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Else Lytken

Else Lytken

Professor

Else Lytken

Search for new phenomena in dijet events using 37 fb-1 of pp collision data collected at s =13 TeV with the ATLAS detector

Author

  • M Aaboud
  • G Aad
  • B. Abbott
  • J Abdallah
  • O Abdinov
  • B Abeloos
  • Torsten Åkesson
  • Simona Bocchetta
  • Caterina Doglioni
  • Vincent Hedberg
  • Göran Jarlskog
  • Charles Kalderon
  • Else Lytken
  • Ulf Mjörnmark
  • Trine Poulsen
  • Oxana Smirnova
  • Oleksandr Viazlo

Summary, in English

Dijet events are studied in the proton-proton collision data set recorded at s=13 TeV with the ATLAS detector at the Large Hadron Collider in 2015 and 2016, corresponding to integrated luminosities of 3.5 fb-1 and 33.5 fb-1 respectively. Invariant mass and angular distributions are compared to background predictions and no significant deviation is observed. For resonance searches, a new method for fitting the background component of the invariant mass distribution is employed. The data set is then used to set upper limits at a 95% confidence level on a range of new physics scenarios. Excited quarks with masses below 6.0 TeV are excluded, and limits are set on quantum black holes, heavy W′ bosons, W∗ bosons, and a range of masses and couplings in a Z′ dark matter mediator model. Model-independent limits on signals with a Gaussian shape are also set, using a new approach allowing factorization of physics and detector effects. From the angular distributions, a scale of new physics in contact interaction models is excluded for scenarios with either constructive or destructive interference. These results represent a substantial improvement over those obtained previously with lower integrated luminosity. © 2017 CERN.

Department/s

  • Particle and nuclear physics
  • eSSENCE: The e-Science Collaboration

Publishing year

2017

Language

English

Publication/Series

Physical Review D

Volume

96

Issue

5

Document type

Journal article

Publisher

American Physical Society

Topic

  • Subatomic Physics

Status

Published

ISBN/ISSN/Other

  • ISSN: 1550-2368