Supersymmetry and LHC missing energy signals

Carena, Marcela (Fermi National Accelerator Laboratory, P.O. Box 500, Batavia, Illinois 60510, USA) (Enrico Fermi Institute and Kavli Institute for Cosmological Physics, University of Chicago, Chicago, Illinois 60637, USA) ; Osborne, James (Department of Physics & Astronomy, Wayne State University, Detroit, Michigan 48201, USA) ; Shah, Nausheen R. (Department of Physics & Astronomy, Wayne State University, Detroit, Michigan 48201, USA) ; Wagner, Carlos E. M. (Enrico Fermi Institute and Kavli Institute for Cosmological Physics, University of Chicago, Chicago, Illinois 60637, USA) (HEP Division, Argonne National Laboratory, 9700 Cass Avenue, Argonne, Illinois 60439, USA)

07 December 2018

Abstract: Current analyses of the LHC data put stringent bounds on strongly interacting supersymmetric particles, restricting the masses of squarks and gluinos to be above the TeV scale. However, the supersymmetric electroweak sector is poorly constrained. In this article we explore the consistency of possible LHC missing energy signals with the broader phenomenological structure of the electroweak sector in low energy supersymmetry models. As an example, we focus on the newly developed recursive jigsaw reconstruction analysis by ATLAS, which reports interesting event excesses in channels containing dilepton and trilepton final states plus missing energy. We show that it is not difficult to obtain compatibility of these LHC data with the observed dark matter relic density, the bounds from dark matter direct detection experiments, and the measured anomalous magnetic moment of the muon. We provide analytical expressions which can be used to understand the range of gaugino masses, the value of the Higgsino mass parameter, the heavy Higgs spectrum, the ratio of the Higgs vacuum expectation values tanβ, and the slepton spectrum obtained in our numerical analysis of these observables.


Published in: Physical Review D 98 (2018)
Published by: APS
DOI: 10.1103/PhysRevD.98.115010
arXiv: 1809.11082
License: CC-BY-4.0



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