Título: Neural particle Discriminator Based on Principal Components Analysis
Autores: Seixas, J. M.; Caloba, L. P.; Kastrup, B.
Resumo: An electron/jets discriminator for high energy physics experiments is devoloped using neural networks. A principal componentes analysis is performed in order to reduce dramatically the input space dimension. So that system implementation becomes simpler. It is shown that using simulated calorimeter data. 95% electron efficiency is obtrained with 9,5% of jets being misidentified, when input data is projected onto the subspace spanned by six principal components.
Código DOI: 10.21528/CBRN1994-001
Artigo em PDF: CBRN1994-paper1.pdf
Arquivo BibTex: CBRN1994-paper1.bib