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We review a scalable two- and three-dimensional computer code for low-temperature plasma simulations in multi-material complex geometries. Our approach is based on embedded boundary (EB) finite volume discretizations of the minimal…

Computational Physics · Physics 2019-05-01 Robert Marskar

We consider a linear-quadratic optimization problem with pointwise bounds on the state for which the constraint is given by the Laplace-Beltrami equation (to have uniqueness we add an lower order term) on a two-dimensional surface . By…

Optimization and Control · Mathematics 2016-06-10 Ahmad Ahmad Ali , Michael Hinze , Heiko Kröner

We study the use of polyhedral discretizations for the solution of heat diffusion and elastodynamic problems in computer graphics. Polyhedral meshes are more natural for certain applications than pure triangular or quadrilateral meshes,…

Graphics · Computer Science 2024-12-10 Junyu Liu , Daniele Panozzo , Mario Botsch , Teseo Schneider

Stochastic sampling methods are arguably the most direct and least intrusive means of incorporating parametric uncertainty into numerical simulations of partial differential equations with random inputs. However, to achieve an overall error…

Numerical Analysis · Mathematics 2014-04-09 Hans-Werner van Wyk

A framework for exponential time discretization of the multilayer rotating shallow water equations is developed in combination with a mimetic discretization in space. The method is based on a combination of existing exponential time…

Numerical Analysis · Mathematics 2019-08-27 Konstantin Pieper , K. Chad Sockwell , Max Gunzburger

This paper proposes a novel approach to solving nonlinear programming problems using a sharp augmented Lagrangian method with a smoothing technique. Traditional sharp augmented Lagrangian methods are known for their effectiveness but are…

Optimization and Control · Mathematics 2024-10-07 José Luis Romero , Damián Fernandez , Germán Ariel Torres

Large linear systems of saddle-point type have arisen in a wide variety of applications throughout computational science and engineering. The discretizations of distributed control problems have a saddle-point structure. The numerical…

Numerical Analysis · Mathematics 2021-12-01 Yunhui He

The multigrid-reduction-in-time (MGRIT) technique has proven to be successful in achieving higher run-time speedup by exploiting parallelism in time. The goal of this article is to develop and analyze a MGRIT algorithm, using FCF-relaxation…

Numerical Analysis · Mathematics 2021-02-10 Xiaoqiang Yue , Kejia Pan , Jie Zhou , Zhifeng Weng , Shi Shu , Juan Tang

We present a continuous finite element method for some examples of fully nonlinear elliptic equation. A key tool is the discretisation proposed in Lakkis & Pryer (2011, SISC) allowing us to work directly on the strong form of a linear PDE.…

Numerical Analysis · Mathematics 2015-03-19 Omar Lakkis , Tristan Pryer

Smoothed particle hydrodynamics (SPH) has been extensively used to model high and low Reynolds number flows, free surface flows and collapse of dams, study pore-scale flow and dispersion, elasticity, and thermal problems. In different…

Numerical Analysis · Mathematics 2017-12-01 Alexander A. Lukyanov , Kees Vuik

We introduce a lattice random walk discretisation scheme for stochastic differential equations (SDEs) that samples binary or ternary increments at each step, suppressing complex drift and diffusion computations to simple 1 or 2 bit random…

Numerical Analysis · Mathematics 2026-02-18 Samuel Duffield , Maxwell Aifer , Denis Melanson , Zach Belateche , Patrick J. Coles

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

This paper uses the technology of weighted and regular triangulations to study discrete versions of the Laplacian on piecewise Euclidean manifolds. Regular triangulations are studied in some detail, including flip algorithms. The Laplacian…

Metric Geometry · Mathematics 2007-05-23 David Glickenstein

In this paper, we propose an accurate finite difference method to discretize the $d$-dimensional (for $d\ge 1$) tempered integral fractional Laplacian and apply it to study the tempered effects on the solution of problems arising in various…

Numerical Analysis · Mathematics 2019-10-30 Siwei Duo , Yanzhi Zhang

Brain-computer interfaces (BCIs) offer transformative potential, but decoding neural signals presents significant challenges. The core premise of this paper is built around demonstrating methods to elucidate the underlying low-dimensional…

Machine Learning · Computer Science 2025-02-28 Benjamin J. Choi

The effects of several nonlinear regularization techniques are discussed in the framework of 3D seismic tomography. Traditional, linear, $\ell_2$ penalties are compared to so-called sparsity promoting $\ell_1$ and $\ell_0$ penalties, and a…

Geophysics · Physics 2010-08-19 I. Loris , H. Douma , G. Nolet , I. Daubechies , C. Regone

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

We introduce a new Partition of Unity Method for the numerical homogenization of elliptic partial differential equations with arbitrarily rough coefficients. We do not restrict to a particular ansatz space or the existence of a finite…

Numerical Analysis · Mathematics 2016-05-04 Daniel Peterseim , Patrick Henning , Philipp Morgenstern

This article provides a brief review of recent developments on two nonlocal operators: fractional Laplacian and fractional time derivative. We start by accounting for several applications of these operators in imaging science, geophysics,…

Optimization and Control · Mathematics 2021-06-28 Harbir Antil , Thomas S. Brown , Ratna Khatri , Akwum Onwunta , Deepanshu Verma , Mahamadi Warma

Ordinary differential equations (ODEs) are commonly used to model dynamic behavior of a system. Because many parameters are unknown and have to be estimated from the observed data, there is growing interest in statistics to develop…

Statistics Theory · Mathematics 2010-01-13 Xin Qi , Hongyu Zhao
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