Increasing efficiency of ion-solid Monte Carlo simulations by using stratified sampling

被引:0
|
作者
Universidad de La Laguna, Tenerife, Spain [1 ]
机构
来源
Radiation Effects and Defects in Solids | 1997年 / 141卷 / 1 -4 pt 1期
关键词
This work was supported in part by BMBF (Germany) and MEC (Spain) through Acciones Integradas 1995. The Author would like to thank Dr. Matthias Posselt; Dr. Karl-Heinz Heinig; and the staff of the Institute of Ion Beam Physics and Material Research; for their support during his stay at the Forschungszentrum Rossendorf;
D O I
暂无
中图分类号
学科分类号
摘要
12
引用
收藏
页码:23 / 36
相关论文
共 50 条
  • [1] Increasing efficiency of ion-solid Monte Carlo simulations by using stratified sampling
    Jakas, MM
    RADIATION EFFECTS AND DEFECTS IN SOLIDS, 1997, 141 (1-4): : 23 - 36
  • [2] A simplified Monte-Carlo calculation to model ion-solid interactions in the classroom
    Kitanovski, Karlo
    Braunstein, Gabriel
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS, 2007, 261 (1-2): : 255 - 257
  • [3] Monte Carlo simulations of benthic macroinvertebrate populations: estimates using random, stratified, and gradient sampling
    Statzner, B
    Gore, JA
    Resh, VH
    JOURNAL OF THE NORTH AMERICAN BENTHOLOGICAL SOCIETY, 1998, 17 (03): : 324 - 337
  • [4] Increasing the efficiency of Monte Carlo simulation with sampling from an approximate potential
    Bandyopadhyay, Pradipta
    CHEMICAL PHYSICS LETTERS, 2013, 556 : 341 - 345
  • [5] Increasing the efficiency of Monte Carlo cohort simulations with variance reduction techniques
    Shechter, Steven M.
    Schaefer, Andrew J.
    Braithwaite, R. Scott
    Roberts, Mark S.
    MEDICAL DECISION MAKING, 2006, 26 (05) : 550 - 553
  • [6] Improving the sampling efficiency of Monte Carlo molecular simulations: an evolutionary approach
    Leblanc, B
    Braunschweig, B
    Toulhoat, H
    Lutton, E
    MOLECULAR PHYSICS, 2003, 101 (22) : 3293 - 3308
  • [7] Uncertainty quantification in ion-solid interaction simulations
    Preuss, R.
    von Toussaint, U.
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS, 2017, 393 : 26 - 28
  • [8] Adaptive strategy for stratified Monte Carlo sampling
    Carpentier, Alexandra
    Munos, Remi
    Antosy, András
    Journal of Machine Learning Research, 2015, 16 : 2231 - 2271
  • [9] Adaptive Strategy for Stratified Monte Carlo Sampling
    Carpentier, Alexandra
    Munos, Remi
    Antos, Andras
    JOURNAL OF MACHINE LEARNING RESEARCH, 2015, 16 : 2231 - 2271
  • [10] Stratified random sampling for dependent inputs in Monte Carlo simulations from computer experiments
    Mondal, Anirban
    Mandal, Abhijit
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2020, 205 : 269 - 282