mFOAM-1.02: A compact version of the cellular event generator FOAM

The general-purpose self-adapting Monte Carlo (MC) event generator/simulator mFOAM (standing for mini-FOAM) is a new compact version of the FOAM program, with a slightly limited functionality with respect to its parent version. On the other hand, mFOAM is easier to use for the average user. This new version is fully integrated with the ROOT package, the C++ utility library used widely in the particle physics community. The internal structure of the code is simplified and the very valuable feature of the persistency of the objects of the mFOAM class is improved. With the persistency at hand, it is possible to record very easily the complete state of a MC simulator object based on mFOAM and ROOT into a disk-file at any stage of its use: just after object allocation, after full initialization (exploration of the distribution), or at any time during the generation of the long series of MC events. Later on the MC simulator object can be easily restored from the disk-file in the " ready to go " state. Objects of TFoam class can be used as a stand-alone solution to many everyday problems in the area of the Monte Carlo simulation, or as building blocks in large-scale MC projects, taking full advantage of the object-oriented technology and persistency. Title of the program: mFOAM (mini FOAM), version 1.02. At present mFOAM is distributed with the ROOT package (version 4.04 and later). Programming languages used: ANSI C++. High-speed storage required: Depends on the complexity of the problem. For the default 2000 cells it is about 25 MB while for 100,000 cells it allocates about 35 MB. These data are for running from CINT command line and include also memory consumption by CINT itself. No. of lines in combined program and test deck: mFOAM-1.02 2776 lines of C++ code. Nature of the physical problem: Monte Carlo integration or generation of unweighted (weight equals 1) events with a given probability distribution is a standard problem in many areas of research, ranging from high-energy physics to economy. In any library of general utilities it is highly desirable to include a general-purpose numerical tool (program) with the MC generation algorithm featuring the built-in capability of automatically adjusting generation procedure to an arbitrary pattern of singularities in the generated distribution. Our primary goal is the simulation of the differential distribution in the multiparticle Lorentz-invariant phase space for the purpose of comparison between Quantum Field …