Search for Dark Matter in dijet events using Quark/Gluon Tagging

Ribaric, Neza and Bertram, Iain (2019) Search for Dark Matter in dijet events using Quark/Gluon Tagging. Masters thesis, Lancaster University.

Text (NezaRMScbyResearch)
NezaRMScbyResearch.pdf - Published Version
Available under License Creative Commons Attribution-NoDerivs.
Download (6MB)

Abstract

This thesis explores the possibility of improving the limits set on the Dark Matter mediator Z′ obtained from the dijet invariant mass spectrum using a technique called quark/gluon tagging. The main discriminator between quark and gluon initiated jets is the number of tracks within the jet, however both linear and logarithmic functions of jet pT and invariant mass with various starting parameters were tested. The new limits obtained from the sub-samples were compared to the un-tagged dijet data sample generated to mimic 2015/2016 data of 37fb−1 collected with the ATLAS detector at the LHC. The samples are generated using Pythia 8 with the leading-order NNPDF 2.3 PDFs and A14 tune and the detector response is modeled in Geant 4. It was shown that for an ideal separation (based on parton truth ID), the improvement in significance can range up to 50%. However, the best separation functions based on jet pT and mjj show improvements in the range of 2-5%. The dependence on mjj shows potential for significant improvements in the mass range lower than the one analyzed in this thesis.