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We establish convergence results for a spatial semidiscretization of Mean Curvature Flow (MCF) for surfaces with fixed boundaries. Our analysis is based on Huisken's evolution equations for the mean curvature and the normal vector, enabling…

Numerical Analysis · Mathematics 2025-04-29 Bárbara Solange Ivaniszyn , Pedro Morin , M. Sebastián Pauletti

In this paper a new semi-implicit relaxation scheme for the simulation of multi-scale hyperbolic conservation laws based on a Jin-Xin relaxation approach is presented. It is based on the splitting of the flux function into two or more…

Numerical Analysis · Mathematics 2025-02-24 Andrea Thomann

We provide a new proof of convergence to motion by mean curvature (MMC) for the Merriman-Bence-Osher (MBO) thresholding algorithm. The proof is elementary and does not rely on maximum principle for the scheme. The strategy is to construct a…

Analysis of PDEs · Mathematics 2017-03-21 Drew Swartz , Nung Kwan Yip

We introduce an inferential framework for a wide class of semi-linear stochastic differential equations (SDEs). Recent work has shown that numerical splitting schemes can preserve critical properties of such types of SDEs, give rise to…

Computation · Statistics 2025-07-22 Shu Huang , Richard G. Everitt , Massimiliano Tamborrino , Adam M. Johansen

Phase-field models such as the Allen-Cahn equation may give rise to the formation and evolution of geometric shapes, a phenomenon that may be analyzed rigorously in suitable scaling regimes. In its sharp-interface limit, the vectorial…

Analysis of PDEs · Mathematics 2022-04-01 Julian Fischer , Alice Marveggio

We study the systematic numerical approximation of a class of Allen-Cahn type problems modeling the motion of phase interfaces. The common feature of these models is an underlying gradient flow structure which gives rise to a decay of an…

Numerical Analysis · Mathematics 2017-03-09 Anke Böttcher , Herbert Egger

We present a positivity preserving variational scheme for the phase-field modeling of incompressible two-phase flows with high density ratio and using meshes of arbitrary topology. The variational finite element technique relies on the…

Fluid Dynamics · Physics 2018-07-05 Vaibhav Joshi , Rajeev K. Jaiman

A high-order quasi-conservative discontinuous Galerkin (DG) method is proposed for the numerical simulation of compressible multi-component flows. A distinct feature of the method is a predictor-corrector strategy to define the grid…

Numerical Analysis · Mathematics 2021-01-18 Dongmi Luo , Shiyi Li , Weizhang Huang , Jianxian Qiu , Yibing Chen

We perform a rigorous examination of the sharp interface limit of a coupled Navier-Stokes and mass-conserving Allen-Cahn system in a two-dimensional, bounded, and smooth domain as the parameter $\varepsilon > 0$, representing the thickness…

Analysis of PDEs · Mathematics 2026-04-14 Helmut Abels , Hanifah Mumtaz

We consider a mass conserved Allen-Cahn equation $u_t=\Delta u+ \e^{-2} (f(u)-\e\lambda(t))$ in a bounded domain with no flux boundary condition, where $\e\lambda(t)$ is the average of $f(u(\cdot,t))$ and $-f$ is the derivative of a double…

Analysis of PDEs · Mathematics 2017-03-29 Xinfu Chen , Danielle Hilhorst , Elisabeth Logak

We present a new high-resolution, non-oscillatory semi-discrete central-upwind scheme for one-dimensional two-layer shallow-water flows with friction and entrainment along channels with arbitrary cross sections and bottom topography. These…

Numerical Analysis · Mathematics 2021-04-08 Gerardo Hernandez-Duenas , Jorge Balbas

A popular approach to semi-supervised learning proceeds by endowing the input data with a graph structure in order to extract geometric information and incorporate it into a Bayesian framework. We introduce new theory that gives appropriate…

Machine Learning · Statistics 2020-01-14 Nicolas Garcia Trillos , Zachary Kaplan , Thabo Samakhoana , Daniel Sanz-Alonso

We propose Annealed Langevin Monte Carlo for Flow ODE Sampling (ALMC-ODE), a method for generating samples from unnormalized target distributions, with a particular emphasis on multimodal densities that are challenging for standard Markov…

Computation · Statistics 2026-05-01 Hanwen Huang

In this article we consider static Bayesian parameter estimation for partially observed diffusions that are discretely observed. We work under the assumption that one must resort to discretizing the underlying diffusion process, for…

Computation · Statistics 2017-01-23 Ajay Jasra , Kengo Kamatani , Kody J. H. Law , Yan Zhou

A mass-preserving two-step Lagrange-Galerkin scheme of second order in time for convection-diffusion problems is presented, and convergence with optimal error estimates is proved in the framework of $L^2$-theory. The introduced scheme…

Numerical Analysis · Mathematics 2022-02-22 Kouta Futai , Niklas Kolbe , Hirofumi Notsu , Tasuku Suzuki

We develop a semi-discretization approximation for scalar conservation laws with multiple rough time dependence in inhomogeneous fluxes. The method is based on Brenier's transport-collapse algorithm and uses characteristics defined in the…

Numerical Analysis · Mathematics 2015-12-21 Benjamin Gess , Benoît Perthame , Panagiotis E. Souganidis

We propose a novel Monte-Carlo based ab-initio algorithm for directly computing the statistics for quantities of interest in an immiscible two-phase compressible flow. Our algorithm samples the underlying probability space and evolves these…

Numerical Analysis · Mathematics 2023-03-30 Marco Petrella , Remi Abgrall , Siddhartha Mishra

The mean curvature flow describes the evolution of a surface (a curve) with normal velocity proportional to the local mean curvature. It has many applications in mathematics, science and engineering. In this paper, we develop a numerical…

Numerical Analysis · Mathematics 2026-04-03 Yihe Liu , Xianmin Xu

We show convergence of the Navier-Stokes/Allen-Cahn system to a classical sharp interface model for the two-phase flow of two viscous incompressible fluids with same viscosities in a smooth bounded domain in two and three space dimensions…

Analysis of PDEs · Mathematics 2024-06-06 Helmut Abels , Julian Fischer , Maximilian Moser

The Massively Parallel Computation (MPC) model is an emerging model which distills core aspects of distributed and parallel computation. It has been developed as a tool to solve (typically graph) problems in systems where the input is…

Data Structures and Algorithms · Computer Science 2020-02-20 Artur Czumaj , Peter Davies , Merav Parter