The Large Hadron Collider, due for completion at the end of 2007, will provide an essential piece in the puzzle of electroweak symmetry breaking. Precision measure ments from LEP predict a low mass Standard Model Higgs boson close to the current experimental lower limit. In this mass region identification of the Higgs boson will be difficult, requiring more than one channel to be studied. ttH0, H0 → bb is one of three channels proposed for this purpose. In order to reduce the large backgrounds full reconstruction of the two top-quarks in the event is necessary. This thesis inves tigates a number of new techniques to improve the reconstruction procedure of this channel using the fast simulation of the ATLAS detector, Atlfast. Methods inves tigated include the introduction of hadronic W candidates created from three jets combined with a new energy rescaling method for the W candidates. A new quantity to choose the jet pairings in the event, utilising jet and lepton energy uncertainties from Atlfast, is studied. An Artificial Neural Network is trained to select signal from background events. An increase in the expected signal significance from 1.8 to 2.4 for an integrated luminosity of 30fb_1 and Higgs mass of 120GeV is observed from the techniques proposed. An important tool for any high energy physics experiment is an event display program. Visual representation is the most efficient way to transfer data from a computer to the human brain, providing the user with a powerful tool to investigate specific events. The Atlantis event display for the ATLAS experiment is presented, along with the development carried out to enable its use in the 2004 Combined Test Beam. The test beam used a full slice of the detector to provide an essential study of the performance capabilities of ATLAS.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:434912 |
| Date | January 2006 |
| Creators | Drohan, Janice Gail |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1444633/ |
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