论文标题
Parton分布功能
Parton distribution functions
论文作者
论文摘要
我们通过将其作为模式识别问题的一种特殊形式的形式来讨论对黑龙的帕顿子结构的确定，其中模式是概率分布，我们介绍了解决此问题的方法。具体而言，我们回顾了PDF确定的NNPDF方法，该方法基于Monte Carlo方法与神经网络作为基本基础插入器的组合。我们基于遗传最小化及其通过封闭测试的验证讨论当前的NNPDF方法。然后，我们提出了最新的发展，在该发展中，正在开发，优化和测试一个高度优化的深度学习框架以确定PDF。
We discuss the determination of the parton substructure of hadrons by casting it as a peculiar form of pattern recognition problem in which the pattern is a probability distribution, and we present the way this problem has been tackled and solved. Specifically, we review the NNPDF approach to PDF determination, which is based on the combination of a Monte Carlo approach with neural networks as basic underlying interpolators. We discuss the current NNPDF methodology, based on genetic minimization, and its validation through closure testing. We then present recent developments in which a hyperoptimized deep-learning framework for PDF determination is being developed, optimized, and tested.
