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Title: Quark-gluon discrimination in the search for gluino pair production at the LHC

Journal Article · · Journal of High Energy Physics (Online)
 [1];  [2];  [3];  [4];  [5]
  1. Indian Institute of Science, Bangalore (India)
  2. Univ. of Pittsburgh, Pittsburgh, PA (United States)
  3. The Univ. of Tokyo, Kashiwa (Japan); KEK Theory Center and Sokendai, Tsukuba (Japan)
  4. Korea Advanced Institute of Science and Technology, Yuseong-gu (Republic of Korea)
  5. Cavendish Lab., Cambridge (United Kingdom)

Here, we study the impact of including quark- and gluon-initiated jet discrimination in the search for strongly interacting supersymmetric particles at the LHC. Taking the example of gluino pair production, considerable improvement is observed in the LHC search reach on including the jet substructure observables to the standard kinematic variables within a multivariate analysis. In particular, quark and gluon jet separation has higher impact in the region of intermediate mass-gap between the gluino and the lightest neutralino, as the difference between the signal and the standard model background kinematic distributions is reduced in this region. We also compare the predictions from different Monte Carlo event generators to estimate the uncertainty originating from the modelling of the parton shower and hadronization processes.

Research Organization:
Univ. of Wisconsin, Madison, WI (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
FG02-95ER40896
OSTI ID:
1346819
Journal Information:
Journal of High Energy Physics (Online), Vol. 2017, Issue 1; ISSN 1029-8479
Publisher:
Springer BerlinCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 16 works
Citation information provided by
Web of Science

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Cited By (5)

Weakly Supervised Classification in High Energy Physics text January 2017
Systematics of quark/gluon tagging text January 2017
Jet Substructure Studies with CMS Open Data text January 2017
Casimir Meets Poisson: Improved Quark/Gluon Discrimination with Counting Observables text January 2017
Spectral Analysis of Jet Substructure with Neural Networks: Boosted Higgs Case text January 2018