Real Time Energy Reconstruction in the ATLAS Hadronic Calorimeter and ATLAS sensitivity to Extra Dimension Models

This work has been fulfilled within the ATLAS collaboration. I present here two studies, both related with the ATLAS detector and its operation. The ATLAS detector is described in chapter 1 whereas chapter 2 shows an introduction to the ATLAS tile calorimeter and the TileCal Read-Out Drivers (ROD) where the first part of the thesis is developed. In chapter 3 I present the study and the implementation of the Optimal Filtering algorithm in the TileCal Read-Out Drivers. The ROD provides the energy and the arrival time of the digital signal that is generated in the tile calorimeter. These parameters are reconstructed online using the Optimal Filtering algorithm, the RODs also provide a quality factor of the reconstruction. This information is sent to the standard ATLAS acquisition data flow with a specific data format defined in this thesis. Chapter 4 contains a short introduction to the Standard Model, presents its problems and describes other theories like Supersymmetry, Little Higgs or Extra Dimension models that try to solve them. The ATLAS experiment is enhanced to detect the Higgs boson and to study the physics at the TeV scale. Chapter 5 shows the study of the Kaluza-Klein gluon resonances predicted by models with extra dimensions. These searches are investigated through the decays of the excited gluons to high transverse momentum jets (pT) measured in the tile calorimeter. In this chapter I also propose the measurement of the polarization of the top quark from the excited gluon decay to discriminate between different models with similar final signatures. A summary and the main conclusions of the analyses are presented in the last part of the thesis. On one hand the implementation of the Optimal Filtering algorithm in the ROD DSPs of TileCal and the validation of this algorithm using cosmic muons from the ATLAS commissioning has been done. And on the other hand the ATLAS sensitivity to observe signatures predicted by extra dimension models has been presented.