ALICE EMCal Reconstructable Energy Non-Linearity From Test Beam Monte Carlo

Calorimeters play many important roles in modern high energy physics detectors, such as event selection, triggering, and precision energy measurements. EMCal, in the case of the ALICE experiment provides triggering on high energy jets, improves jet quenching study measurement bias and jet energy resolution, and improves electron and photon measurements [3]. With the EMCal detector in the ALICE experiment taking on so many important roles, it is important to fully understand, characterize and model its interactions with particles. In 2010 SPS and PS electron test beam measurements were performed on an EMCal mini-module [2]. Alongside this, the test beam setup and geometry was recreated in Geant4 by Nico [1]. Figure 1 shows the reconstructable energy linearity for the SPS test beam data and that obtained from the test beam monte carlo, indicating the amount of energy deposit as hits in the EMCal module. It can be seen that for energies above ∼ 100 GeV there is a significant drop in the reconstructableenergymeasuredintheEMCalmodulefromthetestbeam, thisisduetoEM showersnotbeingfullycontainedlongitudinallyintheEMCalmodule, withsomeproportion of the particles from the shower exiting out its back. When compared with the same results for Monte Carlo data, there seems to be the start of a discrepancy in reconstructable energy at 100 GeV, with the MC overestimating the amount of reconstructable energy deposited in the module. It is thought that the cause of this overestimation is either due to problems in the simulation causing it to predict the loss of a smaller fraction of EM showers out of the backfaceoftheEMCalmodule, orinsufficientmodellingofinteractionsandcrosssectionsby the Monte Carlo generator Geant4. This report aims to investigate these two cases, firstly by comparing longitudinal and radial shower shapes from the Monte Carlo with baseline results from Wigmans [4], and secondly by updating to the more modern version of Geant4 (that used currently in AliRoot) to see if dataset improvements improve MC agreement.