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Abstract

In this thesis, data from proton-proton collisions at a center of mass energy of ps = 7 TeV and sqrt{s} = 8 TeV delivered by the Large Hadron Collider and recorded by the ATLAS experiment in the year 2011 and 2012 are used to develop a timing monitoring framework for the ATLAS Level-1 Calorimeter trigger system, to develop a soft electron tagger and carry out a feasibility study for the measurement of pp ->Z(e^+e^-) + b b-bar process respectively.

The Level-1 Calorimeter trigger is a hardware based trigger with a decision latency of up to 2.5 μs. It performs bunch-crossing identification and coarse energy measurement to make a trigger decision. These operations depend on precise timing adjustments which are done to achieve a correct sampling of the signal peaks. For an energy measurement of better than 2% in the trigger, the peak has to be sampled within +/- 5 ns. Software has been written to monitor the signal peak sampling offsets for all 7168 channels. This was done by measuring the signal peak location to the nanosecond level and monitoring this value as a function of time to verify the signal stability.

Conventional jet based b-tagging methods introduce jet energy scale uncertainties in measurements. Alternatively electrons from semileptonic decays of b-quarks can be used for b-tagging, avoiding these uncertainties. The new soft electron tagger developed in this work extensively uses the precision capabilities of the ATLAS Inner Detector and electromagnetic calorimeter system. Signal and background sources identified with Monte Carlo samples were trained with a multivariate boosted decision tree classifier, through supervised learning. The electron identification responses of signal samples were verified by statistically extracting signal distributions from J/psi->e^+e^- and Z -> e^+e^- enriched data samples. Efficiency and systematics of the new soft electron tagger were also estimated using J/psi ->e^+e^- enriched data samples.

A feasibility study for the measurement of pp->Z(e^+e^-)+b b-bar process using the soft electron tagger also has been carried out. Along with the newly developed soft electron tagger, charge combinations as well as kinematic distributions of soft-electron pairs have been used to create regions which are enhanced in the signal with a relatively large signal to background ratio.