Tracking, b-tagging and measurement of the b-jet production cross section with the ATLAS detector

The Standard Model of elementary particle physics was developed to describe the fundamental particles which constitute matter and the interactions between them. The Large Hadron Collider (LHC) at CERN in Geneva was built to solve some of the remaining open questions in the Standard Model and to explore physics beyond it, by colliding two proton beams at world-record centre-of-mass energies. The ATLAS experiment is designed to reconstruct particles and their decay products originating from these collisions. The precise reconstruction of particle trajectories plays an important role in the identification of particle jets which originate from bottom quarks (b-tagging). This thesis describes the step-wise commissioning of the ATLAS track reconstruction and b-tagging software and one of the first measurements of the b-jet production cross section in pp collisions at sqrt(s)=7 TeV with the ATLAS detector. The performance of the track reconstruction software was studied in great detail, first using data from cosmic ray showers and then collisions at sqrt(s)=900 GeV and 7 TeV. The good understanding of the track reconstruction software allowed a very early deployment of the b-tagging algorithms. First studies of these algorithms and the measurement of the b-tagging efficiency in the data are presented. They agree well with predictions from Monte Carlo simulations. The b-jet production cross section was measured with the 2010 dataset recorded by the ATLAS detector, employing muons in jets to estimate the fraction of b-jets. The measurement is in good agreement with the Standard Model predictions.

Packing a trunk : a physically based approach with full motional freedom

Geometric packing problems may be formulated mathematically as constrained optimization problems. But finding a good solution is a challenging task. The more complicated the geometry of the container or the objects to be packed, the more complex the non-penetration constraints become. In this work we propose the use of a physics engine that simulates a system of colliding rigid bodies. It is a tool to resolve interpenetration conflicts and to optimize configurations locally. We develop an efficient and easy-to-implement physics engine that is specialized for collision detection and contact handling. In succession of the development of this engine a number of novel algorithms for distance calculation and intersection volume were designed and imple- mented, which are presented in this work. They are highly specialized to pro- vide fast responses for cuboids and triangles as input geometry whereas the concepts they are based on can easily be extended to other convex shapes. Especially noteworthy in this context is our ε-distance algorithm - a novel application that is not only very robust and fast but also compact in its im- plementation. Several state-of-the-art third party implementations are being presented and we show that our implementations beat them in runtime and robustness. The packing algorithm that lies on top of the physics engine is a Monte Carlo based approach implemented for packing cuboids into a container described by a triangle soup. We give an implementation for the SAE J1100 variant of the trunk packing problem. We compare this implementation to several established approaches and we show that it gives better results in faster time than these existing implementations.