Generalized Fragmentation Functions for Fractal Jet Observables
arXiv:1704.05456 · doi:10.1007/JHEP06(2017)085
Abstract
We introduce a broad class of fractal jet observables that recursively probe the collective properties of hadrons produced in jet fragmentation. To describe these collinear-unsafe observables, we generalize the formalism of fragmentation functions, which are important objects in QCD for calculating cross sections involving identified final-state hadrons. Fragmentation functions are fundamentally nonperturbative, but have a calculable renormalization group evolution. Unlike ordinary fragmentation functions, generalized fragmentation functions exhibit nonlinear evolution, since fractal observables involve correlated subsets of hadrons within a jet. Some special cases of generalized fragmentation functions are reviewed, including jet charge and track functions. We then consider fractal jet observables that are based on hierarchical clustering trees, where the nonlinear evolution equations also exhibit tree-like structure at leading order. We develop a numeric code for performing this evolution and study its phenomenological implications. As an application, we present examples of fractal jet observables that are useful in discriminating quark jets from gluon jets.
37+18 pages, 24 figures
References in corpus (9)
- An Introduction to PYTHIA 8.2
- Boosted objects: a probe of beyond the Standard Model physics
- Deep learning in color: towards automated quark/gluon jet discrimination
- Gaining (Mutual) Information about Quark/Gluon Discrimination
- Parton Fragmentation within an Identified Jet at NNLL
- Resummation of Double-Differential Cross Sections and Fully-Unintegrated Parton Distribution Functions
- Experimental discrimination between charge 2e/3 top quark and charge 4e/3 exotic quark production scenarios
- Associated jet and subjet rates in light-quark and gluon jet discrimination
- Gluon- and Quark-Jet Multiplicities with NNNLO and NNLL Accuracy
Cited by in corpus (22)
- Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning
- Rethinking Jets with Energy Correlators: Tracks, Resummation and Analytic Continuation
- Energy flow polynomials: A complete linear basis for jet substructure
- Analyzing N-point Energy Correlators Inside Jets with CMS Open Data
- Casimir Meets Poisson: Improved Quark/Gluon Discrimination with Counting Observables
- A measurement of soft-drop jet observables in collisions with the ATLAS detector at TeV
- The Energy Distribution of Subjets and the Jet Shape
- Extending Precision Perturbative QCD with Track Functions
- The Hidden Geometry of Particle Collisions
- The Entropy of a Jet
- Jet angularity measurements for single inclusive jet production
- The soft drop groomed jet radius at NLL
- Properties of jet fragmentation using charged particles measured with the ATLAS detector in collisions at TeV
- Phenomenology with a recoil-free jet axis: TMD fragmentation and the jet shape
- Non-Gaussianities in Collider Energy Flux
- Leading jets and energy loss
- Understanding Jet Charge
- Dark Sector Glueballs at the LHC
- Probing hadronization with flavor correlations of leading particles in jets
- The leading jet transverse momentum in inclusive jet production and with a loose jet veto
- Aspects of Track-Assisted Mass
- Safe but Incalculable: Energy-weighting is not all you need