Parametrizing Compton form factors with neural networks

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• 作者：Kre&scaron ; imir Kumeri膷ki^a ; Dieter Mü ; ller^b ; ^c ; Andreas Schä ; fer^d
• 关键词：Deeply virtual Compton scattering ; Generalized parton distributions ; neural networks
• 刊名：Nuclear Physics B - Proceedings Supplements
• 出版年：2012
• 期刊代码：46_09205632
• 类别：ph
• 出版时间：January-March, 2012
• 卷：222-224
• 期：Complete
• 页码：199-203
• 文件大小：558 K

摘要

We describe a method, based on neural networks, of revealing Compton form factors in the deeply virtual region. We compare this approach to standard least-squares model fitting both for a simplified toy case and for HERMES data.