Jet substructure studies with CMS open data

We use public data from the CMS experiment to study the two-prong substructure of jets. The CMS open data are based on 31.8  pb^{-1} of 7 TeV proton-proton collisions recorded at the Large Hadron Collider in 2010, yielding a sample of 768,687 events containing a high-quality central jet with transve...

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Bibliographic Details
Main Authors: Tripathee, Aashish (Contributor), Xue, Wei (Contributor), Larkoski, Andrew (Contributor), Marzani, Simone (Contributor), Thaler, Jesse (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Physics (Contributor)
Format: Article
Language:English
Published: American Physical Society, 2018-07-25T13:15:34Z.
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Summary:We use public data from the CMS experiment to study the two-prong substructure of jets. The CMS open data are based on 31.8  pb^{-1} of 7 TeV proton-proton collisions recorded at the Large Hadron Collider in 2010, yielding a sample of 768,687 events containing a high-quality central jet with transverse momentum larger than 85 GeV. Using CMS's particle flow reconstruction algorithm to obtain jet constituents, we extract the two-prong substructure of the leading jet using soft-drop declustering. We find good agreement between results obtained from the CMS open data and those obtained from parton shower generators, and we also compare to analytic jet substructure calculations performed to modified leading-logarithmic accuracy. Although the 2010 CMS open data do not include simulated data to help estimate systematic uncertainties, we use track-only observables to validate these substructure studies.
Massachusetts Institute of Technology. Charles E. Reed Faculty Initiatives Fund
United States. Department of Energy (Contracts No. DE-SC-00012567)
United States. Department of Energy (Contracts No. DE-SC-00015476)
National Science Foundation (U.S.) (Grant No. PHY-1419008, the LHC Theory Initiative)
National Science Foundation (U.S.) (Grant No. PHY-0969510, the LHC Theory Initiative)
National Science Foundation (U.S.) (Grant No. PHY-1619867)
Massachusetts Institute of Technology. Undergraduate Research Opportunities Program