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In this work we study the degenerate diffusion equation $\partial_{t}=x^{\alpha}a\left(x\right)\partial_{x}^{2}+b\left(x\right)\partial_{x}$ for $\left(x,t\right)\in\left(0,\infty\right)^{2}$, equipped with a Cauchy initial data and the…

Analysis of PDEs · Mathematics 2020-09-01 Linan Chen , Ian Weih-Wadman

This study presents a novel high-order numerical method designed for solving the two-dimensional time-fractional convection-diffusion (TFCD) equation. The Caputo definition is employed to characterize the time-fractional derivative. A weak…

Numerical Analysis · Mathematics 2023-08-21 Anshima Singh , Sunil Kumar

We present a novel approach that redefines the traditional interpretation of explicit and implicit discretization methods for solving a general class of advection-diffusion equations (ADEs) featuring nonlinear advection, diffusion…

Analysis of PDEs · Mathematics 2025-06-10 Amin Jafarimoghaddam , Manuel Soler , Irene Ortiz

We consider an optimal control problem on a bounded domain $\Omega\subset\mathbb{R}^2,$ governed by a parabolic convection--diffusion--reaction equation with pointwise control constraints. We follow the optimize--then--discretize approach,…

Numerical Analysis · Mathematics 2025-12-11 Christos Pervolianakis

In this paper we propose a numerical method to solve a 2D advection-diffusion equation, in the highly oscillatory regime. We use an efficient and robust integrator which leads to an accurate approximation of the solution without any time…

Numerical Analysis · Mathematics 2023-07-27 Clarissa Astuto , Mohammed Lemou , Giovanni Russo

The main contribution of this work is to construct and analyze stable and high order schemes to efficiently solve the two-dimensional time Caputo-Fabrizio fractional diffusion equation. Based on a third-order finite difference method in…

Numerical Analysis · Mathematics 2020-08-24 Fan Yu , Minghua Chen

In this paper, we discuss the steady and time-dependent nonlinear convection-diffusion (advection-diffusion) equations with the Dirichlet boundary condition. For the steady nonlinear equation, we use an iteration method to reformulate the…

Numerical Analysis · Mathematics 2025-07-28 Qiwei Feng , Catalin Trenchea

We study the large deviations principle for locally periodic stochastic differential equations with small noise and fast oscillating coefficients. There are three possible regimes depending on how fast the intensity of the noise goes to…

Probability · Mathematics 2012-04-05 Paul Dupuis , Konstantinos Spiliopoulos

The dispersion of a diffusive scalar in a fluid flowing through a network has many applications including to biological flows, porous media, water supply and urban pollution. Motivated by this, we develop a large-deviation theory that…

Fluid Dynamics · Physics 2016-09-14 Alexandra Tzella , Jacques Vanneste

In this paper, we address a time-dependent one-dimensional linear advection-diffusion equation with Dirichlet homogeneous boundary conditions. The equation is solved both analytically, using separation of variables, and numerically,…

Analysis of PDEs · Mathematics 2023-12-12 Eeshwar Prasad Poudel , Pitambar Acharya , Jeevan Kafle , Shreeram Khadka

We apply the macroscopic fluctuation theory to analyze the long-time statistics of the position of a tracer in the dense and the dilute limits of diffusive single-file systems. Our explicit results are about the corresponding large…

Statistical Mechanics · Physics 2023-02-01 Jagannath Rana , Tridib Sadhu

Based on the weighted and shifted Gr\"{u}nwald difference (WSGD) operators [24], we further construct the compact finite difference discretizations for the fractional operators. Then the discretization schemes are used to approximate the…

Numerical Analysis · Mathematics 2014-01-30 Han Zhou , WenYi Tian , Weihua Deng

Direct methods for the simulation of optimal control problems apply a specific discretization to the dynamics of the problem, and the discrete adjoint method is suitable to calculate corresponding conditions to approximate an optimal…

Developments in dynamical systems theory provides new support for the discretisation of \pde{}s and other microscale systems. By systematically resolving subgrid microscale dynamics the new approach constructs asymptotically accurate,…

Numerical Analysis · Mathematics 2009-04-07 Tony MacKenzie , A. J. Roberts

In this work we propose a nonlinear stabilization technique for convection-diffusion-reaction and pure transport problems discretized with space-time isogeometric analysis. The stabilization is based on a graph-theoretic artificial…

Numerical Analysis · Computer Science 2019-11-18 Jesús Bonilla , Santiago Badia

We provide a framework for high-order discretizations of nonlinear scalar convection-diffusion equations that satisfy a discrete maximum principle. The resulting schemes can have arbitrarily high order accuracy in time and space, and can be…

Numerical Analysis · Mathematics 2021-09-20 Manuel Quezada de Luna , David I. Ketcheson

In mathematical physics, the space-fractional diffusion equations are of particular interest in the studies of physical phenomena modelled by L\'{e}vy processes, which are sometimes called super-diffusion equations. In this article, we…

Numerical Analysis · Mathematics 2018-01-03 X. G. Zhu , Z. B. Yuan , F. Liu , Y. F. Nie

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

The Douglas--Rachford and Peaceman--Rachford splitting methods are common choices for temporal discretizations of evolution equations. In this paper we combine these methods with spatial discretizations fulfilling some easily verifiable…

Numerical Analysis · Mathematics 2016-05-10 Eskil Hansen , Erik Henningsson

Practical diffusion sampling is a numerical approximation problem: under a fixed inference budget, one must simulate a reverse-time ODE or SDE using only a limited number of denoising steps, so discretization error is often the dominant…

Machine Learning · Computer Science 2026-05-12 Samuel Hurault , Thomas Moreau , Gabriel Peyré