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In this work, we study long-time numerical integration of Hamiltonian systems subject to linear perturbations. By introducing an energy-induced metric, we establish a straightforward, coordinate-free criterion for dissipativity that ensures…

Numerical Analysis · Mathematics 2026-03-03 Lu Li , Xiaoli Li , Zaijiu Shang , Quanquan Xu

In this work, we design and analyze semi/fully-discrete virtual element approximations for the time-dependent Navier--Stokes-Cahn--Hilliard equations, modeling the dynamics of two-phase incompressible fluid flows with diffuse interfaces. A…

Numerical Analysis · Mathematics 2026-01-27 Alberth Silgado , Giuseppe Vacca

We present error estimates for four unconditionally energy stable numerical schemes developed for solving Allen-Cahn equations with nonlocal constraints. The schemes are linear and second order in time and space, designed based on the…

Numerical Analysis · Mathematics 2018-10-23 Shouwen Sun , Xiaobo Jing , Qi Wang

We propose two efficient energetic spectral-element methods in time for marching nonlinear gradient systems with the phase-field Allen--Cahn equation as an example: one fully implicit nonlinear method and one semi-implicit linear method.…

Numerical Analysis · Mathematics 2026-05-06 Shiqin Liu , Haijun Yu

We construct and analyze first- and second-order implicit-explicit (IMEX) schemes based on the scalar auxiliary variable (SAV) approach for the magneto-hydrodynamic equations. These schemes are linear, only require solving a sequence of…

Numerical Analysis · Mathematics 2021-04-02 Xiaoli Li , Weilong Wang , Jie Shen

"Generalized Hydrodynamics" (GHD) stands for a model that describes one-dimensional \textit{integrable} systems in quantum physics, such as ultra-cold atoms or spin chains. Mathematically, GHD corresponds to nonlinear equations of kinetic…

Computational Physics · Physics 2023-11-21 Frederik Møller , Nicolas Besse , Igor E. Mazets , Hans-Peter Stimming , Norbert J. Mauser

Using the framework of the quantum separation of variables (SoV) for higher rank quantum integrable lattice models [1], we introduce some foundations to go beyond the obtained complete transfer matrix spectrum description, and open the way…

Mathematical Physics · Physics 2020-12-16 J. M. Maillet , G. Niccoli , L. Vignoli

We present compact semi-implicit finite difference schemes on structured grids for numerical solutions of the advection by an external velocity and by a speed in normal direction that are applicable in level set methods. The most involved…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Nikola Gajdošová

We study linear abstract differential-algebraic equations (ADAEs), and we introduce an index concept which is based on polynomial growth of a~pseudo-resolvent. Our approach to solvability analysis is based on degenerate semigroups. We apply…

Functional Analysis · Mathematics 2023-12-06 Hannes Gernandt , Timo Reis

We introduce a new variational inference (VI) framework, called energetic variational inference (EVI). It minimizes the VI objective function based on a prescribed energy-dissipation law. Using the EVI framework, we can derive many existing…

Machine Learning · Statistics 2026-05-12 Yiwei Wang , Jiuhai Chen , Chun Liu , Lulu Kang

We propose a novel framework for discovering Stochastic Partial Differential Equations (SPDEs) from data. The proposed approach combines the concepts of stochastic calculus, variational Bayes theory, and sparse learning. We propose the…

Machine Learning · Statistics 2023-06-29 Yogesh Chandrakant Mathpati , Tapas Tripura , Rajdip Nayek , Souvik Chakraborty

In this paper, we construct efficient schemes based on the scalar auxiliary variable (SAV) block-centered finite difference method for the modified phase field crystal (MPFC) equation, which is a sixth-order nonlinear damped wave equation.…

Numerical Analysis · Mathematics 2020-04-10 Xiaoli Li , Jie Shen

We present a novel partitioned iterative formulation for modeling of fluid-structure interaction in two-phase flows. The variational formulation consists of a stable and robust integration of three blocks of differential equations, viz.,…

Fluid Dynamics · Physics 2020-05-06 Vaibhav Joshi , Rajeev K. Jaiman

In this paper, we develop an energy dissipative numerical scheme for gradient flows of planar curves, such as the curvature flow and the elastic flow. Our study presents a general framework for solving such equations. To discretize time, we…

Numerical Analysis · Mathematics 2016-10-11 Tomoya Kemmochi

This paper contributes to the exploration of a recently introduced computational paradigm known as second-order flows, which are characterized by novel dissipative hyperbolic partial differential equations extending accelerated gradient…

Numerical Analysis · Mathematics 2025-05-13 Haifan Chen , Guozhi Dong , José A. Iglesias , Wei Liu , Ziqing Xie

This paper focuses on the numerical approximation of the linearized shallow water equations using hybridizable discontinuous Galerkin (HDG) methods, leveraging the Hamiltonian structure of the evolution system. First, we propose an…

Numerical Analysis · Mathematics 2025-07-04 C. Núñez , M. A. Sánchez

In this paper we combine a flexible covariant formulation of the shallow water equations with the semi-implicit numerical scheme developed over the years by Casulli and collaborators. After adopting an orthogonal, but non-orthonormal,…

Fluid Dynamics · Physics 2026-05-26 Maurizio Tavelli , Olindo Zanotti

We are concerned with the Cauchy problem for the KdV equation for nonsmooth locally integrable initial profiles q's which are, in a certain sense, essentially bounded from below and q(x)=O(e^{-cx^{{\epsilon}}}),x\rightarrow+\infty, with…

Exactly Solvable and Integrable Systems · Physics 2011-09-29 Alexei Rybkin

This paper proposes a novel first-order and a novel second-order fully discrete virtual element schemes based on the scalar auxiliary variable method for the three dimensional inductionless magnetohydrodynamics problem. The backward Eular…

Analysis of PDEs · Mathematics 2024-12-13 Xianghai Zhou , Haiyan Su

In this work, we propose a new particle-based variational inference (ParVI) method for accelerating the Energetic Variational Inference with Implicit scheme (EVI-Im) introduced in Ref. \cite{wang2021particle}. Inspired by energy…

Machine Learning · Statistics 2026-05-14 Xuelian Bao , Lulu Kang , Chun Liu , Yiwei Wang