There is strong motivation to study standard model physics using the highest-energy data provided by the Large Hadron Collider. This is aided by the process of defining clusters of hadrons to form ‘jets’. Existing jet-finders are dependent on pre-defined parameters which, to some extent, influence their properties. This thesis introduces a novel algorithm which aims to reconstruct partons outgoing from hard interactions, prior to any splitting, by concentrating solely on the highest momentum transfer scale. In this way parton properties such as fragmentation and structure functions from hadron colliders may be compared directly with results from DIS and e+e− annihilation. This original, standalone tool is named ‘traps’ - the Topological Reconstruction Algorithm for Parton Scatters. The algorithm was developed using Pythia Monte Carlo QCD events, under a pragmatic approach that assumes the model provides a good approximation to reality at both hadronic and partonic level. Various tests were made to gauge the performance of the algorithm against standard jet-finders. The infrared safety and algorithm speed were also assessed. The objective of traps is to have low sensitivity to parameters, and to be fast and robust. A high event acceptance is necessary, as maximum statistics are required where cross-sections are at their lowest. A chapter of this thesis is dedicated to a description of the author’s studies in calibration and monitoring of the timing of the ATLAS Level-1 Calorimeter Trigger system. Pulses from triggered energy are sent via largely η× φ = 0.1 × 0.1 granularity ‘trigger towers’. Synchronous triggering with 1-2 ns precision is required for the system to make an accurate energy estimate.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:554376 |
Date | January 2012 |
Creators | Ellis, K. V. |
Publisher | Queen Mary, University of London |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | http://qmro.qmul.ac.uk/xmlui/handle/123456789/8556 |
Page generated in 0.0015 seconds