An Optimal Observable for Color Singlet Identification

Abstract

We present a novel approach to construct a color tagger, i.e. an observable that is able to discriminate the decay of a color-singlet into two jets from a two-jet background in a different color configuration. We do this by explicitly taking the ratio of the corresponding leading-order matrix elements in the soft limit, thus obtaining an observable that is provably optimal within our approximation. We call this observable the "jet color ring" and we compare its performance to other color-sensitive observables such as jet pull and dipolarity. We also assess the performance of the jet color ring in simulations by applying it to the case of the hadronic decays of a boosted Higgs boson and of an electroweak boson.

10 pages, 6 figures, ancillary Rivet routine provided

References in corpus (46)

• Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC
• PYTHIA 6.4 Physics and Manual
• PYTHIA 6.2 Physics and Manual
• The anti-k_t jet clustering algorithm
• An Introduction to PYTHIA 8.2
• MadGraph 5 : Going Beyond
• A General Algorithm for Calculating Jet Cross Sections in NLO QCD
• Pileup subtraction using jet areas
• Identifying Boosted Objects with N-subjettiness
• Soft Drop
• Matching matrix elements and shower evolution for top-quark production in hadronic collisions
• The Dipole Formalism for the Calculation of QCD Jet Cross Sections at Next-to-Leading Order
• N-Jettiness: An Inclusive Event Shape to Veto Jets
• Observation of Higgs boson decay to bottom quarks
• Robust Independent Validation of Experiment and Theory: Rivet version 3
• Observation of $H\to b\bar{b}$ decays and $VH$ production with the ATLAS detector
• Jet-Images -- Deep Learning Edition
• Power Counting to Better Jet Observables
• Seeing in Color: Jet Superstructure
• Sudakov Safety in Perturbative QCD
• Finding top quarks with shower deconstruction
• Finding physics signals with shower deconstruction
• Super-leading logarithms in non-global observables in QCD: Colour basis independent calculation
• Unsafe but Calculable: Ratios of Angularities in Perturbative QCD
• Boosting $H\to b\bar{b}$ with Machine Learning
• Search for a pseudoscalar boson decaying into a Z boson and the 125 GeV Higgs boson in llbb final states
• Soft gluons at large angles in hadron collisions
• Search for the standard model Higgs boson produced through vector boson fusion and decaying to b bbar
• Finding physics signals with event deconstruction
• Jet Dipolarity: Top Tagging with Color Flow
• Quark-Gluon tagging with Shower Deconstruction: Unearthing dark matter and Higgs couplings
• Jet vetoing at the LHC
• The Hidden Geometry of Particle Collisions
• Soft evolution of multi-jet final states
• Measurement of colour flow with the jet pull angle in $t\bar{t}$ events using the ATLAS detector at $\sqrt{s}=8$ TeV
• Resurrecting the Dead Cone
• Hadron collisions and the fifth form factor
• Measurement of color flow in t-tbar events from p-pbar collisions at sqrt(s)=1.96 TeV
• Measurement of colour flow using jet-pull observables in $t\bar{t}$ events with the ATLAS experiment at $\sqrt{s}=13$ TeV
• Higgs Boson Decay to Light Jets at the LHC
• Boosted Multijet Resonances and New Color-Flow Variables
• Distinguishing Color-Octet and Color-Singlet Resonances at the Large Hadron Collider
• Theory Predictions for the Pull Angle
• Safe Use of Jet Pull
• Calculating Pull for Non-Singlet Jets
• An approach to constraining the Higgs width at the LHC and HL-LHC

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• Measurements of $WH$ and $ZH$ production with Higgs boson decays into bottom quarks and direct constraints on the charm Yukawa coupling in $13\mathrm{TeV}$ $pp$ collisions with the ATLAS detector
• The $Higgs\to b\bar{b},c\bar{c},gg$ measurement at CEPC
• Systematic Quark/Gluon Identification with Ratios of Likelihoods
• Interplay of Traditional Methods and Machine Learning Algorithms for Tagging Boosted Objects
• Riemannian Data preprocessing in Machine Learning to focus on QCD color structure
• Designing Observables for Quantum Interference in Jets at Subleading Color
• Identifying the Quantum Properties of Hadronic Resonances using Machine Learning
• Systematically Constructing the Likelihood for Boosted $H\to gg$ Decays
• Tagging the Higgs boson decay to bottom quarks with colour-sensitive observables and the Lund jet plane
• Jet Charge with Global Event Shapes: Probing Quark Flavor Dynamics