A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations

Physics – Computational Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Scientific paper

10.1016/j.nima.2011.11.084

In Monte Carlo particle transport codes, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This makes it possible to increase the cross section of nuclear reactions by factors exceeding 10^4 (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful, for example, in problems that involve computation of particle penetration deep into a target, such as occurs in atmospheric showers or in shielding.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A probability-conserving cross-section biasing mechanism for variance reduction in Monte Carlo particle transport calculations will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-450154

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.