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Title: An operational definition of quark and gluon jets

Journal Article · · Journal of High Energy Physics (Online)

While “quark” and “gluon” jets are often treated as separate, well-defined objects in both theoretical and experimental contexts, no precise, practical, and hadron-level definition of jet flavor presently exists. To remedy this issue, we develop and advocate for a data-driven, operational definition of quark and gluon jets that is readily applicable at colliders. Rather than specifying a per-jet flavor label, we aggregately define quark and gluon jets at the distribution level in terms of measured hadronic cross sections. Intuitively, quark and gluon jets emerge as the two maximally separable categories within two jet samples in data. Benefiting from recent work on data-driven classifiers and topic modeling for jets, we show that the practical tools needed to implement our definition already exist for experimental applications. As an informative example, we demonstrate the power of our operational definition using Z+jet and dijet samples, illustrating that pure quark and gluon distributions and fractions can be successfully extracted in a fully well-defined manner.

Research Organization:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25); USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26)
Grant/Contract Number:
SC0011090; SC0012567
OSTI ID:
1611581
Journal Information:
Journal of High Energy Physics (Online), Journal Name: Journal of High Energy Physics (Online) Journal Issue: 11 Vol. 2018; ISSN 1029-8479
Publisher:
Springer BerlinCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (20)

Topic model for four-top at the LHC journal January 2020
Learning the latent structure of collider events journal October 2020
The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics journal December 2021
Jet tagging via particle clouds journal March 2020
Properties of jet fragmentation using charged particles measured with the ATLAS detector in $pp$ collisions at $\sqrt{s}=13$ TeV text January 2019
Uncovering latent jet substructure text January 2019
A Theory of Quark vs. Gluon Discrimination text January 2019
Towards Machine Learning Analytics for Jet Substructure text January 2020
Anomaly Detection for Physics Analysis and Less than Supervised Learning preprint January 2020
Safety of Quark/Gluon Jet Classification preprint January 2021
Energy flow networks: deep sets for particle jets journal January 2019
Investigating the topology dependence of quark and gluon jets journal March 2019
A theory of quark vs. gluon discrimination journal October 2019
Uncovering latent jet substructure journal September 2019
Jet substructure at the Large Hadron Collider journal December 2019
Quark-gluon tagging: Machine learning vs detector journal January 2019
Energy Flow Networks: Deep Sets for Particle Jets text January 2018
Investigating the Topology Dependence of Quark and Gluon Jets text January 2018
Quark-Gluon Tagging: Machine Learning vs Detector text January 2018
A Theory of Quark vs. Gluon Discrimination text January 2019

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