Application of Gene Expression Programming to Event Selection in High Energy Physics
Liliana Teodorescu · 2009
Gene Expression Programming is a new evolutionary algorithm found to be very efficient for solving benchmark problems from computer science.The algorithm was successfully tested for event selection in high energy physics for the K S π π decay process.This paper presents an extended version of this analysis, as well as a comparison of its results with those obtained with an Artificial Neural Network and a Boosted Decision Trees method.All three methods produced selection functions which allowed good signal and background separation for the problem investigated, with the classification accuracies higher than 95%.