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We present an energy-stable scheme for numerically approximating the governing equations for incompressible two-phase flows with different densities and dynamic viscosities for the two fluids. The proposed scheme employs a scalar-valued…

Computational Physics · Physics 2019-06-26 Z. Yang , S. Dong

An explicit numerical method is developed for a class of non-autonomous time-changed stochastic differential equations, whose coefficients obey H\"older's continuity in terms of the time variables and are allowed to grow super-linearly in…

Numerical Analysis · Mathematics 2022-05-03 Xiaotong Li , Wei Liu , Tianjiao Tang

We consider the long-time behavior of an explicit tamed Euler scheme applied to a class of stochastic differential equations driven by additive noise, under a one-sided Lipschitz continuity condition. The setting encompasses drift…

Numerical Analysis · Mathematics 2020-10-02 Charles-Edouard Bréhier

The space fractional Cahn-Hilliard phase-field model is more adequate and accurate in the description of the formation and phase change mechanism than the classical Cahn-Hilliard model. In this article, we propose a temporal second-order…

Numerical Analysis · Mathematics 2021-05-13 Yong-Liang Zhao , Meng Li , Alexander Ostermann , Xian-Ming Gu

This work studies a stabilization technique for first-order hyperbolic differential equations used in DNA transcription modeling. Specifically we use the Lighthill-Whitham-Richards Model with a nonlinear Greenshield's velocity proposed in…

Numerical Analysis · Mathematics 2025-07-15 Ali Balooch , Faranak Courtney-Pahlevani , Lisa Davis , Adrian Dunca , Monika Neda , Jorge Reyes

We study the steady states and dynamics of a thin film-type equation with non-conserved mass in one dimension. The evolution equation is a nonlinear fourth-order degenerate parabolic PDE motivated by a model of volatile viscous fluid films…

Analysis of PDEs · Mathematics 2019-10-29 Hangjie Ji , Thomas P. Witelski

In this work, we investigate the two-step backward differentiation formula (BDF2) with nonuniform grids for the Allen-Cahn equation. We show that the nonuniform BDF2 scheme is energy stable under the time-step ratio restriction…

Numerical Analysis · Mathematics 2022-01-05 Hong-lin Liao , Tao Tang , Tao Zhou

We propose a physics-informed consistency modeling framework for solving partial differential equations (PDEs) via fast, few-step generative inference. We identify a key stability challenge in physics-constrained consistency training, where…

Machine Learning · Computer Science 2026-02-11 Che-Chia Chang , Chen-Yang Dai , Te-Sheng Lin , Ming-Chih Lai , Chieh-Hsin Lai

We present a nonlinear dynamical approximation method for time-dependent Partial Differential Equations (PDEs). The approach makes use of parametrized decoder functions, and provides a general, and principled way of understanding and…

Numerical Analysis · Mathematics 2025-05-20 Daan Bon , Benjamin Caris , Olga Mula

We propose and analyse new stabilized time marching schemes for Phase Fields model such as Allen-Cahn and Cahn-Hillard equations, when discretized in space with high order finite differences compact schemes. The stabilization applies to…

Numerical Analysis · Mathematics 2019-10-01 Matthieu Brachet , Jean-Paul Chehab

We propose an energy-stable parametric finite element method (ES-PFEM) for simulating solid-state dewetting of thin films in two dimensions via a sharp-interface model, which is governed by surface diffusion and contact line (point)…

Numerical Analysis · Mathematics 2020-06-08 Quan Zhao , Wei Jiang , Weizhu Bao

In this paper, we investigate a large-scale stochastic system with bilinear drift and linear diffusion term. Such high dimensional systems appear for example when discretizing a stochastic partial differential equations in space. We study a…

Optimization and Control · Mathematics 2018-04-06 Martin Redmann

We study the strong approximation of the solutions to singular stochastic kinetic equations (also referred to as second-order SDEs) driven by $\alpha$-stable processes, using an Euler-type scheme inspired by [11]. For these equations, the…

Probability · Mathematics 2025-11-18 Chengcheng Ling

This paper investigates the strong convergence properties of two Euler-type methods for a class of time-changed stochastic differential equations (TCSDEs) with super-linearly growing drift and diffusion coefficients. Building upon existing…

Numerical Analysis · Mathematics 2026-01-16 Shuai Wang , Yuanling Niu , Ying Zhang

Two ocean models are considered for geophysical flow simulations: the multi-layer shallow water equations and the multi-layer primitive equations. For the former, we investigate the parallel performance of exponential time differencing…

Atmospheric and Oceanic Physics · Physics 2021-10-04 Rihui Lan , Wei Leng , Zhu Wang , Lili Ju , Max Gunzburger

Explicit step-truncation tensor methods have recently proven successful in integrating initial value problems for high-dimensional partial differential equations (PDEs). However, the combination of non-linearity and stiffness may introduce…

Numerical Analysis · Mathematics 2023-03-21 Abram Rodgers , Daniele Venturi

We consider the distributed optimization problem where $n$ agents each possessing a local cost function, collaboratively minimize the average of the $n$ cost functions over a connected network. Assuming stochastic gradient information is…

Optimization and Control · Mathematics 2021-05-12 Kun Huang , Shi Pu

First-order energy dissipative schemes in time are available in literature for the Poisson-Nernst-Planck (PNP) equations, but second-order ones are still in lack. This work proposes novel second-order discretization in time and finite…

Numerical Analysis · Mathematics 2023-09-08 Jie Ding , Shenggao Zhou

It is well-known that wave-type equations with memory, under appropriate assumptions on the memory kernel, are uniformly exponentially stable. On the other hand, time delay effects may destroy this behavior. Here, we consider the…

Analysis of PDEs · Mathematics 2015-07-14 Cristina Pignotti

We develop the theory of Energy Conserving Descent (ECD) and introduce ECDSep, a gradient-based optimization algorithm able to tackle convex and non-convex optimization problems. The method is based on the novel ECD framework of…

Machine Learning · Computer Science 2023-06-02 G. Bruno De Luca , Alice Gatti , Eva Silverstein
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