Computer Physics Communications Program Library

Programs in Physics & Physical Chemistry

PROGRAM SUMMARY

Manuscript Title: MC-TESTER: a universal tool for comparisons of Monte Carlo predictions for particle decays in high energy physics.
Authors: P. Golonka, T. Pierzchala, Z. Was
Program title: MC-TESTER version 1.1
Catalogue identifier: ADSM
Journal reference: Comput. Phys. Commun. 157(2004)39
Programming language: C ++, Fortran 77.
Computer: PC.
Operating system: Linux Red Hat 6.1/7.2/8.0.
RAM: 40M words
Keywords: Particle physics, Elementary, Event Reconstruction, Decay simulation, Monte Carlo methods, Invariant mass distributions, Programs comparison.
Classification: 11.9.
Nature of problem: The decays of individual particles are well defined modules of a typical Monte Carlo program chain in high energy physics. A fast semi-automatic way of comparing results from different programs is often desirable, for the development of new programs, to check correctness of the installations or for discussion of uncertainties.
Solution method: A typical HEP Monte Carlo program stores the generated events in the event records such as HEPEVT or PYJETS. MC_TESTER scans, event by event, the contents of the record and searches for the decays of the particle under study. The list of the found decay modes is successively incremented and histograms of all invariant masses which can be calculated from the momenta of the particle decay products are defined and filled. The outputs from the two runs of distinct programs can be later compared. A booklet of comparisons is created: for every decay channel, all histograms present in the two outputs are plotted and parameter quantifying shape difference is calculated. Its maximum over every decay channel is printed in the summary table.
Restrictions: For a list of limitations see section 6 of the manuscript.
Running time: Varies substantially with the analyzed decay particle. On a PC/Linux with 2.0 GHz processors MC-TESTER increases the run time of the τ-lepton Monte Carlo program TAUOLA by 4.0 seconds for every 100 000 analyzed events (generation itself takes 26 seconds). The analysis step takes 13 seconds; LaTeX processing takes additionally 10 seconds. Generation step runs may be executed simultaneously on multi-processor machines.