Novel Networks in Collider Searches for New Physics

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dc.contributor.advisorWhite, Martin
dc.contributor.advisorJackson, Paul
dc.contributor.authorMullin, Anna Jane
dc.contributor.schoolSchool of Physical Sciencesen
dc.date.issued2021
dc.description.abstractBeyond-Standard Model (BSM) physics searches at the LHC are limited by the amount of information available to distinguish a new physics process from its backgrounds. Analyses apply a range of classification algorithms to obtain sensitivity to rare signals, but are challenged to obtain enough information in a broad parameter space without relying on heavy optimisation in narrow search regions. LHC event classification techniques become more powerful when they can be applied broadly to diverse models, requiring a large number of independent variables sensitive to anomalous signals. In our prototype ATLAS search, we create new variables that target information not used in current methods. Whereas typical variables treat events in isolation, we obtain further discrimination from the “similarity” between event pairs by evaluating “distances” in a kinematic space. A map of event similarities forms a graph network, which provides a convenient range of network variables able to quantify local topologies. In networks constructed from nodes of LHC events, we aim to use network variables to increase sensitivity to anomalous topologies local to BSM events. Our proof-of-principle analysis reveals that BSM physics events may populate distinct distributions compared with Standard Model events in several types of network variables, including measures of local centrality and clustering, using supersymmetry searches as examples. Graph network analysis may contribute power to existing methods of event classification and increase sensitivity to anomalous signatures.en
dc.description.dissertationThesis (MPhil) -- University of Adelaide, School of Physical Sciences, 2021en
dc.identifier.urihttps://hdl.handle.net/2440/133440
dc.language.isoenen
dc.provenanceThis electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exceptions. If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legalsen
dc.subjectgraphen
dc.subjectgraph networken
dc.subjectATLASen
dc.subjectParticle physicsen
dc.subjectLHCen
dc.subjectHEPen
dc.titleNovel Networks in Collider Searches for New Physicsen
dc.typeThesisen

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