Searches for New Physics in final states containing one lepton and two b-jets using the ATLAS detector
Lead Research Organisation:
University of Liverpool
Department Name: Physics
Abstract
The Standard Model of Particle Physics (SM), despite being extremely successful experimentally, leaves many questions unanswered. Cosmological observations estimate that only ~5% of the Universe's content is baryonic matter described by the SM, while ~27% is matter which is non-interacting with photons, known as Dark Matter (DM). DM is unexplained at the fundamental particle level as the SM fails to provide a suitable candidate. Searches for physics beyond the SM (BSM) are therefore needed to understand our Universe at the smallest scales.
The production mechanism for DM is unknown and thus searches for a large variety of BSM models, such as Supersymmetry (SUSY), are undertaken. SUSY introduces an additional symmetry between bosons and fermions, the result being the introduction of partner-particles for each of the SM particles, known as 'sparticles'. Combinations of the sparticles can be formed to give fermions known as charginos and neutralinos; the lightest neutralino is often assumed to be the lightest supersymmetric particle (LSP). The LSP is an extremely important particle as in models prohibiting its decay, it is an excellent candidate for DM.
A search is being undertaken to discover SUSY in proton collision events containing a chargino and next-to-lightest neutralino pair. These are unstable and decay respectively to a SM W boson and an LSP and a Higgs boson and an LSP. The W boson subsequently decays into a lepton and a neutrino while the Higgs decays to two b-quarks, which hadronise into jets. The two LSPs in the event escape detection, and along with the neutrino, form a measurable momentum imbalance, referred to as missing transverse energy. This search was undertaken using data collected at ATLAS in 2010-2012 at a centre-of-mass energy of 8 TeV, with no significant excess above the SM expectation observed. A result using data collected in 2015-2016 at a centre-of-mass energy of 13 TeV is expected to greatly significantly increase sensitivity in this channel.
The production mechanism for DM is unknown and thus searches for a large variety of BSM models, such as Supersymmetry (SUSY), are undertaken. SUSY introduces an additional symmetry between bosons and fermions, the result being the introduction of partner-particles for each of the SM particles, known as 'sparticles'. Combinations of the sparticles can be formed to give fermions known as charginos and neutralinos; the lightest neutralino is often assumed to be the lightest supersymmetric particle (LSP). The LSP is an extremely important particle as in models prohibiting its decay, it is an excellent candidate for DM.
A search is being undertaken to discover SUSY in proton collision events containing a chargino and next-to-lightest neutralino pair. These are unstable and decay respectively to a SM W boson and an LSP and a Higgs boson and an LSP. The W boson subsequently decays into a lepton and a neutrino while the Higgs decays to two b-quarks, which hadronise into jets. The two LSPs in the event escape detection, and along with the neutrino, form a measurable momentum imbalance, referred to as missing transverse energy. This search was undertaken using data collected at ATLAS in 2010-2012 at a centre-of-mass energy of 8 TeV, with no significant excess above the SM expectation observed. A result using data collected in 2015-2016 at a centre-of-mass energy of 13 TeV is expected to greatly significantly increase sensitivity in this channel.
Organisations
People |
ORCID iD |
Monica D'Onofrio (Primary Supervisor) | |
Matthew Sullivan (Student) |
Publications
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ST/N504142/1 | 01/10/2015 | 31/03/2021 | |||
1796912 | Studentship | ST/N504142/1 | 01/10/2016 | 31/07/2020 | Matthew Sullivan |
Description | Machine Learning outreach talk to ecologists |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Many ecology postgraduate students at the University of Aberdeen attended my seminar on the use of machine learning classification. Examples were given in the context of my own research in HEP, along with an example I developed using deep learning to identify individual marmots from trap camera footage. |
Year(s) Of Engagement Activity | 2019 |