Editing VEGAS algorithm (section)

{{short description|Algorithm}}
The '''VEGAS algorithm''', due to [[G. Peter Lepage]],<ref name=Lepage1978>{{cite journal|last=Lepage|first=G.P.|title=A New Algorithm for Adaptive Multidimensional Integration|journal=Journal of Computational Physics|date=May 1978|volume=27|issue=2|pages=192–203|doi=10.1016/0021-9991(78)90004-9|bibcode=1978JCoPh..27..192L}}</ref><ref name=Lepage1980>{{cite journal|last=Lepage|first=G.P.|title=VEGAS: An Adaptive Multi-dimensional Integration Program|journal=Cornell Preprint|volume=CLNS 80-447|date=March 1980}}</ref><ref name=Ohl1999>{{cite journal|last=Ohl|first=T.|title=Vegas revisited: Adaptive Monte Carlo integration beyond factorization|journal=Computer Physics Communications|date=July 1999|volume=120|issue=1|pages=13–19|doi=10.1016/S0010-4655(99)00209-X|arxiv=hep-ph/9806432|bibcode=1999CoPhC.120...13O|s2cid=18194240}}</ref> is a method for [[variance reduction|reducing error]] in [[Monte Carlo simulation]]s by using a known or approximate [[probability distribution]] function to concentrate the search in those areas of the [[integrand]] that make the greatest contribution to the final [[integral]].

The VEGAS algorithm is based on [[importance sampling]]. It samples points from the probability distribution described by the function <math>|f|,</math> so that the points are concentrated in the regions that make the largest contribution to the integral. The [[GNU Scientific Library]] (GSL) provides a VEGAS routine.