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The neural network approach to parton fitting
We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parto...
| Autores principales: | , , , , |
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| Lenguaje: | eng |
| Publicado: |
2005
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1063/1.2122059 http://cds.cern.ch/record/834983 |
| Sumario: | We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits. |
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