Finding the Effects of Jet Quenching with Machine Learning

Abstract

In the collisions of heavy ions we can find that a quark-gluon plasma forms. A result of this quark-gluon plasma is that jetquenching can take place. There has been a lot of research to study the workings of jetquenching. When we are looking at particle collisions however, it is not yet possible to reliably tell if a jet has been quenched based on their final state. In this research we wanted to find a way to look at the final state of a particle collision and tell if jet quenching had taken place. We firstly investigated the jets and looked at which parameters are important. After finding useful variables of the jets we used a machine learning algorithm to try and find a pattern between hundreds of thousands of simulated non quenched jets. We then looked at how this algorithm treated simulated quenched jets, to see if it would recognise them as being different. The Algorithm seemed successful at finding a difference between the normal jets and the quenched jets. It is however unsure how the algorithm found this pattern. We can therefore not say with certainty if the algorithm was successful. An important reason why the algorithm seemed to find a difference is due to the way the events are generated. Additional research is therefore needed to further study this problem, and to try to find whether machine learning can find a difference between quenched and non quenched jets. It could then also be used to look at real data of events and find out if they have been quenched and by how much.