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In this paper, we present a novel second-order generalised rotational discrete gradient scheme for numerically approximating the orthonormal frame gradient flow of biaxial nematic liquid crystals. This scheme relies on reformulating the…

Numerical Analysis · Mathematics 2023-10-17 Hanbin Wang , Jie Xu , Zhiguo Yang

In this paper, we consider mixed finite element semi-/full discretizations of the Rosensweig ferrofluid flow model. We first establish some regularity results for the model under several basic assumptions. Then we show that the energy…

Numerical Analysis · Mathematics 2024-12-03 Yongke Wu , Xiaoping Xie

In this work, we propose a structure-preserving discretisation for the recently studied Cahn-Hilliard-Biot system using conforming finite elements in space and problem-adapted explicit-implicit Euler time integration. We prove that the…

Numerical Analysis · Mathematics 2024-07-18 Aaron Brunk , Marvin Fritz

This paper develops the high-order accurate entropy stable finite difference schemes for one- and two-dimensional special relativistic hydrodynamic equations. The schemes are built on the entropy conservative flux and the weighted…

Numerical Analysis · Mathematics 2020-03-30 Junming Duan , Huazhong Tang

In this work, we develop a new hydrostatic reconstruction procedure to construct well-balanced schemes for one and multilayer shallow water flows, including wetting and drying. Initially, we derive the method for a path-conservative finite…

Numerical Analysis · Mathematics 2024-06-21 Patrick Ersing , Sven Goldberg , Andrew R. Winters

We present a novel approximate inference method for diffusion processes, based on the Wasserstein gradient flow formulation of the diffusion. In this formulation, the time-dependent density of the diffusion is derived as the limit of…

Machine Learning · Statistics 2018-06-13 Charlie Frogner , Tomaso Poggio

This paper presents a family of spatial discretisations of the nonlinear rotating shallow-water equations that conserve both energy and potential enstrophy. These are based on two-dimensional mixed finite element methods and hence, unlike…

Numerical Analysis · Mathematics 2015-06-16 Andrew T. T. McRae , Colin J. Cotter

We present a method to efficiently compute Wasserstein gradient flows. Our approach is based on a generalization of the back-and-forth method (BFM) introduced by Jacobs and L\'eger to solve optimal transport problems. We evolve the gradient…

Numerical Analysis · Mathematics 2020-11-17 Matt Jacobs , Wonjun Lee , Flavien Léger

Second-order flows in this paper refer to some artificial evolutionary differential equations involving second-order time derivatives distinguished from gradient flows which are considered to be first-order flows. This is a popular topic…

Numerical Analysis · Mathematics 2023-01-09 Haifan Chen , Guozhi Dong , Wei Liu , Ziqing Xie

We prove an existence result for a large class of PDEs with a nonlinear Wasserstein gradient flow structure. We use the classical theory of Wasserstein gradient flow to derive an EDI formulation of our PDE and prove that under some…

Analysis of PDEs · Mathematics 2024-07-31 Thibault Caillet , Filippo Santambrogio

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

Many studies have been conducted on flows of probability measures, often in terms of gradient flows. We utilize a generalized notion of derivatives with respect to time to model the instantaneous evolution of empirically observed…

Methodology · Statistics 2021-09-16 Yaqing Chen , Hans-Georg Müller

We design and analyse an energy stable, structure preserving and well-balanced scheme for the Ripa system of shallow water equations. The energy stability of the numerical solutions is achieved by introducing appropriate stabilisation terms…

Numerical Analysis · Mathematics 2024-10-29 K. R. Arun , Rahuldev Ghorai

This paper introduces a robust reformulation of the incompressible Navier-Stokes equations, establishing a foundational framework for designing efficient, structure-preserving algorithms that strictly conserve the original energy…

Numerical Analysis · Mathematics 2025-08-12 Zihan Weng , Qi Hong , Chunwu Wang , Yuezheng Gong

In this paper, we design and analyze second order positive and free energy satisfying schemes for solving diffusion equations with interaction potentials. The semi-discrete scheme is shown to conserve mass, preserve solution positivity, and…

Numerical Analysis · Mathematics 2020-08-26 Hailiang Liu , Wumaier Maimaitiyiming

This study proposes and analyses a novel higher-order, structure preserving discretization method for inviscid barotropic flows from a Lagrangian perspective. The method is built on a multisymplectic variational principle discretized over a…

Numerical Analysis · Mathematics 2025-12-10 Mukthesh Mahadev , Marc Gerritsma

This paper aims to investigate the diffusion behavior of particles moving in stochastic flows under a structure-preserving scheme. We compute the effective diffusivity for normal diffusive random flows and establish the power law between…

Numerical Analysis · Mathematics 2024-05-30 Tan Zhang , Zhongjian Wang , Jack Xin , Zhiwen Zhang

Existence and uniqueness of global in time measure solution for a one dimensional nonlinear aggregation equation is considered. Such a system can be written as a conservation law with a velocity field computed through a selfconsistant…

Analysis of PDEs · Mathematics 2014-09-05 Francois James , Nicolas Vauchelet

We present a new numerical scheme for one dimensional dynamical systems. This is a modification of the discrete gradient method and keeps its advantages, including the stability and the conservation of the energy integral. However, its…

Numerical Analysis · Computer Science 2015-05-13 Jan L. Cieslinski , Boguslaw Ratkiewicz

Recently, optimization on the Riemannian manifold have provided valuable insights to the optimization community. In this regard, extending these methods to to the Wasserstein space is of particular interest, since optimization on…

Machine Learning · Computer Science 2025-11-05 Mingyang Yi , Bohan Wang