Point cloud transformers applied to collider physics

Abstract Methods for processing point cloud information have seen a great success in collider physics applications. One recent breakthrough machine learning is the usage of transformer networks to learn semantic relationships between sequences language processing. In this work, we apply modified network called as method incorporate advantages architecture an unordered set particles resulting from collision events. To compare performance with other strategies, study jet-tagging applications highly-boosted particles.