Biasing in random number space

An interesting way to compare the biased random number technique to more conventional biasing techniques is to consider what is really calculated by analog Monte-Carlo. Each history is associated with a random number sequence \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \u...

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Bibliographische Detailangaben
1. Verfasser: Booth, T. E.
Format: Buchkapitel
Sprache:eng
Online-Zugang:Volltext
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Zusammenfassung:An interesting way to compare the biased random number technique to more conventional biasing techniques is to consider what is really calculated by analog Monte-Carlo. Each history is associated with a random number sequence \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$\vec r_i$$ \end{document} and a history score \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$T(\vec r_i )$$ \end{document} that depends on the random walk specified by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$\vec r_i$$ \end{document}. The random number sequence \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$\vec r_i$$ \end{document} is selected from a uniform density \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$f(\vec r)$$ \end{document} of random number sequences. The expected score is then: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$E = \smallint T(\vec r)f(\vec r)d\vec r$$ \end{document}. When the calculation is biased, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} $$T(\vec r)$$ \end{document} is normally altered to some \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\odd
ISSN:0075-8450
1616-6361
DOI:10.1007/BFb0049058