Speaker
Zhongtian Dong
(University of Kansas)
Description
Tensor Networks, originally developed for quantum many-body systems, offer powerful representations of high-dimensional data. When applied to discriminate top quark signals from QCD backgrounds, the entanglement entropy of the tensor network model can give us insight into the correlations it has learned. Moreover, our study shows tensor network model is more resilient to detector effects and pile-up.
