English
Related papers

Related papers: Maximum likelihood discretization of the transport…

200 papers

In this work, we construct novel discretizations for the unsteady convection-diffusion equation. Our discretization relies on multiderivative time integrators together with a novel discretization that reduces the total number of unknowns…

Numerical Analysis · Mathematics 2017-02-10 Jochen Schütz , David C. Seal , Alexander Jaust

We consider flux-corrected finite element discretizations of 3D convection-dominated transport problems and assess the computational efficiency of algorithms based on such approximations. The methods under investigation include…

Numerical Analysis · Mathematics 2024-01-15 Abhinav Jha , Ondřej Pártl , Naveed Ahmed , Dmitri Kuzmin

Empirical divergence maximization (EDM) refers to a recently proposed strategy for estimating f-divergences and likelihood ratio functions. This paper extends the idea to empirical vector quantization where one seeks to empirically derive…

Information Theory · Computer Science 2015-06-03 Michael A. Lexa

This work introduces a single-stage, single-step method for the compressible Euler equations that is provably positivity-preserving and can be applied on both Cartesian and unstructured meshes. This method is the first case of a…

Numerical Analysis · Mathematics 2016-02-01 Scott A. Moe , James A. Rossmanith , David C. Seal

In this paper, we propose an efficient, high order accurate and asymptotic-preserving (AP) semi-Lagrangian (SL) method for the BGK model with constant or spatially dependent Knudsen number. The spatial discretization is performed by a mass…

Numerical Analysis · Mathematics 2021-05-07 Mingchang Ding , Jing-Mei Qiu , Ruiwen Shu

A numerical method based on the hybridizable discontinuous Galerkin method in space and backward Euler in time is formulated and analyzed for solving the miscible displacement problem. Under low regularity assumptions, convergence is…

Numerical Analysis · Mathematics 2025-05-19 Keegan L. A. Kirk , Beatrice Riviere

We present a numerical method for simulating rarefied gases that interact with moving boundaries and rigid bodies. The gas is described by the BGK equation in Lagrangian form and solved using an Arbitrary Lagrangian-Eulerian method, in…

Numerical Analysis · Mathematics 2026-04-28 Klaas Willems , Axel Klar , Giovanni Russo , Giovanni Samaey , Sudarshan Tiwari

We propose a generalized Eulerian-Lagrangian (GEL) discontinuous Galerkin (DG) method. The method is a generalization of the Eulerian-Lagrangian (EL) DG method for transport problems proposed in [arXiv preprint arXiv: 2002.02930 (2020)],…

Numerical Analysis · Mathematics 2022-06-08 Xue Hong , Jing-Mei Qiu

Maximal regularity is a kind of a priori estimates for parabolic-type equations and it plays an important role in the theory of nonlinear differential equations. The aim of this paper is to investigate the temporally discrete counterpart of…

Numerical Analysis · Mathematics 2024-05-17 Takahito Kashiwabara , Tomoya Kemmochi

We present a robust and accurate discretization approach for incompressible turbulent flows based on high-order discontinuous Galerkin methods. The DG discretization of the incompressible Navier-Stokes equations uses the local…

Fluid Dynamics · Physics 2018-08-01 Niklas Fehn , Wolfgang A Wall , Martin Kronbichler

Particle-based methods include a variety of techniques, such as Markov Chain Monte Carlo (MCMC) and Sequential Monte Carlo (SMC), for approximating a probabilistic target distribution with a set of weighted particles. In this paper, we…

Machine Learning · Statistics 2024-12-03 Hadi Mohasel Afshar , Gilad Francis , Sally Cripps

Stochastic Galerkin methods offer unexplored potential for the numerical simulation of parabolic problems with random variables, in particular if they are combined with variational discretizations of the space and time variables. Due to the…

Numerical Analysis · Mathematics 2026-05-21 Moataz Dawor , Nils Margenberg , Markus Bause

Given a statistical model, the maximum likelihood degree is the number of complex solutions to the likelihood equations for generic data. We consider discrete algebraic statistical models and study the solutions to the likelihood equations…

Algebraic Geometry · Mathematics 2014-05-06 Elizabeth Gross , Jose Israel Rodriguez

This paper explores energy-, momentum-, density-, and positivity-preserving spatio-temporal discretizations for the nonlinear Landau collision operator. We discuss two approaches, namely direct Galerkin formulations and discretizations of…

Plasma Physics · Physics 2018-04-24 Eero Hirvijoki , Joshua W. Burby , Michael Kraus

We consider the discretization and subsequent model reduction of a system of partial differential-algebraic equations describing the propagation of pressure waves in a pipeline network. Important properties like conservation of mass,…

Numerical Analysis · Mathematics 2017-04-12 Herbert Egger , Thomas Kugler , Björn Liljegren-Sailer , Nicole Marheineke , Volker Mehrmann

We introduce a Lagrangian nodal discontinuous Galerkin (DG) cell-centered hydrodynamics method for solving multi-dimensional hyperbolic systems. By incorporating an adaptation of Zalesak's flux-corrected transport algorithm, we combine a…

Numerical Analysis · Mathematics 2025-10-30 Joshua Vedral , Nathaniel Morgan , Dmitri Kuzmin , Jacob Moore

We propose a modified local discontinuous Galerkin (LDG) method for second--order elliptic problems that does not require extrinsic penalization to ensure stability. Stability is instead achieved by showing a discrete Poincar\'e--Friedrichs…

Numerical Analysis · Mathematics 2017-02-17 Lorenz John , Michael Neilan , Iain Smears

We consider a semilinear parabolic equation with a large class of nonlinearities without any growth conditions. We discretize the problem with a discontinuous Galerkin scheme dG(0) in time (which is a variant of the implicit Euler scheme)…

Numerical Analysis · Mathematics 2018-08-17 Dominik Meidner , Boris Vexler

We study a nonlinear multimarginal optimal transport problem arising in risk management, where the objective is to maximize a spectral risk measure of the pushforward of a coupling by a cost function. Although this problem is inherently…

Optimization and Control · Mathematics 2026-03-27 Adrien Cances , Quentin Mérigot , Luca Nenna

We study discretizations of Hamiltonian systems on the probability density manifold equipped with the $L^2$-Wasserstein metric. Based on discrete optimal transport theory, several Hamiltonian systems on graph (lattice) with different…

Numerical Analysis · Mathematics 2020-06-17 Jianbo Cui , Luca Dieci , Haomin Zhou