Study of the impact of environmental parameters on the operation of CMS RPCs

CMS (Compact Muon Solenoid) is a general purpose detector designed to run at the highest luminosity at Large Hadron Collider (LHC), CERN, Geneva, Switzerland. The muon system of the CMS experiment relies on Drift Tubes (DT), Cathode Strip Chambers (CSC) and Resistive Plate Chambers (RPC). RPCs are dedicated for the first level muon trigger and they are characterized by bakelite electrodes delimited in a specialized gas volume filled with operational gas mixture. This analysis has been done for the RPC chambers installed in CMS experiment at CERN. The Currents of CMS RPCs chambers are analyzed as a function of environmental parameters such as Temperature, Humidity and pressure, which are important for the operation of the muon detector system. A novel Neural Network approach has been used to analyze the data and to build a model using experimental measurements and combining the results of the simulations. Data from RPC Chambers in CMS experiment are taken and compared to the results from neural Network.