Performance of the High Level Trigger gamma-conversion reconstruction chain in the ALICE central tracking detectors

Abstract

Photons are produced through various processes in the particle and nuclei collisions at the LHC, and pose as useful probes of the formation of a Qaurk-Gluon Plasma. The probability of a photon converting within the central tracking detectors of ALICE has been found to be approximately 8-9%. The thesis explores the performance of the photon reconstruction through the conversion method, for the High Level Trigger using the central tracking detectors of ALICE. The photon reconstruction method through its conversion will compliment the photon detection performed by the calorimeters. However, due to the large acceptance of the central tracking detectors, the method has proved equally beneficial through the off-line event reconstruction, even though the conversion probability is low. It has therefore been a goal to map the potential performance of an on-line reconstruction of the photons through the conversion method. The performance of the photon reconstruction has been analyzed through the simulation, and subsequent High Level Trigger reconstruction, of highly contrived events and minimum bias p-p collisions at √s = 14 TeV per nucleon pair. The events were embedded with additional Γs in the central pseudo-rapidity range to provide higher statistics. The analysis led to the optimization and further development of the existing code in the High Level Trigger, dedicated to the on-line reconstruction of neutral particles through the detection of their decay products. An overview of the reconstruction algorithm and potential future upgrades is provided. The results obtained for the simulated data is presented along side the optimal off-line results. The final results obtained for the Γ embedded minimum bias p-p collisions for the on-line reconstruction, yielded an average photon conversion reconstruction efficiency of 41.7%, with an average purity of the reconstructed sample of 74.2%.