A Generic Surface Sampler for Monte Carlo Simulations

被引：4

作者：

Detwiler, J. A. ^{[1
]}

Henning, R. ^{[1
,2
]}

Johnson, R. A. ^{[3
,4
]}

Marino, M. G. ^{[3
,4
]}

机构：

[1] Univ Calif Berkeley, Lawrence Berkeley Lab, Berkeley, CA 94720 USA

[2] Univ N Carolina, Dept Phys, Chapel Hill, NC 27599 USA

[3] Univ Washington, Dept Phys, Seattle, WA 98195 USA

[4] Univ Washington, Ctr Expt Nucl Phys & Astrophys, Seattle, WA 98195 USA

来源：

IEEE TRANSACTIONS ON NUCLEAR SCIENCE | 2008年 / 55卷 / 04期

关键词：

Algorithms; alpha particles; GEANT; imaging; simulation;

D O I：

10.1109/TNS.2008.2001063

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：

We present a Monte Carlo algorithm that generates points randomly and uniformly on a set of arbitrary surfaces. The algorithm is completely general and only requires the geometry, modeling software to provide the intersection points of an arbitrary line with the surface being sampled. We demonstrate the algorithm using the Geant4 Monte Carlo simulation toolkit. The efficiency of the sampling algorithm is discussed, along with various options in the implementation and example applications.

引用

页码：2329 / 2333

页数：5

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