Feasibility of reconstructing ttH (with H decaying to WW) for the purpose of measuring the Standard Model Higgs CP

in end to end analysis

This work investigates the feasibility of reconstructing ttH (with H decaying to WW) for the purpose of measuring the Standard Model Higgs CP. The method used to measure the Higgs CP relies on using the top quark momenta and therefore requires that the ttH topology be fully reconstructed. To this end, a fit based method using chi squared minimization is implemented and explored as a means by which the events can be reconstructed. This method is compared to a multivariate boosted decision tree implementation. The boosted decision tree implementation yields improved results compared to the fit based approach, particularly in events with a semi-leptonically decaying top. In such events, this approach is seen to yield improvements of the order of 10 % for certain aspects of the reconstructed topology and by as much as a few percent for the ttH topology as a whole.

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Optimization of the Level 2 electron-photon Trigger within ATLAS

in end to end analysis

This report outlines preliminary studies performed into the optimization of the ATLAS Level 2 electron-photon egamma trigger with respect to the 2010 data run. Electrons from Z decay are a major source of high pT electrons, an understanding of which is vital for many physics analyses. This optimization focuses on electrons from Z decay. The optimization procedure identifies signal (actual electrons) and background (mis-identified electrons) Level 2 trigger electrons using geometrical matching. Reducing the number of these background trigger electrons has obvious benefits with respect to data storage. A number of possible variables useful in discriminating this signal from background are identified. A log-likelihood ratio discriminant method is developed based on these variables and tested using Monte Carlo. The performance is cross checked using 2010 data. The log-likelihood discriminant method is compared with a cuts based method, based on individual variables and is shown to give improved results.

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Searching for the Higgs Boson with the ATLAS detector at CERN

in end to end analysis

The search potential of a Standard Model Higgs boson in the Vector Boson Fusion production mechanism with Higgs boson decaying to two leptons and two neutrinos via decay to two Z bosons with the ATLAS detector is investigated. The ATLAS detector is a general purpose detector in operation at CERN measuring proton-proton collisions produced by the Large Hadron Collider. This channel has been shown to have high sensitivity at large Higgs mass, where large amounts of missing energy in the signal provide good discrimination over expected backgrounds. This work takes a first look at whether the sensitivity of this channel may be improved using the remnants of the vector boson fusion process to provide extra discrimination, particularly at lower mass where sensitivity of the main analysis is reduced because of lower missing energy.

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Web Scraping text data with Scrapy and Beautiful Soup

in data cleaning

There is a wealth of information available on the internet. Web scraping is the process which enables people to collate and start to organise this data into a more structured format for further analysis. This project investigates this process using data provided by the UK Parliment, in particular the financial interests of members of the House of Commons. Attributes of the html data motivate the use of two Python libraries, Beautiful Soup and Scrapy, for this work.

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