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We investigate the construction and performance of summation-by-parts (SBP) operators, which offer a powerful framework for the systematic development of structure-preserving numerical discretizations of partial differential equations.…

Numerical Analysis · Mathematics 2026-02-12 Jan Glaubitz , Armin Iske , Joshua Lampert , Philipp Öffner

We study the numerical solutions of time-dependent systems of partial differential equations, focusing on the implementation of boundary conditions. The numerical method considered is a finite difference scheme constructed by high order…

Numerical Analysis · Mathematics 2017-10-31 Sofia Eriksson

A generalised analytical notion of summation-by-parts (SBP) methods is proposed, extending the concept of SBP operators in the correction procedure via reconstruction (CPR), a framework of high-order methods for conservation laws. For the…

Numerical Analysis · Mathematics 2017-04-26 Hendrik Ranocha , Philipp Öffner , Thomas Sonar

This paper presents a method for calculating Region of Attraction of a target set (not necessarily an equilibrium) for controlled polynomial dynamical systems, using a hierarchy of semidefinite programming problems (SDPs). Our approach…

Optimization and Control · Mathematics 2021-03-08 Vít Cibulka , Milan Korda , Tomáš Haniš

We analyze the stability and functional superconvergence of discretizations of diffusion problems with the narrow-stencil second-derivative generalized summation-by-parts (SBP) operators coupled with simultaneous approximation terms (SATs).…

Numerical Analysis · Mathematics 2021-12-21 Zelalem Arega Worku , David W. Zingg

In this paper, we consider finite difference approximations of the second order wave equation. We use finite difference operators satisfying the summation-by-parts property to discretize the equation in space. Boundary conditions and grid…

Numerical Analysis · Mathematics 2015-09-04 Siyang Wang , Gunilla Kreiss

In this paper we propose a stochastic primal dual fixed point method (SPDFP) for solving the sum of two proper lower semi-continuous convex function and one of which is composite. The method is based on the primal dual fixed point method…

Optimization and Control · Mathematics 2020-04-21 YaNanZhu , XiaoqunZhang

In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest.…

Methodology · Statistics 2024-07-23 Lucia Clarotto , Denis Allard , Thomas Romary , Nicolas Desassis

This article extends the theory of classical finite-difference summation-by-parts (FD-SBP) time-marching methods to the generalized summation-by-parts (GSBP) framework. Dual-consistent GSBP time-marching methods are shown to retain: A and…

Numerical Analysis · Mathematics 2016-01-26 Pieter D. Boom , David W. Zingg

The construction of stable, conservative, and accurate volume dissipation is extended to discretizations that possess a generalized summation-by-parts (SBP) property within a tensor-product framework. The dissipation operators can be…

Numerical Analysis · Mathematics 2026-03-19 Alex Bercik , David A. Craig Penner , David W. Zingg

This chapter reviews and compares discontinuous Galerkin time-stepping methods for the numerical approximation of second-order ordinary differential equations, particularly those stemming from space finite element discretization of wave…

Numerical Analysis · Mathematics 2025-05-12 Paola F. Antonietti , Alberto Artoni , Gabriele Ciaramella , Ilario Mazzieri

A numerical method is proposed for computing time-periodic and relative time-periodic solutions in dissipative wave systems. In such solutions, the temporal period, and possibly other additional internal parameters such as the propagation…

Pattern Formation and Solitons · Physics 2014-08-28 Jianke Yang

The advection-diffusion and wave equations are the fundamental equations governing any physical law and therefore arise in many areas of physics and astrophysics. For complex problems and geometries, only numerical simulations can give…

Computational Physics · Physics 2014-01-08 J. Pétri

We present a finite-horizon optimization algorithm that extends the established concept of Dual Dynamic Programming (DDP) in two ways. First, in contrast to the linear costs, dynamics, and constraints of standard DDP, we consider problems…

Optimization and Control · Mathematics 2018-07-17 Marc Hohmann , Joseph Warrington , John Lygeros

In this work, we design and analyze a novel, provably conditionally stable, weakly coupled partitioned scheme to solve the conjugate heat transfer (CHT) problem. We consider a model CHT problem consisting of linear advection-diffusion and…

Numerical Analysis · Mathematics 2026-02-23 Sarah Nataj , David C. Del Rey Fernández , David Brown , Rajeev Jaiman

We construct a structure preserving non-conforming finite element approximation scheme for the bi-harmonic wave maps into spheres equation. It satisfies a discrete energy law and preserves the non-convex sphere constraint of the continuous…

Numerical Analysis · Mathematics 2026-04-09 Ľubomír Baňas , Sebastian Herr

The Laplacian appears in several partial differential equations used to model wave propagation. Summation-by-parts--simultaneous approximation term (SBP-SAT) finite difference methods are often used for such equations, as they combine…

Numerical Analysis · Mathematics 2020-02-11 Martin Almquist , Eric M. Dunham

The problem of sparse approximation and the closely related compressed sensing have received tremendous attention in the past decade. Primarily studied from the viewpoint of applied harmonic analysis and signal processing, there have been…

Information Theory · Computer Science 2018-10-23 Ali Çivril

The numerical approximation of some Boussinesq systems in two spatial dimensions is here considered. The differential systems under study are proposed as asymptotic models for the propagation of waves along the interface of two layers of…

Numerical Analysis · Mathematics 2026-05-05 A. Durán

In this work, we address the problem of solving a series of underdetermined linear inverse problems subject to a sparsity constraint. We generalize the spike-and-slab prior distribution to encode a priori correlation of the support of the…

Machine Learning · Statistics 2018-01-19 Michael Riis Andersen , Aki Vehtari , Ole Winther , Lars Kai Hansen