Telescoping jet substructure

Abstract

We introduce a novel jet substructure method which exploits the variation of observables with respect to a sampling of phase-space boundaries quantified by the variability. We apply this technique to identify boosted W boson and top quark jets using telescoping subjets which utilizes information coming from subjet topology and that coming from subjet substructure. We find excellent performance of the variability, in particular its robustness against finite detector resolution. The extension to telescoping jet grooming and other telescoping jet substructure observables is also straightforward. This method provides a new direction in heavy particle tagging and suggests a systematic approach to the decomposition of jet substructure.

arXiv comment5 pages, 3 figures

References in corpus (37)

• The anti-k_t jet clustering algorithm
• A Brief Introduction to PYTHIA 8.1
• FastJet user manual
• Identifying Boosted Objects with N-subjettiness
• Soft Drop
• Jet Trimming
• Towards an understanding of jet substructure
• N-Jettiness: An Inclusive Event Shape to Veto Jets
• Maximizing Boosted Top Identification by Minimizing N-subjettiness
• Pileup Per Particle Identification
• Boosted objects: a probe of beyond the Standard Model physics
• Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning
• Techniques for improved heavy particle searches with jet substructure
• Jet Substructure at the Tevatron and LHC: New results, new tools, new benchmarks
• Power Counting to Better Jet Observables
• Boosted objects and jet substructure at the LHC
• Measurement of isolated photon production in pp and PbPb collisions at sqrt(sNN) = 2.76 TeV
• Seeing in Color: Jet Superstructure
• Identification techniques for highly boosted W bosons that decay into hadrons
• SoftKiller, a particle-level pileup removal method
• Performance of top-quark and $W$-boson tagging with ATLAS in Run 2 of the LHC
• $h\to Z\gamma$ in the complex two Higgs doublet model
• Particle-level pileup subtraction for jets and jet shapes
• W-jet Tagging: Optimizing the Identification of Boosted Hadronically-Decaying W Bosons
• Probing the time structure of the quark-gluon plasma with top quarks
• Qjets: A Non-Deterministic Approach to Tree-Based Jet Substructure
• Jet Cleansing: Pileup Removal at High Luminosity
• XCone: N-jettiness as an Exclusive Cone Jet Algorithm
• Jet Dipolarity: Top Tagging with Color Flow
• Measurement of colour flow with the jet pull angle in $t\bar{t}$ events using the ATLAS detector at $\sqrt{s}=8$ TeV
• Heavy resonances at energy-frontier hadron colliders
• Measurement of colour flow using jet-pull observables in $t\bar{t}$ events with the ATLAS experiment at $\sqrt{s}=13$ TeV
• Resolving Boosted Jets with XCone
• Telescoping Jets: Multiple Event Interpretations with Multiple R's
• Jet Sampling: Improving Event Reconstruction through Multiple Interpretations
• Fuzzy Jets
• Quantifying the power of multiple event interpretations

Cited by in corpus (5)

• Recursive Soft Drop
• Collinear Drop
• Probing heavy ion collisions using quark and gluon jet substructure with machine learning
• Identifying the Quantum Properties of Hadronic Resonances using Machine Learning
• Heavy ion jet physics studies using precision jet substructure and quark-gluon jet classification