Machine Learning for Jet Physics

Session

Heavy Ions

12 Dec 2017, 11:30

2-100 (Lawrence Berkeley National Laboratory)

19. Introduction and Overview (15'+5')

Peter Jacobs

12/12/2017, 11:30

9. Identifying QCD transition using convolution neural network (15'+5')

Long Pang

12/12/2017, 11:50

The initial state fluctuations in relativistic heavy ion collisions are converted to the final state correlations of soft particles in momentum space, through strong collective expansion of the quark gluon plasma (QGP) and the QCD transition from QGP to hadrons. The patterns (equations of state) encoded in the relativistic hydrodynamic evolution are extracted from the final particle...

5. Probing heavy ion collisions using quark and gluon jet substructure with machine learning (15'+5')

Dr Raghav Kunnawalkam Elayavalli (Wayne State University)

12/12/2017, 12:10

We study the classification of quark-initiated jets and gluon-initiated jets in proton-proton and heavy ion collisions using modern machine learning techniques. We train the deep convolutional neutral network on discretized jet images. The classification performance is compared with the multivariate analysis of several physically-contructed jet observables including the jet mass, the $p_T^D$,...