1997/05/31 by T. Maggipinto, G. Nardulli, S. Dusini +6 · 1 citation
Physics and Astronomy · #High-Energy Particle Collisions Research #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #hep-ex #hep-ph
paper · pdf · doi:10.1016/s0370-2693(97)00887-3
published as Phys.Lett. B409 (1997) 517-522 · Latex, 8 pages, 2 figures
arxiv created 1997/06/02 · openalex publication_date 1997/09/01 · arxiv updated 2009/11/30 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
We show that neural network classifiers can be helpful to discriminate Higgs production from background at LHC in the Higgs mass range M= 200 GeV. We employ a common feed-forward neural network trained by the backpropagation algorithm for off-line analysis and the neural chip Totem, trained by the Reactive Tabu Search algorithm, which could be used for on-line analysis.