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Using techniques developed recently in the field of compressed sensing we prove new upper bounds for general (nonlinear) sampling numbers of (quasi-)Banach smoothness spaces in $L^2$. In particular, we show that in relevant cases such as…

Numerical Analysis · Mathematics 2023-08-02 Thomas Jahn , Tino Ullrich , Felix Voigtlaender

We describe a novel Godunov-type numerical method for solving the equations of resistive relativistic magnetohydrodynamics. In the proposed approach, the spatial components of both magnetic and electric fields are located at zone interfaces…

Computational Physics · Physics 2019-05-01 A. Mignone , G. Mattia , G. Bodo , L. Del Zanna

In this paper we study the class of optimal entropy-transport problems introduced by Liero, Mielke and Savar\'e in Inventiones Mathematicae 211 in 2018. This class of unbalanced transport metrics allows for transport between measures of…

Optimization and Control · Mathematics 2025-11-12 David P. Bourne , Bernhard Schmitzer , Benedikt Wirth

We discrete the ergodic semilinear stochastic partial differential equations in space dimension $d \leq 3$ with additive noise, spatially by a spectral Galerkin method and temporally by an exponential Euler scheme. It is shown that both the…

Numerical Analysis · Mathematics 2020-06-16 Ziheng Chen , Siqing Gan , Xiaojie Wang

We establish several quantitative stability estimates for optimal transport maps between non-degenerate densities on uniformly convex domains for the quadratic cost. Under H\"older regularity assumptions, we prove Lipschitz $L^2$…

Analysis of PDEs · Mathematics 2026-05-26 F. -U. Caja-Lopez , Matias G. Delgadino , Jun Kitagawa

We develop, and implement in a Finite Volume environment, a density-based approach for the Euler equations written in conservative form using density, momentum, and total energy as variables. Under simplifying assumptions, these equations…

Numerical Analysis · Mathematics 2024-05-01 Nicola Clinco , Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

A compactness framework is established for approximate solutions to subsonic-sonic flows governed by the steady full Euler equations for compressible fluids in arbitrary dimension. The existing compactness frameworks for the two-dimensional…

Analysis of PDEs · Mathematics 2015-07-28 Gui-Qiang G. Chen , Fei-Min Huang , Tian-Yi Wang

Computing intrinsic distances on discrete surfaces is at the heart of many minimization problems in geometry processing and beyond. Solving these problems is extremely challenging as it demands the computation of on-surface distances along…

Graphics · Computer Science 2024-04-30 Yue Li , Logan Numerow , Bernhard Thomaszewski , Stelian Coros

The paper considers the Euler system of PDE on a smooth compact Riemannian manifold of positive curvature without boundary, and the sphere ${\mathbb{S}}^2$ in particular. The paper interprets the Euler equations as a transport problem for…

Analysis of PDEs · Mathematics 2020-11-24 Gordon Blower

We consider uniformly rotating incompressible Euler and Navier-Stokes equations. We study the suppression of vertical gradients of Lagrangian displacement ("vertical" refers to the direction of the rotation axis). We employ a formalism that…

Analysis of PDEs · Mathematics 2007-05-23 Peter Constantin

An inviscid two-dimensional fluid model with nonlinear dispersion that arises simultaneously in coarse-grained descriptions of the dynamics of the Euler equation and in the description of non-Newtonian fluids of second grade is considered.…

Fluid Dynamics · Physics 2007-05-23 Balasubramanya T. Nadiga

In this note we show the following result using the integral-geometric formula of R. Howard: Consider the totally geodesic $\mathbb{R}P^{2m}$ in $\mathbb{C}P^n$. Then it minimizes volume among the isotropic submanifolds in the same…

Differential Geometry · Mathematics 2007-05-23 Edward Goldstein

When expressed in Lagrangian variables, the equations of motion for compressible (barotropic) fluids have the structure of a classical Hamiltonian system in which the potential energy is given by the internal energy of the fluid. The…

Analysis of PDEs · Mathematics 2021-12-21 Thomas Gallouët , Quentin Merigot , Andrea Natale

We study geodesically convex (g-convex) problems that can be written as a difference of Euclidean convex functions. This structure arises in several optimization problems in statistics and machine learning, e.g., for matrix scaling,…

Optimization and Control · Mathematics 2022-10-24 Melanie Weber , Suvrit Sra

This paper proposes semi-discrete and fully discrete hybridizable discontinuous Galerkin (HDG) methods for the Burgers' equation in two and three dimensions. In the spatial discretization, we use piecewise polynomials of degrees $ k \ (k…

Numerical Analysis · Mathematics 2021-02-02 Zimo Zhu , Gang Chen , Xiaoping Xie

A compactness framework is formulated for the incompressible limit of approximate solutions with weak uniform bounds with respect to the adiabatic exponent for the steady Euler equations for compressible fluids in any dimension. One of our…

Analysis of PDEs · Mathematics 2016-06-22 Gui-Qiang G. Chen , Feimin Huang , Tian-Yi Wang , Wei Xiang

Spatially-periodic channels are increasingly attracting attention as an efficient alternative to packed columns for a number of analytical and engineering processes. In incompressible flows, the periodic geometry allows to compute the flow…

In three space dimensions, we consider the compressible inviscid model describing the time evolution of two fluids sharing the same velocity and enjoying the algebraic pressure closure. By employing the technique of convex integration, we…

Analysis of PDEs · Mathematics 2019-12-24 Yang Li , Ewelina Zatorska

In the semi-discrete version of Monge's problem one tries to find a transport map $T$ with minimum cost from an absolutely continuous measure $\mu$ on $\mathbb{R}^d$ to a discrete measure $\nu$ that is supported on a finite set in…

Numerical Analysis · Mathematics 2017-06-23 Valentin Hartmann

Estimating optimal transport maps between two distributions from respective samples is an important element for many machine learning methods. To do so, rather than extending discrete transport maps, it has been shown that estimating the…

Statistics Theory · Mathematics 2025-02-04 Clément Lalanne , Franck Iutzeler , Jean-Michel Loubes , Julien Chhor