Detecção online eficiente de eventos raros utilizando detectores finamente segmentados

Abstract

Large physics experiments, which work by investigating the frontiers of knowledge, push technological limits further and further, so that new discoveries can be achieved. A good example is the largest and most complex particle accelerator ever built, the LHC (Large Hadron Collider). In order to increase the probability of observing rare physical events, the particles are accelerated and collide at high energies and high rates. ATLAS, the largest LHC experiment, was designed to observe and analyze the collision subproducts and study a wide variety of interesting topics in physics. For this purpose, the LHC is planning to increase both the energy and luminosity of collisions, and upgrades are required for ATLAS to be able to operate in such hard conditions while maintaining or improving performance. For high efficiency in detecting signals of interest, ATLAS uses an online trigger system. The work developed in this thesis is based on the ATLAS update context for operation in increased luminosity conditions, which deteriorates the online trigger performance. Therefore, a solution is presented for high bandwidth occupancy in the first-level online trigger for muon detection. The solution involves the use of the main hadronic calorimeter for muon detection and a fusion of information between the calorimeter and the muon spectrometer, in order to reject particles that hit the muon chambers but are not LHC interest. The integration results of this solution in ATLAS, as well as the performance analysis, are presented in this work, and proves to keep the high efficiency (> 98%) of the online trigger system with a rate reduction of 6 percentual points for the take signal bandwidth.