart C. Whitehouse , Matthew R. Bate , Joe J. Monaghan

An iterative scheme is presented to solve analytically the relativistic fluid dynamics equations. The scheme is applied to longitudinal expansion, transversal symmetric and transversal asymmetric (triaxial) expansion as well. Within this…

High Energy Physics - Theory · Physics 2012-12-06 F. Wunderlich , B. Kämpfer

In these lectures I give an introduction to the time-dependent approach to inverse scattering, that has been developed recently. The aim of this approach is to solve various inverse scattering problems with time-dependent methods that…

Mathematical Physics · Physics 2007-05-23 Ricardo Weder

This article performs a unified convergence analysis of a variety of numerical methods for a model of the miscible displacement of one incompressible fluid by another through a porous medium. The unified analysis is enabled through the…

Numerical Analysis · Mathematics 2018-03-07 Jérôme Droniou , Robert Eymard , Alain Prignet , Kyle S. Talbot

Numerical solutions for flows in partially saturated porous media pose challenges related to the non-linearity and elliptic-parabolic degeneracy of the governing Richards' equation. Iterative methods are therefore required to manage the…

Numerical Analysis · Mathematics 2024-02-02 Nicolae Suciu , Florin A. Radu , Jakob S. Stokke , Emil Cătinaş , Andra Malina

Training diffusion models is always a computation-intensive task. In this paper, we introduce a novel speed-up method for diffusion model training, called, which is based on a closer look at time steps. Our key findings are: i) Time steps…

Machine Learning · Computer Science 2025-03-26 Kai Wang , Mingjia Shi , Yukun Zhou , Zekai Li , Zhihang Yuan , Yuzhang Shang , Xiaojiang Peng , Hanwang Zhang , Yang You