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We propose and analyze a linearly stabilized semi-implicit diffusive Crank--Nicolson scheme for the Cahn--Hilliard gradient flow. In this scheme, the nonlinear bulk force is treated explicitly with two second-order stabilization terms. This…

Numerical Analysis · Mathematics 2020-04-14 Lin Wang , Haijun Yu

We consider a one dimensional periodic forward-backward parabolic equation, regularized by a non-linear fourth order term of order $\epsilon^2\ll 1$. This equation is known in the literature as Cahn-Hilliard equation with degenerate…

Analysis of PDEs · Mathematics 2015-10-20 Matias G. Delgadino

We consider coarsening dynamics associated with a Burgers--Cahn--Hilliard system modeling a two-phase flow in one space dimension. Our emphasis is on the effect that coupling between the phase and fluid dynamics has on coarsening rates, and…

Analysis of PDEs · Mathematics 2024-05-21 Peter Howard , Adam Larios , Quyuan Lin

The Cahn--Hilliard equation is one of the most common models to describe phase separation processes of a mixture of two materials. For a better description of short-range interactions between the material and the boundary, various dynamic…

Analysis of PDEs · Mathematics 2021-04-27 Patrik Knopf , Kei Fong Lam , Chun Liu , Stefan Metzger

In this paper we establish a rigorous gradient flow structure for one-dimensional Kimura equations with respect to some Wasserstein-Shahshahani optimal transport geometry. This is achieved by first conditioning the underlying stochastic…

Analysis of PDEs · Mathematics 2022-10-03 Jean-Baptiste Casteras , Léonard Monsaingeon

We consider a Fokker-Planck equation which is coupled to an externally given time-dependent constraint on its first moment. This constraint introduces a Lagrange-multiplier which renders the equation nonlocal and nonlinear. In this paper we…

Analysis of PDEs · Mathematics 2018-11-28 Simon Eberle , Barbara Niethammer , André Schlichting

The Cahn--Hilliard equation is a widely used model that describes amongst others phase separation processes of binary mixtures or two-phase flows. In the recent years, different types of boundary conditions for the Cahn--Hilliard equation…

Numerical Analysis · Mathematics 2021-03-04 Stefan Metzger

We study the one-dimensional Cahn-Hilliard equation with an additional driving term representing, say, the effect of gravity. We find that the driving field $E$ has an asymmetric effect on the solution for a single stationary domain wall…

Condensed Matter · Physics 2009-10-28 C. L. Emmott , A. J. Bray

The scalar auxiliary variable (SAV) approach of Shen et al. (2018), which presents a novel way to discretize a large class of gradient flows, has been extended and improved by many authors for general dissipative systems. In this work we…

Numerical Analysis · Mathematics 2025-01-16 Kei Fong Lam , Ru Wang

The Cahn-Hilliard equation is a fundamental model that describes the phase separation process in multi-component mixtures. It has been successfully extended to many different contexts in several scientific fields. In this survey article, we…

Analysis of PDEs · Mathematics 2022-06-22 Hao Wu

The $L^2$ gradient flow of the Ginzburg-Landau free energy functional leads to the Allen Cahn equation that is widely used for modeling phase separation. Machine learning methods for solving the Allen-Cahn equation in its strong form suffer…

Machine Learning · Computer Science 2025-03-27 Revanth Mattey , Susanta Ghosh

In this work, we investigate links between the formulation of the flow of marginals of reversible diffusion processes as gradient flows in the space of probability measures and path wise large deviation principles for sequences of such…

Probability · Mathematics 2014-05-16 Max Fathi

In this paper, we consider numerical approximations for the viscous Cahn-Hilliard equation with hyperbolic relaxation. This type of equations processes energy-dissipative structure. The main challenge in solving such a diffusive system…

Numerical Analysis · Mathematics 2017-12-18 Xiaofeng Yang , Jia Zhao

The Cahn-Hilliard equation describes phase separation in binary liquids. Here we study this equation with spatially-varying sources and stirring, or advection. We specialize to symmetric mixtures and time-independent sources and discuss…

Fluid Dynamics · Physics 2017-10-26 Lennon O Naraigh , Jean-Luc Thiffeault

This paper is concerned with a rigorous convergence analysis of a fully discrete Lagrangian scheme for the Hele-Shaw flow, which is the fourth order thin-film equation with linear mobility in one space dimension. The discretization is based…

Numerical Analysis · Mathematics 2015-09-07 Horst Osberger , Daniel Matthes

In this paper, we study the sharp interface limit for solutions of the Cahn-Hilliard equation with disparate mobilities. This means that the mobility function degenerates in one of the two energetically favorable configurations, suppressing…

Analysis of PDEs · Mathematics 2022-01-19 Milan Kroemer , Tim Laux

Using the advective Cahn-Hilliard equation as a model, we illuminate the role of advection in phase-separating binary liquids. The advecting velocity is either prescribed, or is determined by an evolution equation that accounts for the…

Fluid Dynamics · Physics 2008-05-12 Lennon O Naraigh

The Navier-Stokes-Cahn-Hilliard (NSCH) system governs the diffuse-interface dynamics of two incompressible and immiscible fluids. We consider a relaxation approximation of the NSCH system that is composed by a system of first-order…

Numerical Analysis · Mathematics 2026-01-27 Jan Giesselmann , Jens Keim , Fabio Leotta , Christian Rohde

Non-equilibrium dynamics for relativistic fluid or quark gluon plasma (QGP) have already been calculated earlier upto third order using both kinetic and thermodynamic approaches. Calculations presented in this manuscript are based on…

Nuclear Theory · Physics 2020-09-09 Mohammed Younus , Azwinndini Muronga

Gradient flows of the Kullback--Leibler (KL) divergence, such as the Fokker--Planck equation and Stein Variational Gradient Descent, evolve a distribution toward a target density known only up to a normalizing constant. We introduce new…

Machine Learning · Statistics 2026-02-09 Elias Hess-Childs , Dejan Slepčev , Lantian Xu