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Title: Identifying dark matter interactions in monojet searches

We study the discrimination of quark-initiated jets from gluon-initiated jets in monojet searches for dark matter using the technique of averaged jet energy profiles. We demonstrate our results in the context of effective field theories of dark matter interactions with quarks and gluons, but our methods apply more generally to a wide class of models. Different effective theories of dark matter and the standard model backgrounds each have a characteristic quark/gluon fraction for the leading jet. When used in conjunction with the traditional cut-and-count monojet search, the jet energy profile can be used to set stronger bounds on contact interactions of dark matter. In the event of a discovery of a monojet excess at the 14 TeV LHC, contact interactions between dark matter with quarks or with gluons can be differentiated at the 95% confidence level. For a given rate at the LHC, signal predictions at direct detection experiments for different dark matter interactions can span five orders of magnitude. Lastly, the ability to identify these interactions allows us to make a tighter connection between LHC searches and direct detection experiments.
 [1] ;  [2]
  1. Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
  2. Michigan State Univ., East Lansing, MI (United States)
Publication Date:
Report Number(s):
Journal ID: ISSN 1029-8479; arXiv eprint number arXiv:1312.5325
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Journal of High Energy Physics (Online)
Additional Journal Information:
Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2014; Journal Issue: 5; Journal ID: ISSN 1029-8479
Springer Berlin
Research Org:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Country of Publication:
United States
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; dark matter and double beta decay; jet substructure; jets
OSTI Identifier: