Investigating the topology dependence of quark and gluon jets

A bstractAs most target final states for searches and measurements at the Large Hadron Collider have a particular quark/gluon composition, tools for distinguishing quark- from gluon-initiated jets can be very powerful. In addition to the difficulty of the classification task, quark-versus-gluon jet tagging is challenging to calibrate. The difficulty arises from the topology dependence of quark-versus-gluon jet tagging: since quarks and gluons have net quantum chromodynamic color charge while only colorless hadrons are measured, the radiation pattern inside a jet of a particular type depends on the rest of its environment. Given a definition of a quark or gluon jet, this paper studies the topology dependence of such jets in simulation. A set of phase space regions and jet substructure observables are identified for further comparative studies between generators and eventually in data.

[1]  C. Frye,et al.  Factorization for groomed jet substructure beyond the next-to-leading logarithm , 2016, Journal of High Energy Physics.

[2]  T. Hussain,et al.  Measurement of D0, D+, D*+ and D s + production in Pb-Pb collisions at sNN−−−√=5.02 TeV , 2018, 1804.09083.

[3]  V. M. Ghete,et al.  Charged-particle nuclear modification factors in PbPb and pPb collisions at sNN=5.02$$ \sqrt{s_{\mathrm{N}\;\mathrm{N}}}=5.02 $$ TeV , 2016 .

[4]  B. Nachman,et al.  Jet substructure at the Large Hadron Collider: A review of recent advances in theory and machine learning , 2017, Physics Reports.

[5]  F. Tegenfeldt,et al.  TMVA - Toolkit for multivariate data analysis , 2012 .

[6]  B. Nachman,et al.  Classification without labels: learning from mixed samples in high energy physics , 2017, Journal of High Energy Physics.

[7]  V. M. Ghete,et al.  Search for vectorlike light-flavor quark partners in proton-proton collisions at √{s }=8 TeV , 2018 .

[8]  E. Vallazza,et al.  The BaBar Physics Book: Physics at an Asymmetric B Factory , 1998 .

[9]  L. Dery,et al.  Weakly supervised classification in high energy physics , 2017, Journal of High Energy Physics.

[10]  M. P. Casado,et al.  Measurement of the charged-particle multiplicity inside jets from $$\sqrt{s}=8$$s=8$${\mathrm{TeV}}$$TeV pp collisions with the ATLAS detector , 2016, The European physical journal. C, Particles and fields.

[11]  C. Frye,et al.  Casimir meets Poisson: improved quark/gluon discrimination with counting observables , 2017, Journal of High Energy Physics.

[12]  S. D. Ellis,et al.  Recombination algorithms and jet substructure: Pruning as a tool for heavy particle searches , 2009, 0912.0033.

[13]  P. Alam.  ‘A’ , 2021, Composites Engineering: An A–Z Guide.

[14]  E. Metodiev,et al.  Jet Topics: Disentangling Quarks and Gluons at Colliders. , 2018, Physical review letters.

[15]  M. P. Casado,et al.  Search for the Standard Model Higgs boson produced by vector-boson fusion and decaying to bottom quarks in s=8$$ \sqrt{s}=8 $$ TeV pp collisions with the ATLAS detector , 2016 .

[16]  D. Barducci,et al.  Bounding wide composite vector resonances at the LHC , 2015, 1511.01101.

[17]  T. Morimoto.  Markov Processes and the H -Theorem , 1963 .

[18]  D. Kar,et al.  Systematics of quark/gluon tagging , 2017, 1704.03878.

[19]  T. Tuuva,et al.  Search for direct production of supersymmetric partners of the top quark in the all-jets final state in proton-proton collisions at s=13$$ \sqrt{s}=13 $$ TeV , 2017, 1707.03316.

[20]  R. Ellis,et al.  QCD Jet Broadening in Hadron Hadron Collisions , 1986 .

[21]  G. Soyez,et al.  Soft drop , 2014, 1402.2657.

[22]  M. P. Casado,et al.  Measurement of colour flow using jet-pull observables in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$t\bar{t}$$\en , 2018, The European Physical Journal C.

[23]  F. Tackmann,et al.  Dissecting soft radiation with factorization. , 2014, Physical review letters.

[24]  Gebräuchliche Fertigarzneimittel,et al.  V , 1893, Therapielexikon Neurologie.

[25]  R. Frederix,et al.  The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations , 2014, 1405.0301.

[26]  M. Campanelli,et al.  Jet substructure at the Large Hadron Collider , 2018, Reviews of Modern Physics.

[27]  W. Waalewijn,et al.  Gaining (mutual) information about quark/gluon discrimination , 2014, Journal of High Energy Physics.

[28]  J. Butterworth,et al.  Jet substructure as a new Higgs-search channel at the Large Hadron Collider. , 2008, Physical review letters.

[29]  M. Cacciari,et al.  FastJet user manual , 2011, 1111.6097.

[30]  P. Alam.  ‘G’ , 2021, Composites Engineering: An A–Z Guide.

[31]  B. Nachman.  Investigating the Quantum Properties of Jets and the Search for a Supersymmetric Top Quark Partner with the ATLAS Detector , 2016, 1609.03242.

[32]  Patrick T. Komiske,et al.  Deep learning in color: towards automated quark/gluon jet discrimination , 2016, Journal of High Energy Physics.

[33]  G. Salam,et al.  Towards an understanding of jet substructure , 2013, 1307.0007.

[34]  E. Farhi.  Quantum Chromodynamics Test for Jets , 1977 .

