Search for Supersymmetry and Large Extra Dimensions with the ATLAS Experiment

The Large Hadron Collider is the most powerful particle accelerator built to date. It is a proton-proton and heavy ion collider which in 2015 and 2016 operated at an unprecedented center of mass energy of √s = 13 TeV. The Tile Calorimeter is the ATLAS hadronic calorimeter covering the central region of the detector. It is designed to measure hadrons, jets, tau particles and missing energy. In order to accurately be able to properly reconstruct these physical objects a careful description of the electronic noise is required. This thesis presents the work done in updating, monitoring and studying the noise calibration constants used in the processing and identication of hadronic jet in the 2011 data. Moreover the results of the searches for compressed supersymmetric squark-neutralino and large extra dimensions models are also presented in this thesis. The present work uses an experimental signature with a high energy hadronic jet and large missing transverse energy later often referred to as monojet signature. The search for supersymmetry is carried out using an integrated luminosity of 3.2 fb-1 recorded by the ATLAS experiment in 2015. The search for large extra dimensions presented in this work uses the full 2015 + 2016 dataset of 36.1 fb-1. No signicant excess compared to the Standard Model prediction has been observed on the production of squark pairs with the subsequent decay of the squark in a quark and a neutrino. Exclusion limits are set on squark production as a function of the neutralino mass. Squark masses up to 608 GeV are excluded for a mass difference between the squark and the neutralino of 5 GeV. In the second search for the presence of large extra spatial dimensions in the Arkani-Hamed, Dimopoulos and Dvali model scenario a good agreement between data and Standard Model prediction is observed and exclusion limits are set on the effective Planck scale MD of 7.7 and 4.8 TeV for two and six hypothesized large extra dimensions respectively signicantly improving earlier results