2004/07/01 by A. Bueno, A. Martínez de la Ossa, A. Martinez de la Ossa +2
Physics and Astronomy · #Astrophysics and Cosmic Phenomena #Neutrino Physics Research #Radiation Detection and Scintillator Technologies #hep-ph
paper · pdf · doi:10.1088/1126-6708/2004/11/014
published as JHEP0411:014,2004 · 24 pages, 15 figures
arxiv created 2004/07/01 · openalex publication_date 2004/11/10 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/01
Classic statistical techniques (like the multi-dimensional likelihood and the Fisher discriminant method) together with Multi-layer Perceptron and Learning Vector Quantization Neural Networks have been systematically used in order to find the best sensitivity when searching for νμ→ ντ oscillations. We discovered that for a general direct ντ appearance search based on kinematic criteria: a) An optimal discrimination power is obtained using only three variables (Evisible, PTmiss and ρl) and their correlations. Increasing the number of variables (or combinations of variables) only increases the complexity of the problem, but does not result in a sensible change of the expected sensitivity. b) The multi-layer perceptron approach offers the best performance. As an example to assert numerically those points, we have considered the problem of ντ appearance at the CNGS beam using a Liquid Argon TPC detector.