An Asymptotic Preserving Discontinuous Galerkin Method for a Linear Boltzmann Semiconductor Model

IF 2.8 2区 数学 Q1 MATHEMATICS, APPLIED
Victor P. DeCaria, Cory D. Hauck, Stefan R. Schnake
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引用次数: 0

Abstract

SIAM Journal on Numerical Analysis, Volume 62, Issue 3, Page 1067-1097, June 2024.
Abstract. A key property of the linear Boltzmann semiconductor model is that as the collision frequency tends to infinity, the phase space density [math] converges to an isotropic function [math], called the drift-diffusion limit, where [math] is a Maxwellian and the physical density [math] satisfies a second-order parabolic PDE known as the drift-diffusion equation. Numerical approximations that mirror this property are said to be asymptotic preserving. In this paper we build a discontinuous Galerkin method to the semiconductor model, and we show this scheme is both uniformly stable in [math], where 1/[math] is the scale of the collision frequency, and asymptotic preserving. In particular, we discuss what properties the discrete Maxwellian must satisfy in order for the schemes to converge in [math] to an accurate [math]-approximation of the drift-diffusion limit. Discrete versions of the drift-diffusion equation and error estimates in several norms with respect to [math] and the spacial resolution are also included.
线性玻尔兹曼半导体模型的渐近保留非连续伽勒金方法
SIAM 数值分析期刊》第 62 卷第 3 期第 1067-1097 页,2024 年 6 月。 摘要。线性玻尔兹曼半导体模型的一个关键特性是,当碰撞频率趋于无穷大时,相空间密度[math]收敛于一个各向同性的函数[math],称为漂移扩散极限,其中[math]是一个麦克斯韦函数,物理密度[math]满足一个二阶抛物线 PDE,称为漂移扩散方程。反映这一特性的数值近似被称为渐近保全。在本文中,我们针对半导体模型建立了一种非连续伽勒金方法,并证明该方法在[math](其中 1/[math] 是碰撞频率的尺度)内是均匀稳定的,而且具有渐近保留性。我们特别讨论了离散麦克斯韦必须满足哪些性质,才能使方案在[math]中收敛到漂移扩散极限的精确[math]近似值。此外,我们还讨论了漂移扩散方程的离散版本以及与[math]和空间分辨率相关的几种规范的误差估计。
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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