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Title: Energy flow polynomials: a complete linear basis for jet substructure

Abstract

We introduce the energy flow polynomials: a complete set of jet substructure observables which form a discrete linear basis for all infrared- and collinear-safe observables. Energy flow polynomials are multiparticle energy correlators with specific angular structures that are a direct consequence of infrared and collinear safety. We establish a powerful graph-theoretic representation of the energy flow polynomials which allows us to design efficient algorithms for their computation. Many common jet observables are exact linear combinations of energy flow polynomials, and we demonstrate the linear spanning nature of the energy flow basis by performing regression for several common jet observables. Using linear classification with energy flow polynomials, we achieve excellent performance on three representative jet tagging problems: quark/gluon discrimination, boosted W tagging, and boosted top tagging. Lastly, the energy flow basis provides a systematic framework for complete investigations of jet substructure using linear methods.

Authors:
 [1];  [1];  [1]
  1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Center for Theoretical Physics
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
OSTI Identifier:
1501473
Grant/Contract Number:  
SC0011090; SC0012567
Resource Type:
Accepted Manuscript
Journal Name:
Journal of High Energy Physics (Online)
Additional Journal Information:
Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2018; Journal Issue: 4; Journal ID: ISSN 1029-8479
Publisher:
Springer Berlin
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; Jets; QCD Phenomenology

Citation Formats

Komiske, Patrick T., Metodiev, Eric M., and Thaler, Jesse. Energy flow polynomials: a complete linear basis for jet substructure. United States: N. p., 2018. Web. doi:10.1007/jhep04(2018)013.
Komiske, Patrick T., Metodiev, Eric M., & Thaler, Jesse. Energy flow polynomials: a complete linear basis for jet substructure. United States. doi:10.1007/jhep04(2018)013.
Komiske, Patrick T., Metodiev, Eric M., and Thaler, Jesse. Wed . "Energy flow polynomials: a complete linear basis for jet substructure". United States. doi:10.1007/jhep04(2018)013. https://www.osti.gov/servlets/purl/1501473.
@article{osti_1501473,
title = {Energy flow polynomials: a complete linear basis for jet substructure},
author = {Komiske, Patrick T. and Metodiev, Eric M. and Thaler, Jesse},
abstractNote = {We introduce the energy flow polynomials: a complete set of jet substructure observables which form a discrete linear basis for all infrared- and collinear-safe observables. Energy flow polynomials are multiparticle energy correlators with specific angular structures that are a direct consequence of infrared and collinear safety. We establish a powerful graph-theoretic representation of the energy flow polynomials which allows us to design efficient algorithms for their computation. Many common jet observables are exact linear combinations of energy flow polynomials, and we demonstrate the linear spanning nature of the energy flow basis by performing regression for several common jet observables. Using linear classification with energy flow polynomials, we achieve excellent performance on three representative jet tagging problems: quark/gluon discrimination, boosted W tagging, and boosted top tagging. Lastly, the energy flow basis provides a systematic framework for complete investigations of jet substructure using linear methods.},
doi = {10.1007/jhep04(2018)013},
journal = {Journal of High Energy Physics (Online)},
number = 4,
volume = 2018,
place = {United States},
year = {2018},
month = {4}
}

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Cited by: 26 works
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