Classification of Equation of State in Relativistic Heavy-Ion Collisions Using Deep Learning

Understand

Convolutional Neural Nets, which is a powerful method of Deep Learning, is applied to classify equation of state of heavy-ion collision event generated within the UrQMD model.

• Event-by-event transverse momentum and azimuthal angle distributions of protons are used to train a classifier.
• An overall accuracy of classification of 98\% is reached for Au+Au events at $\sqrt{s_{NN}} = 11$ GeV.
• Performance of classifiers, trained on events at different colliding energies, is investigated.