ABCNet: An attention-based method for particle tagging

Understand

In high energy physics, graph-based implementations have the advantage of treating the input data sets in a similar way as they are collected by collider experiments.

• To expand on this concept, we propose a graph neural network enhanced by attention mechanisms called ABCNet.
• To exemplify the advantages and flexibility of treating collider data as a point cloud, two physically motivated problems are investigated: quark-gluon discrimination and pileup reduction.
• The former is an event-by-event classification while the latter requires each reconstructed particle to receive a classification score.