1999/10/31 by S. Jadach · 2 citations
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Combinatorics #Computational science #Computer science #Dimension (graph theory) #Event (particle physics) #Fortran #Generator (circuit theory) #Geometry #Grid #Initialization #Markov Chains and Monte Carlo Methods #Markov chain Monte Carlo #Mathematical Approximation and Integration #Mathematics #Monte Carlo integration #Monte Carlo method #Monte Carlo molecular modeling #Parallel Computing and Optimization Techniques #Physics #Quasi-Monte Carlo method #Simplex #Statistical physics #Statistics #hep-ph #physics.comp-ph
paper · pdf · doi:10.1016/s0010-4655(00)00047-3
published as Comput.Phys.Commun. 130 (2000) 244-259
arxiv created 1999/12/14 · openalex publication_date 2000/08/01 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
A new general purpose Monte Carlo event generator with self-adapting grid consisting of simplices is described. In the process of initialization, the simplex-shaped cells divide into daughter subcells in such a way that: (a) cell density is biggest in areas where integrand is peaked, (b) cells elongate themselves along hyperspaces where integrand is enhanced/singular. The grid is anisotropic, i.e. memory of the axes directions of the primary reference frame is lost. In particular, the algorithm is capable of dealing with distributions featuring strong correlation among variables (like ridge along diagonal). The presented algorithm is complementary to others known and commonly used in the Monte Carlo event generators. It is, in principle, more effective then any other one for distributions with very complicated patterns of singularities - the price to pay is that it is memory-hungry. It is therefore aimed at a small number of integration dimensions (<10). It should be combined with other methods for higher dimension. The source code in Fortran77 is available from http://home.cern.ch/~jadach