Using Neural Networks to Measure Drell-Yan Electron Pair Production Cross Section

Speaker: Colin Jacob

When: December 7, 2016 (Wed), 10:00AM to 11:30AM (add to my calendar)
Location: SCI 352

This event is part of the Preliminary Oral Exam.

Examining Committee: Larry Sulak, Sheldon Glashow, John Butler, Shyam Erramilli

Colin

Abstract:

A study of Drell-Yan dielectron production in proton-proton collisions at center-of-mass energy of 13 TeV at the Compact Muon Solenoid experiment at the Large Hadron Collider is presented. The Drell-Yan process is a Standard Model standard candle, which allows for precise measurements of Standard Model parameters. The study investigates the phase space: 71GeV<mee<111GeV,|ηe |<2.4,|ηjet |<2.4,p(T,e)>20,p(T,jet)>30. The Z boson mass and width are measured and compared with measurements from other studies. The cross-section σ of Z^0/γ^*→e^+ e^- as well as the differential cross-sections dσ/dY,dσ/(dmee ) are measured. The advantages of using neural networks to separate signal from background are presented, and the use of neural networks in this study is proposed. Improvements to software used in the Hadronic Calorimeter are presented.