Variance reduction for Monte Carlo simulation of semiconductor devices

被引:0
|
作者
Yamada, Y [1 ]
机构
[1] Kyushu Tokai Univ, Dept Informat Sci, Kumamoto 8628652, Japan
关键词
semiconductor devices; GaAs MESFET; ensernble Monte Carlo simulation; variance reduction;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Some techniques being effective for the variance reduction of ensemble Monte Carlo simulation(EMC) are proposed on the basis of the electron physics. They consist of expression of a particle with the gaussian cloud depending on the electron density, suppression of the local fluctuation of the electron density due to the dielectric relaxation, introduction of the displacement current and so on. They are applied to an EMC of the GaAs MESFET with a submicrometer gate length. Their effectiveness is confirmed through a calculation of the spatial distributions of the electron density and the electric field and the current responses. The present variance reduction technique causes an increase of the computational time. But the increase is not so much.
引用
收藏
页码:1055 / 1059
页数:5
相关论文
共 50 条
  • [41] Variance Reduction Monte Carlo methods for wind turbines
    Sichani, M. T.
    Nielsen, S. R. K.
    Thoft-Christensen, P.
    APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING, 2011, : 141 - 149
  • [42] OPTIMAL VARIANCE REDUCTION FOR MARKOV CHAIN MONTE CARLO
    Huang, Lu-Jing
    Liao, Yin-Ting
    Chen, Ting-Li
    Hwang, Chii-Ruey
    SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2018, 56 (04) : 2977 - 2996
  • [43] Variance of the ensemble Monte Carlo algorithm for semiconductor transport modeling
    Nedjalkov, M
    Kosina, H
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2001, 55 (1-3) : 191 - 198
  • [44] Monte Carlo variance reduction with deterministic importance functions
    Haghighat, A
    Wagner, JC
    PROGRESS IN NUCLEAR ENERGY, 2003, 42 (01) : 25 - 53
  • [45] Variance reduction for Monte Carlo solutions of the Boltzmann equation
    Baker, LL
    Hadjiconstantinou, NG
    PHYSICS OF FLUIDS, 2005, 17 (05) : 1 - 4
  • [46] On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
    Chatterji, Niladri S.
    Flammarion, Nicolas
    Ma, Yi-An
    Bartlett, Peter L.
    Jordan, Michael I.
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 80, 2018, 80
  • [47] 'Supercomputer simulation of advanced semiconductor devices by self-consistent Monte Carlo Technique'
    Fjeldly, T.A.
    Jensen, G.U.
    Lund, B.
    Brudevoll, T.
    Shur, M.S.
    Proceedings of the Nordic Semiconductor Meeting, 1990,
  • [48] Neural Control Variates for Monte Carlo Variance Reduction
    Wan, Ruosi
    Zhong, Mingjun
    Xiong, Haoyi
    Zhu, Zhanxing
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2019, PT II, 2020, 11907 : 533 - 547
  • [49] Quantum transport simulation of nanoscale semiconductor devices based on Wigner Monte Carlo approach
    Koba, Shunsuke
    Aoyagi, Ryo
    Tsuchiya, Hideaki
    JOURNAL OF APPLIED PHYSICS, 2010, 108 (06)
  • [50] Ex post facto Monte Carlo variance reduction
    Booth, TE
    NUCLEAR SCIENCE AND ENGINEERING, 2004, 148 (03) : 391 - 402