MONTE CARLO NONUNIFORM SAMPLING TECHNIQUE APPLIED TO THE KLEIN-NISHINA PROBABILITY DENSITY FUNCTION.

Y. S. Horowitz; A. Dubi; S. Mordechai

doi:10.13182/nse76-a26906

MONTE CARLO NONUNIFORM SAMPLING TECHNIQUE APPLIED TO THE KLEIN-NISHINA PROBABILITY DENSITY FUNCTION.

Y. S. Horowitz, A. Dubi, S. Mordechai

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2 Scopus citations

Abstract

The Monte Carlo generalized rejection technique provides a continuous passage from the inverse equation sampling method to the uniform sampling rejection method. It is well known that the nonuniform rejection method can be used to achieve very significant increases in sampling efficiency. The nonuniform rejection method has been applied to the Klein-Nishina Probability Density Function and have obtained improved efficiencies over the uniform sampling method of up to 100% at high gamma-ray energies and 10 to 60% improved efficiencies in the energy range from 0. 3 to 1. 5 MeV, respectively.

Original language	English
Pages (from-to)	461-482
Number of pages	22
Journal	Nuclear Science and Engineering
Volume	60
Issue number	4
DOIs	https://doi.org/10.13182/nse76-a26906
State	Published - 1 Jan 1976

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Nuclear Energy and Engineering

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abstract = "The Monte Carlo generalized rejection technique provides a continuous passage from the inverse equation sampling method to the uniform sampling rejection method. It is well known that the nonuniform rejection method can be used to achieve very significant increases in sampling efficiency. The nonuniform rejection method has been applied to the Klein-Nishina Probability Density Function and have obtained improved efficiencies over the uniform sampling method of up to 100% at high gamma-ray energies and 10 to 60% improved efficiencies in the energy range from 0. 3 to 1. 5 MeV, respectively.",

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MONTE CARLO NONUNIFORM SAMPLING TECHNIQUE APPLIED TO THE KLEIN-NISHINA PROBABILITY DENSITY FUNCTION.

Abstract

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