Description

Particle transport Monte Carlo simulations are a key tool for High Energy Physics experiments, including the LHC experiments at CERN. All Monte Carlo (MC) simulations depend vitaly on Pseudo-Random Number Generators (PRNGs) used to sample many distributions. Each LHC experiments generates 5-10 Billion sampled physics events a year using around 10^18 sampled values from PRNGs. PRNGs take 1-5% of CPU time. PRNGs used must possess very large periods, fast execution, the ability to create a large number of streams, and very good correlation properties between streams and sampled values. It must be possible to reproduced a simulated event any time, for reexamination or debugging.

Task ideas

• Create a prototype that changes the use of random number generation in a Geant simulation so that the RNG state is associated with each track:
  • When a secondary is created, attach to it either a seed or a new state for PRNG, for use in that track.
  • Participating in extending the interface different PRNGs to provide different ways to choose the state of PRNG for a secondary.
  • Create implementations including MCRGs, counter-based PRNGs and novel PRNGs with guarantees of stream independence.

Requirements

Programming in C/C++ or Java at least for class projects is required. Use of Linux/Unix, cmake and/or a coding IDE (Eclipse, Xcode) will be assets. Knowledge gained: use of Pseudo-Random Number Generators and state of the art of PRNGs.

Mentors

• John Apostolakis
• Sandro Wenzel

Web site

http://cern.ch/geant4

Source code

https://github.com/Geant4/geant4

Corresponding Project

• Geant4

Participating Organizations

• CERN

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