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Discrete optimal transport solvers do not scale well on dense large problems since they do not explicitly exploit the geometric structure of the cost function. In analogy to continuous optimal transport we provide a framework to verify…

Optimization and Control · Mathematics 2016-04-19 Bernhard Schmitzer

We propose an Exponential DG approach for numerically solving partial differential equations (PDEs). The idea is to decompose the governing PDE operators into linear (fast dynamics extracted by linearization) and nonlinear (the remaining…

Numerical Analysis · Mathematics 2021-08-11 Shinhoo Kang , Tan Bui-Thanh

We develop a hybrid spatial discretization for the wave equation in second order form, based on high-order accurate finite difference methods and discontinuous Galerkin methods. The hybridization combines computational efficiency of finite…

Numerical Analysis · Mathematics 2022-10-26 Siyang Wang , Gunilla Kreiss

Adjoint-based shape optimization most often relies on Eulerian flow field formulations. However, since Lagrangian particle methods are the natural choice for solving sedimentation problems in oceanography, extensions to the Lagrangian…

Fluid Dynamics · Physics 2022-09-07 Luka Schlegel , Volker Schulz

We develop a third-order conservative semi-Lagrangian discontinuous Galerkin (SLDG) scheme for solving linear transport equations on curvilinear unstructured triangular meshes, tailored for complex geometries. To ensure third-order spatial…

Numerical Analysis · Mathematics 2025-11-14 Xiaofeng Cai , Yibing Chen , Kunkai Fu , Liujun Pan

Moist thermodynamics is a fundamental driver of atmospheric dynamics across all scales, making accurate modeling of these processes essential for reliable weather forecasts and climate change projections. However, atmospheric models often…

Atmospheric and Oceanic Physics · Physics 2024-11-18 Kieran Ricardo , David Lee , Kenneth Duru

We present an efficient solver for diffeomorphic image registration problems in the framework of Large Deformations Diffeomorphic Metric Mappings (LDDMM). We use an optimal control formulation, in which the velocity field of a hyperbolic…

Computer Vision and Pattern Recognition · Computer Science 2017-11-02 Andreas Mang , Lars Ruthotto

In this paper, we consider the numerical approximation of a general second order semilinear stochastic partial differential equation (SPDE) driven by multiplicative and additive noise. Our main interest is on such SPDEs where the nonlinear…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety of applications in machine learning and engineering, ranging from constrained deep neural networks, to…

Optimization and Control · Mathematics 2023-05-31 Ilgee Hong , Sen Na , Michael W. Mahoney , Mladen Kolar

In this work, we study and extend a class of semi-Lagrangian exponential methods, which combine exponential time integration techniques, suitable for integrating stiff linear terms, with a semi-Lagrangian treatment of nonlinear advection…

Numerical Analysis · Mathematics 2025-04-25 João Guilherme Caldas Steinstraesser , Martin Schreiber , Pedro da Silva Peixoto

A deterministic method is proposed for solving the Boltzmann equation. The method employs a Galerkin discretization of the velocity space and adopts, as trial and test functions, the collocation basis functions based on weights and roots of…

Computational Physics · Physics 2013-11-19 Gian Pietro Ghiroldi , Livio Gibelli

This paper proposes and analyzes a gradient-type algorithm based on Burer-Monteiro factorization, called the Asymmetric Projected Gradient Descent (APGD), for reconstructing the point set configuration from partial Euclidean distance…

Machine Learning · Computer Science 2025-10-20 Yicheng Li , Xinghua Sun

It is shown that the computational efficiency of the discrete least-squares (DLS) approximation of solutions of stochastic elliptic PDEs is improved by incorporating a reduced-basis method into the DLS framework. The goal is to recover the…

Numerical Analysis · Mathematics 2017-11-09 Max Gunzburger , Michael Schneier , Clayton Webster , Guannan Zhang

We develop error estimates for the semi-discrete conservative spectral method for the approximation of the elastic and inelastic space homogeneous Boltzmann equation introduced by the authors in \cite{GT09}. In addition we study the long…

Numerical Analysis · Mathematics 2019-06-21 Ricardo J. Alonso , Irene M. Gamba , Sri Harsha Tharkabhushanam

Novel fully discrete schemes are developed to numerically approximate a semilinear stochastic wave equation driven by additive space-time white noise. Spectral Galerkin method is proposed for the spatial discretization, and exponential time…

Numerical Analysis · Mathematics 2020-08-10 Xiaojie Wang , Siqing Gan , Jingtian Tang

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 describe a mesh-free three-dimensional numerical scheme for solving the incompressible semi-geostrophic equations based on semi-discrete optimal transport techniques. These results generalise previous two-dimensional implementations. The…

Numerical Analysis · Mathematics 2026-02-12 Théo Lavier

We present a stability and error analysis of an embedded-hybridized discontinuous Galerkin (EDG-HDG) finite element method for coupled Stokes--Darcy flow and transport. The flow problem, governed by the Stokes--Darcy equations, is…

Numerical Analysis · Mathematics 2023-07-07 Aycil Cesmelioglu , Sander Rhebergen

This article presents a novel and practically useful link between geometric integration, low-discrepancy sampling and code coupling for Lagrangian and Eulerian Vlasov-Poisson solvers. Low-discrepancy sequences, also called quasi-random…

Numerical Analysis · Mathematics 2020-06-26 Jakob Ameres