[35]  P. Richardson,et al.  Improving the simulation of quark and gluon jets with Herwig 7 , 2017, 1708.01491.

[36]  B. Webber,et al.  Jet broadening measures in e + e - annihilation , 1992 .

[37]  M. Schwartz,et al.  Seeing in color: jet superstructure. , 2010, Physical review letters.

[38]  Patrick T. Komiske,et al.  An operational definition of quark and gluon jets , 2018, Journal of High Energy Physics.

[39]  G. Salam,et al.  Small-radius jets to all orders in QCD , 2014, 1411.5182.

[40]  Jesse Thaler,et al.  On the Topic of Jets , 2018 .

[41]  V. M. Ghete,et al.  Search for $\mathrm{t}\overline{\mathrm{t}}$H production in the all-jet final state in proton-proton collisions at $\sqrt{s}=$ 13 TeV , 2018 .

[42]  Kai Wang,et al.  Quark jet versus gluon jet: fully-connected neural networks with high-level features , 2017, Science China Physics, Mechanics & Astronomy.

[43]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[44]  V. M. Ghete,et al.  Search for supersymmetry in proton-proton collisions at 13 TeV using identified top quarks , 2017 .

[45]  S. D. Ellis,et al.  Techniques for improved heavy particle searches with jet substructure , 2009, 0903.5081.

[46]  S. M. Ali,et al.  A General Class of Coefficients of Divergence of One Distribution from Another , 1966 .

[47]  M. Cacciari,et al.  The anti-$k_t$ jet clustering algorithm , 2008, 0802.1189.

[48]  M. D. Pietra,et al.  Search for the Standard Model Higgs boson produced by vector-boson fusion in 8 TeV pp collisions and decaying to bottom quarks with the ATLAS detector , 2016 .

[49]  B. Webber,et al.  Transverse Momentum Moments of Hadron Distributions in {QCD} Jets , 1981 .

[50]  S. M. Etesami,et al.  Measurement of electroweak production of two jets in association with a Z boson in proton–proton collisions at \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{ , 2014, The European Physical Journal C.

[51]  M. Schwartz,et al.  Quark and gluon tagging at the LHC. , 2011, Physical review letters.

[52]  M. Schwartz,et al.  Quark and gluon jet substructure , 2012, Journal of High Energy Physics.

[53]  Anna Zilnyk.  A brief introduction to… , 2011 .

[54]  Lian-tao Wang,et al.  Jet trimming , 2009, 0912.1342.

[55]  J. T. Childers,et al.  Light-quark and gluon jet discrimination in pp collisions at √s=7 TeV with the ATLAS detector , 2014, 1405.6583.

[56]  J. T. Childers,et al.  Light-quark and gluon jet discrimination in [Formula: see text] collisions at [Formula: see text] with the ATLAS detector. , 2014, The European physical journal. C, Particles and fields.

[57]  Jason I. Brown,et al.  Measurement of color flow in tt̄ events from pp̄ collisions at √s=1.96TeV , 2011 .

[58]  P. Skands,et al.  Tuning PYTHIA 8.1: the Monash 2013 tune , 2014, 1404.5630.

[59]  C. Pollard,et al.  QCD-aware partonic jet clustering for truth-jet flavour labelling , 2015, 1507.00508.

[60]  Hui Luo,et al.  Quark jet versus gluon jet: deep neural networks with high-level features , 2017, 1712.03634.

[61]  Bingqing Li,et al.  A Class of New Metrics Based on Triangular Discrimination , 2015, Inf..

[62]  W. Marsden.  I and J , 2012 .

[63]  S. Marzani,et al.  Sudakov Safety in Perturbative QCD , 2015, 1502.01719.

[64]  G. Parisi,et al.  Asymptotic Freedom in Parton Language , 1977 .

[65]  Flemming Topsøe,et al.  Some inequalities for information divergence and related measures of discrimination , 2000, IEEE Trans. Inf. Theory.

[66]  Taoli Cheng,et al.  Recursive Neural Networks in Quark/Gluon Tagging , 2017, Computing and Software for Big Science.

[67]  Peter Skands,et al.  A brief introduction to PYTHIA 8.1 , 2007, Comput. Phys. Commun..

[68]  J. T. Childers,et al.  Measurement of colour flow with the jet pull angle in tt¯ events using the ATLAS detector at √s = 8 TeV , 2015 .

[69]  Gavin P. Salam,et al.  Non-perturbative QCD effects in jets at hadron colliders , 2007, 0712.3014.

[70]  Johannes Bellm,et al.  Herwig 7.0/Herwig++ 3.0 release note , 2015, 1512.01178.

[71]  P. Alam.  ‘S’ , 2021, Composites Engineering: An A–Z Guide.

[72]  V. M. Ghete,et al.  Electroweak production of two jets in association with a Z boson in proton–proton collisions at $$\sqrt{s}= $$s= 13$$\,\text {TeV}$$TeV , 2017, The European Physical Journal C.

[73]  Manuel Robbins,et al.  Seeing in Color , 1983 .

[74]  Patrick T. Komiske,et al.  Learning to classify from impure samples with high-dimensional data , 2018, Physical Review D.

[75]  S. M. Etesami,et al.  Search for the standard model Higgs boson produced through vector boson fusion and decaying to bb , 2015 .

[76]  V. M. Ghete,et al.  Search for a Higgs boson in the decay channel H → ZZ(*) → q$ \overline {\text{q}} $ℓ−ℓ+ in pp collisions at $ \sqrt {s} = 7 $TeV , 2012 .