Multilevel Monte Carlo FDTD Method for Uncertainty Quantification

被引：0

作者：

Zhu, Xiaojie ^{[1
,2
]}

Di Rienzo, Luca ^{[2
]}

Ma, Xikui ^{[1
]}

Codecasa, Lorenzo ^{[2
]}

机构：

[1] Xi An Jiao Tong Univ, State Key Lab Elect Insulat & Power Equipment, Sch Elect Engn, Xian 710049, Peoples R China

[2] Politecn Milan, Dipartimento Elettron Informaz & Bioingn, I-20133 Milan, Italy

来源：

IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS | 2022年 / 21卷 / 10期

基金：

国家重点研发计划;

关键词：

Finite difference methods; Time-domain analysis; Monte Carlo methods; Standards; Uncertainty; Random variables; Electric fields; Finite-difference time-domain method; multilevel Monte Carlo method (MLMC); uncertainty quantification; STOCHASTIC FDTD; ROUGH-SURFACE; SCATTERING;

D O I：

10.1109/LAWP.2022.3189414

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The recent multilevel Monte Carlo method is here proposed for uncertainty quantification in electromagnetic problems solved by the finite-difference time-domain (FDTD) method, when material parameters are modeled as random variables. It improves the estimations of the mean and variance of the quantities of interest computed on a FDTD spatial grid by sampling at coarser levels of discretization. The proposed approach can amply reduce the computational cost of the standard Monte Carlo FDTD, at the price of a small reduction of its accuracy. It is advantageous with respect to polynomial chaos FDTD, when the latter fails or becomes prohibitive for computational requirements. It also appears to widely outperform stochastic FDTD in terms of accuracy.

引用

页码：2030 / 2034

页数：5

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