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A novel second order family of explicit stabilized Runge-Kutta-Chebyshev methods for advection-diffusion-reaction equations is introduced. The new methods outperform existing schemes for relatively high Peclet number due to their favorable…

Numerical Analysis · Mathematics 2023-06-09 Ibrahim Almuslimani

We study the worst-case behavior of Block Coordinate Descent (BCD) type algorithms for unconstrained minimization of coordinate-wise smooth convex functions. This behavior is indeed not completely understood, and the practical success of…

Optimization and Control · Mathematics 2025-07-23 Yassine Kamri , François Glineur , Julien M. Hendrickx , Ion Necoara

In this paper, we propose numerical scheme for the Riesz space fractional advection-dispersion equations with delay (RFADED). Firstly, analytical solution for RFADED in terms of the functions of Mittag-Leffler type is derived. Secondly, the…

Numerical Analysis · Mathematics 2021-07-22 M. Saedshoar Heris , M. Javidi

We propose an alternative method for one-dimensional continuum diffusion models with spatially variable (heterogeneous) diffusivity. Our method, which extends recent work on stochastic diffusion, assumes the constant-coefficient homogenized…

Computational Physics · Physics 2019-12-18 Elliot J. Carr

In this paper, we present a meshless hybrid method combining the Generalized Finite Difference (GFD) and Finite Difference based Radial Basis Function (RBF-FD) approaches to solve non-homogeneous partial differential equations (PDEs)…

Numerical Analysis · Mathematics 2025-05-02 Priyal Garg , T. V. S. Sekhar

We consider structure-preserving methods for conservative systems, which rigorously replicate the conservation property yielding better numerical solutions. There, corresponding to the skew-symmetry of the differential operator, that of…

Numerical Analysis · Mathematics 2016-07-19 Daisuke Furihata , Shun Sato , Takayasu Matsuo

We introduce and study a notion of Asymptotic Preserving schemes, related to convergence in distribution, for a class of slow-fast Stochastic Differential Equations. In some examples, crude schemes fail to capture the correct limiting…

Numerical Analysis · Mathematics 2020-11-05 Charles-Edouard Bréhier , Shmuel Rakotonirina-Ricquebourg

This dissertation explores block decomposable methods for large-scale optimization problems. It focuses on alternating direction method of multipliers (ADMM) schemes and block coordinate descent (BCD) methods. Specifically, it introduces a…

Optimization and Control · Mathematics 2026-01-15 Leandro Farias Maia

This paper develops a two-level fourth-order scheme for solving time-fractional convection-diffusion-reaction equation with variable coefficients subjected to suitable initial and boundary conditions. The basis properties of the new…

Numerical Analysis · Mathematics 2022-04-20 Eric Ngondiep

We present a systematic methodology to develop high order accurate numerical approaches for linear advection problems. These methods are based on evolving parts of the jet of the solution in time, and are thus called jet schemes. Through…

Numerical Analysis · Mathematics 2023-08-17 Benjamin Seibold , Jean-Christophe Nave , Rodolfo Ruben Rosales

Coordinate descent algorithms are widely used in machine learning and large-scale data analysis due to their strong optimality guarantees and impressive empirical performance in solving non-convex problems. In this work, we introduce Block…

Optimization and Control · Mathematics 2024-12-17 Zhijie Yuan , Ganzhao Yuan , Lei Sun

In this study, we present a comprehensive global spectral analysis of the convection dispersion equation, which is also referred to in specific contexts as the Korteweg de Vries (KdV) equation, to investigate the behaviour of high order…

Numerical Analysis · Mathematics 2025-07-22 Lavanya V Salian , Vivek S Yadav , Rathan Samala , Rakesh Kumar

In this paper, a positivity-preserving fifth-order finite volume compact-WENO scheme is proposed for solving compressible Euler equations. As we know conservative compact finite volume schemes have high resolution properties while WENO…

Numerical Analysis · Mathematics 2015-06-18 Yan Guo , Tao Xiong , Yufeng Shi

We introduce a locally divergence-free local characteristic decomposition based path-conservative central-upwind (LCD-PCCU) scheme for ideal magnetohydrodynamics (MHD) equations. The proposed method is a low-dissipation extension of the…

Numerical Analysis · Mathematics 2025-12-19 Shaoshuai Chu , Alexander Kurganov , Maria Lukacova-Medvidova , Mingye Na

In this paper, we consider the development and analysis of a new explicit compact high-order finite difference scheme for acoustic wave equation formulated in divergence form, which is widely used to describe seismic wave propagation…

Numerical Analysis · Mathematics 2020-03-24 Da Li , Keran Li , Wenyuan Liao

We present a forward semi-Lagrangian numerical method for systems of transport equations able to advect smooth and discontinuous fields with high-order accuracy. The numerical scheme is composed of an integration of the transport equations…

Computational Physics · Physics 2014-10-13 Julián Becerra-Sagredo , Carlos Málaga , Francisco Mandujano

The ideal MHD equations are a central model in astrophysics, and their solution relies upon stable numerical schemes. We present an implementation of a new method, which possesses excellent stability properties. Numerical tests demonstrate…

Instrumentation and Methods for Astrophysics · Physics 2011-04-28 Knut Waagan , Christoph Federrath , Christian Klingenberg

A discretization scheme is introduced for a set of convection-diffusion equations with a non-linear reaction term, where the convection velocity is constant for each reactant. This constancy allows a transformation to new spatial variables,…

Computational Physics · Physics 2017-09-19 József Vass , Sergey N. Krylov

Discrete diffusion models have emerged as powerful frameworks for generating structured categorical data. However, efficiently sampling from reward-tilted distributions remains a fundamental challenge. While Twisted Sequential Monte Carlo…

Machine Learning · Computer Science 2026-05-25 Jaihoon Kim , Taehoon Yoon , Prin Phunyaphibarn , Seungjun Kim , Morteza Mardani , Minhyuk Sung

Treating diffusion and advection/reaction separately is an effective strategy for solving semilinear advection-diffusion-reaction equations. However, such an approach is prone to suffer from order reduction, especially in the presence of…

Numerical Analysis · Mathematics 2025-11-12 Thi Tam Dang , Lukas Einkemmer , Alexander Ostermann
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