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Scientific article
Open access
English

Search for periodic signals in the dielectron and diphoton invariant mass spectra using 139 fb−1 of pp collisions at \sqrt{s} = 13 TeV with the ATLAS detector

ContributorsATLAS Collaboration
Published inThe journal of high energy physics, vol. 2023, no. 10, 79
Publication date2023
First online date2023-10-13
Abstract

A search for physics beyond the Standard Model inducing periodic signals in the dielectron and diphoton invariant mass spectra is presented using 139 fb$^{−1}$ of $ \sqrt{s} $ = 13 TeV pp collision data collected by the ATLAS experiment at the LHC. Novel search techniques based on continuous wavelet transforms are used to infer the frequency of periodic signals from the invariant mass spectra and neural network classifiers are used to enhance the sensitivity to periodic resonances. In the absence of a signal, exclusion limits are placed at the 95% confidence level in the two-dimensional parameter space of the clockwork gravity model. Model-independent searches for deviations from the background-only hypothesis are also performed.

eng
Keywords
  • Beyond Standard Model
  • Hadron-Hadron Scattering
  • Particle and Resonance Production
  • P p: scattering
  • P p: colliding beams
  • Electron: pair production
  • Photon: pair production
  • Gravitation: model
  • Dimension: 2
  • Spin: resonance
  • Spin: 2
  • Graviton
  • Kaluza-Klein model
  • Mass spectrum: (electron positron)
  • Mass spectrum: (2photon)
  • Mass spectrum: two-photon
  • ATLAS
  • New physics: search for
  • Sensitivity
  • CERN LHC Coll
  • Wavelet
  • Neural network
  • Upper limit
  • Statistical analysis
  • Data analysis method
  • Experimental results
  • 13000 GeV-cms
Citation (ISO format)
ATLAS Collaboration. Search for periodic signals in the dielectron and diphoton invariant mass spectra using 139 fb<sup>−1 </sup>of <i>pp</i> collisions at <i> \sqrt{s} </i> = 13 TeV with the ATLAS detector. In: The journal of high energy physics, 2023, vol. 2023, n° 10, p. 79. doi: 10.1007/jhep10(2023)079
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ISSN of the journal1029-8479
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