Minimisation strategies for the determination of parton density functions

We discuss the current minimisation strategies adopted by research projects involving the determination of parton distribution functions (PDFs) and fragmentation functions (FFs) through the training of neural networks. We present a short overview of a proton PDF determination obtained using the cova...

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Detalles Bibliográficos
Autores principales: Carrazza, Stefano, Hartland, Nathan P.
Lenguaje:eng
Publicado: 2017
Materias:
hep-ph
Particle Physics - Phenomenology
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/1085/5/052007
http://cds.cern.ch/record/2300080
Descripción
Sumario:We discuss the current minimisation strategies adopted by research projects involving the determination of parton distribution functions (PDFs) and fragmentation functions (FFs) through the training of neural networks. We present a short overview of a proton PDF determination obtained using the covariance matrix adaptation evolution strategy (CMA-ES) optimisation algorithm. We perform comparisons between the CMA-ES and the standard nodal genetic algorithm (NGA) adopted by the NNPDF collaboration.

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