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Looking for Beyond the Standard Model Physics in Dijet-Plus-Lepton Final-State Events Collected with the ATLAS Detector

A search for a new resonant state decaying exclusively to two quarks in events with at least two jets and one isolated charged lepton using $139~fb^{-1}$ of proton-proton collision data collected by the ATLAS detector at $\sqrt{s} = 13$~TeV is presented. Requiring a charged lepton in dijet final sta...

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Detalles Bibliográficos
Autor principal: Pascuzzi, Vincent
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:http://cds.cern.ch/record/2705515
Descripción
Sumario:A search for a new resonant state decaying exclusively to two quarks in events with at least two jets and one isolated charged lepton using $139~fb^{-1}$ of proton-proton collision data collected by the ATLAS detector at $\sqrt{s} = 13$~TeV is presented. Requiring a charged lepton in dijet final states provides sensitivity to extensions of the Standard Model which predict the production of dijet resonances in association with leptonically-decaying vector bosons or top quarks. Whereas inclusive searches are limited to resonance masses greater than $1$~TeV due to jet-based triggers which have a minimum jet transverse momentum of about $400$~GeV, lepton triggers can be as low as $24$~GeV, thereby permitting access to resonance masses of order 100~GeV. The search presented in this thesis considers a dijet invariant mass range between $0.22$--$6.3$~TeV. The largest deviation between the number of observed events and the Standard Model background estimate was found at a dijet invariant mass $m_{jj} =1.3$~TeV with a global statistical significance of $0.5$ standard deviations. In the absence of a statistically significant deviation of the data from the background expectation, exclusion limits are set at a 95\% confidence level on the presence of generic Gaussian-shaped signals of different masses and widths. Such signals are excluded with cross sections ranging from $40$--$0.03$~fb between $0.25$--$6.0$~TeV. Limits are also set in the context of a Technicolor model and a Simplified Dark Matter model. A follow-up search using a machine learning approach is discussed last.