A general approach to search for supersymmetry at the LHC by combining signal enhanced kinematic regions using the ATLAS detector

The Standard Model of particle physics is a very successful theory, but it cannot describe e.g. gravity or explain the hierarchy problem. Supersymmetry is a proposed extension to the Standard Model that would solve some of its shortcomings by introducing a relation between fermions and bosons through the existence of a supersymmetric partner to every particle in the Standard Model. Since it is a broken symmetry, supersymmetric particles are heavier than their Standard Model counterparts. No supersymmetric particle has been observed to date. The ATLAS experiment at the Large Hadron Collider is a multi-purpose detector to measure parameters in the Standard Model and conduct searches for new particles. Searching for supersymmetric particles is one of the main goals of the experiment. In 2012, 20.3~fb$^{-1}$ of data at a centre-of-mass energy of $\sqrt{s}$ = 8 TeV was collected by ATLAS. In this thesis, I analyzed the ATLAS data and developed a novel statistical approach that bins a signal enhanced region in phase space into many sub-regions. In a later step, these regions are statistically combined to enhance the sensitivity to a supersymmetric signal. The use of modern likelihood techniques allows to apply my method in a consistent and general way to supersymmetry searches. It can also be applied to other searches. Since no excess in data is observed, I set limits on masses of the supersymmetric particles. The results are compared with another search, which interpreted its results in the same models. My method led to an observed improvement of the limit on the supersymmetric particle masses at the 95 % confidence level of up to 100 GeV, only by only improving the search method, without the need of additional data. I also tested optical receiver components which are built into the readout chain of a new detector subsystem. The tests carried out are also explained in this thesis.