Leading Particle Biasing Overview

Leading Particle Biasing Overview

Jane Tinslay, SLAC

March 2007

Jane Tinslay, SLAC 2

Overview of Techique

Classic electromagnetic leading particle biasing Applications where high energy particles initiate electromagnetic

showers may spend a significant amount of time in analogue shower simulation

Most important processes contributing to EM shower at high energies are bremsstrahlung and pair production - ie, two secondaries produced in each interaction

Reduce computing time by preferentially tracking the highest energy secondary - highest contribution to energy deposit

Hadronic leading particle biasing Hadronic interaction can produce many secondaries of same type

and with similar characteristics Reduce computing time by discarding a predetermined fraction of

them which don’t significantly contribute to shower Can also enhance production of interesting secondaries


Side Effects

Lateral shower profile not reliably reproduced Shower fluctuations not fully modeled

Possible to end up with large weight given to a few low energy particles Energy deposit fluctuations Codes recommend use of weight windows to control

weight fluctuations


Applications

Radiobiological doses Heating effects Radiation damage Estimating shower punch through Reduce time spend simulating hadronic

cascades Reduce time spent simulating high energy EM

showers


Leading Particle Biasing Summary

Classic EM HadronicGeneral

Multiplicity Tuning

Multiple Context

EGS4/EGS5/

EGSnrcY N/A N N

Fluka Y Y N Y

Geant4 N Y N N

MCNP N N N N

MCNPX N Y Y Y

Penelope N N/A N N


EGS4/EGS5/EGSnrc

EM Leading particle biasing for e-/e+/ initiated showers When bremsstrahlung/pair production event occurs,

continue to track only one of the two remaining particles Given:

R = random number between 0 and 1 F = fraction of kinetic energy assigned to the lower energy particle:

If (R < F) keep lower energy particle If (R> F) keep higher energy particle I.e, preferentially keep higher energy particle, but keep lower lower

energy particle some some of the time, to keep the game fair€

F =ELower

ELower + EHigher


Assign surviving particle a weight

Manual states that speed of shower calculations improved by factor of 300 at 33GeV Have problems with large weights reducing efficiency Generally get factors of 20+

€

W =ELower + EHigherESelected


Fluka EM Leading Particle Biasing

EM Leading particle biasing for e-/e+/ initiated showers Derived from the EGS4 implementation Modified to account for annihilation photons produced

from e+e- annihilation Secondary particle selection probability proportional to

useful energy rather than kinetic energy Useful energy e-/ = KE Useful energy e+ = KE + 2*me

Selected particle assigned weight which is inverse of selection probability Same as EGS4, with useful energy taken into consideration


Supports multiple configurations Process combinations:

Bremsstrahlung and pair production Bremsstrahlung Pair production Positron annihilation at rest Compton scattering Bhabha & Moller scattering Photoelectric effect Positron annihilation in flight

Energy thresholds for e-/e+/ Region dependent

Recommend using weight windows to deal with large weight fluctuations


Fluka Multiplicity Tuning

Leading particle biasing for hadrons/muon/photon photonuclear interactions

Define a factor by which average # secondaries should be scaled Always retain leading particle If factor < 1, play Russian Roulette to reduce # secondaries If factor > 1, split secondaries (duplicate particles, split weight) No Russian Roulette played if # secondaries < 3 Adjust weight as appropriate

Configuration: Mixed in with importance sampling configuration Region by region basis Possible to apply tuning to primary particles only Recommend use weight window to control weight fluctuations (region

defined)


Geant4 Hadronic Leading Particle Biasing(Current)

Built in utility for hadronic processes Keep only the most important part of the event

along with representative tracks of given particle types Always keep leading particle Of remaining tracks, if a particle type exists, select

one from each of Baryons, 0’s, mesons, leptons Adjust weight as appropriate

Question: Which frame leading particle determined in ?


MCNPX Secondary Particle Biasing

Similar to Fluka multiplicity tuning Applies to any particle

Effectively combined EM/Hadronic leading particle biasing

Define a factor Sn equivalent to Fluka scale factor Store appropriate weight Didn’t see any mention about keeping the leading

particle Possibly implied ?

Supports multiple configurations Secondary particle type Secondary particle energy Creator particle


References BEAMnrc Users Manual, D.W.O. Rogers et al. NRCC Report PIRS-0509(A)revK (2007) The EGS4 Code System, W. R. Nelson and H. Hirayama and D.W.O. Rogers, SLAC-265,

Stanford Linear Accelerator Center (1985) History, overview and recent improvements of EGS4, A.F. Bielajew et al., SLAC-PUB-6499

(1994) THE EGS5 CODE SYSTEM, Hirayama, Namito, Bielajew, Wilderman, Nelson

SLAC-R-730 (2006) The EGSnrc Code System, I. Kawrakow et al., NRCC Report PIRS-701 (2000) Variance Reduction Techniques, D.W.O. Rogers and A.F. Bielajew (Monte Carlo Transport of

Electrons and Photons. Editors Nelso, Jankins, Rindi, Nahum, Rogers. 1988) NRC User Codes for EGSnrc, D.W.O. Rogers, I. Kawrakow, J.P. Seuntjens, B.R.B. Walters and

E. Mainegra-Hing, PIRS-702(revB) (2005) http://www.fluka.org/course/WebCourse/biasing/P001.html http://www.fluka.org/manual/Online.shtml http://geant4.web.cern.ch/geant4/UserDocumentation/UsersGuides/ForApplicationDeveloper/

html/Fundamentals/biasing.html MCNPX 2.3.0 Users Guide, 2002 (version 2.5.0 is restricted) PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport,

Workshop Proceedings Barcelona, Spain 4-7 July 2006, Francesc Salvat, Jose M. Fernadez-Varea, Josep Sempau, Facultat de Fisica (ECM) , Universitat de Barcelona

Documents

Leading Particle Biasing Overview