论文标题
使用Deepjet的喷气风味分类
Jet Flavour Classification Using DeepJet
论文作者
论文摘要
对于现代高能物理实验，尤其是在LHC中，Jet风味分类对于广泛的应用至关重要。在本文中，我们为这项任务提出了一种新颖的体系结构，以利用现代深度学习技术。这个称为DeepJet的新模型克服了影响先前方法的输入大小的局限性。结果，重型风味分类的性能得到了改善，并且该模型也扩展到执行夸克 - 格鲁隆标签。
Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we propose a novel architecture for this task that exploits modern deep learning techniques. This new model, called DeepJet, overcomes the limitations in input size that affected previous approaches. As a result, the heavy flavour classification performance improves, and the model is extended to also perform quark-gluon tagging.
