Maximizing boosted top identification by minimizing N-subjettiness
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Author(s)
Thaler, Jesse
Van Tilburg, Ken
Date Issued
February 2012
Journal
Journal of High Energy Physics
Publisher
Springer-Verlag
Citation
Thaler, Jesse, and Ken Tilburg. “Maximizing Boosted Top Identification by Minimizing N-subjettiness.” Journal of High Energy Physics 2012.2 (2012): p. 1-33.
Version
Author's final manuscript
Abstract
N -subjettiness is a jet shape designed to identify boosted hadronic objects such as top quarks. Given N subjet axes within a jet, N-subjettiness sums the angular distances of jet constituents to their nearest subjet axis. Here, we generalize and improve on N -subjettiness by minimizing over all possible subjet directions, using a new variant of the k-means clustering algorithm. On boosted top benchmark samples from the BOOST2010 workshop, we demonstrate that a simple cut on the 3-subjettiness to 2-subjettiness ratio yields 20% (50%) tagging efficiency for a 0.23% (4.1%) fake rate, making N -subjettiness a highly effective boosted top tagger. N-subjettiness can be modified by adjusting an angular weighting exponent, and we find that the jet broadening measure is preferred for boosted top searches. We also explore multivariate techniques, and show that additional improvements are possible using a modified Fisher discriminant. Finally, we briefly mention how our minimization procedure can be extended to the entire event, allowing the event shape N-jettiness to act as a fixed N cone jet algorithm.
MIT Department
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1007/jhep02(2012)093
