English
Related papers

Related papers: Shock Regularization with Smoothness-Increasing Ac…

200 papers

We propose a new entropy-compatible neural network method for scalar hyperbolic conservation laws and establish, to our knowledge, the first explicit \(L^1\) convergence rates in this setting that apply to piecewise smooth entropy…

Numerical Analysis · Mathematics 2026-05-20 Jiachuan Cao , Buyang Li , Hao Li

The Lax equivalence theorem guarantees convergence of stable and consistent discretizations for linear hyperbolic partial differential equations (PDEs). For nonlinear problems, however, stability and consistency alone do not generally…

Numerical Analysis · Mathematics 2026-03-20 Zelalem Arega Worku , David C. Del Rey Fernández , David W. Zingg

The characteristic feature of inverse problems is their instability with respect to data perturbations. In order to stabilize the inversion process, regularization methods have to be developed and applied. In this work we introduce and…

Numerical Analysis · Mathematics 2022-08-22 Andrea Ebner , Jürgen Frikel , Dirk Lorenz , Johannes Schwab , Markus Haltmeier

Learning convolution kernels in operators from data arises in numerous applications and represents an ill-posed inverse problem of broad interest. With scant prior information, kernel methods offer a natural nonparametric approach with…

Numerical Analysis · Mathematics 2025-07-17 Haibo Li , Fei Lu

A novel framework for resolving discontinuous solutions of conservation laws, e.g., contact lines, shock waves, and interfaces, using implicit tracking and a high-order discontinuous Galerkin (DG) discretization was introduced in [38].…

Numerical Analysis · Mathematics 2020-04-22 Matthew J. Zahr , Andrew Shi , Per-Olof Persson

I present a review of Smoothed Particle Hydrodynamics (SPH), with the aim of providing a mathematically rigorous, clear derivation of the algorithms from first principles. The method of discretising a continuous field into particles using a…

Instrumentation and Methods for Astrophysics · Physics 2010-10-05 Peter J. Cossins

The Planck length is the minimum length which physical law do not fail. The Dirac delta function was created to deal with continuous range issue, and it is zero except for one point. Thus contradict the Planck length. Renormalization method…

General Physics · Physics 2020-01-03 Hua Zhang , Mingshun Yuan

In this work we propose a simple but effective high order polynomial correction allowing to enhance the consistency of all kind of boundary conditions for the Euler equations (Dirichlet, characteristic far-field and slip-wall), both in 2D…

Numerical Analysis · Mathematics 2022-09-30 Mirco Ciallella , Elena Gaburro , Marco Lorini , Mario Ricchiuto

We consider two-dimensional (2D) Dirac quantum ring systems formed by the infinite mass constraint. When an Aharonov-Bohm magnetic flux is present, e.g., through the center of the ring domain, persistent currents, i.e., permanent currents…

Mesoscale and Nanoscale Physics · Physics 2017-10-25 Lei Ying , Ying-Cheng Lai

Over the past few decades there has been a strong effort towards the development of Smoothness-Increasing Accuracy-Conserving (SIAC) filters for Discontinuous Galerkin (DG) methods, designed to increase the smoothness and improve the…

Numerical Analysis · Mathematics 2016-10-10 Julia Docampo Sánchez , Jennifer K. Ryan , Mahsa Mirzargar , Robert M. Kirby

We present a new, first-order, flux-conservative formulation of relativistic viscous hydrodynamics in the BDNK framework, applicable to conformal and nonconformal fluids at zero chemical potential. Focusing on the conformal case in 1+1…

General Relativity and Quantum Cosmology · Physics 2025-10-21 Nicolas Clarisse , Eduardo O. Pinho , Teerthal Patel , Fabio S. Bemfica , Mauricio Hippert , Jorge Noronha

Deep neural networks (NN) have achieved great success in many applications. However, why do deep neural networks obtain good generalization at an over-parameterization regime is still unclear. To better understand deep NN, we establish the…

Machine Learning · Statistics 2021-12-02 Yueming Lyu , Ivor Tsang

In this paper we present a novel arbitrary-order discrete de Rham (DDR) complex on general polyhedral meshes based on the decomposition of polynomial spaces into ranges of vector calculus operators and complements linked to the spaces in…

Numerical Analysis · Mathematics 2021-11-04 Daniele Antonio Di Pietro , Jérôme Droniou

We introduce a general framework for enforcing local or global maximum principles in high-order space-time discretizations of a scalar hyperbolic conservation law. We begin with sufficient conditions for a space discretization to be bound…

Numerical Analysis · Mathematics 2021-06-14 Dmitri Kuzmin , Manuel Quezada de Luna , David I. Ketcheson , Johanna Grüll

A normalized batch gradient descent optimizer is proposed to improve the first-order regular perturbation coefficients of the Manakov equation, often referred to as kernels. The optimization is based on the linear parameterization offered…

Signal Processing · Electrical Eng. & Systems 2023-01-16 Astrid Barreiro , Gabriele Liga , Alex Alvarado

We study two notions of concentration for homogeneous polynomials of degree $N$ in $d+1$ complex variables on the unit sphere: a local notion measuring the fraction of the $L^2$-norm supported on a measurable subset; and a global notion…

Classical Analysis and ODEs · Mathematics 2026-03-17 María Ángeles García-Ferrero , Joaquim Ortega-Cerdà

When simulating hyperbolic conservation laws with discontinuous solutions, high-order linear numerical schemes often produce undesirable spurious oscillations. In this paper, we propose a jump filter within the discontinuous Galerkin (DG)…

Numerical Analysis · Mathematics 2026-01-30 Lei Wei , Lingling Zhou , Yinhua Xia

We study a second order hyperbolic initial-boundary value partial differential equation with memory, that results in an integro-differential equation with a convolution kernel. The kernel is assumed to be either smooth or no worse than…

Numerical Analysis · Mathematics 2014-01-29 Fardin Saedpanah

We consider the global minimization of a polynomial on a compact set B. We show that each step of the Moment-SOS hierarchy has a nice and simple interpretation that complements the usual one. Namely, it computes coefficients of a polynomial…

Optimization and Control · Mathematics 2020-11-18 Jean-Bernard Lasserre

In simulation sciences, it is desirable to capture the real-world problem features as accurately as possible. Methods popular for scientific simulations such as the finite element method (FEM) and finite volume method (FVM) use piecewise…

Numerical Analysis · Mathematics 2023-07-18 Vidhi Zala , Akil Narayan , Robert M Kirby
‹ Prev 1 8 9 10 Next ›