Commissioning and performance of the trigger and readout system of the liquid argon calorimeter of the ATLAS experiment.

Research in High Energy Physics seeks to identify the fundamental constituents of matter and uncover the laws that govern their interactions. To conduct experiments at high energy particle accelerators and colliders are being used. The actual most powerful particle collider is the Large Hadron Collider (LHC) installed at CERN. Four experiments are hosted on the four collision points of this collider. One of these experiments is ATLAS which consists of a general purpose particle detector. To detect phenomena with low probability in the collision data, large amount of collisions are needed. The LHC will undergo two upgrade phases to increase its luminosity and therefore the number of collisions. The first upgrade phase is being finalized at the moment before the start of the run 3. The second phase will start in 2026 and will lead to the High Luminosity LHC (HL-LHC). An upgrade of the ATLAS detector is needed at each of the LHC upgrade phases. This insures that the data acquisition and the physics performance are not degraded with the more stringent conditions induced by the higher LHC luminosity. During the first upgrade phase a new trigger data path is added for the liquid argon calorimeter. The on-detector electronic boards of this new path digitize the electronic signals from the detector before sending them to the ATLAS processing systems. It allows to in- crease the readout granularity by a factor of ten. This digital system, described in this thesis, will replace the old electronic system which is based on analog transmission of the detector signals. The new on-detector boards of this system are configured and monitored using a new system based on OPC-UA servers. The installation and commissioning of this system was successfully completed in March 2022. The descrip- tion of the complete system, its implementation and performances are presented and discussed. The second upgrade phase of the liquid argon calorimeter will take place in the next long shutdown of the LHC starting in 2026. During this second phase, the complete electronic chain of this calorimeter will be replaced, in particular its elec- tronic signal processing boards, thus bringing new computing and signal processing capabilities. This new readout system is presented then the use of artificial neural networks to reconstruct the detector signals into energies is described and studied. Embedded on these electronic boards, the implementation of the neural networks and the performances obtained are presented and discussed.