Abstract
New jet observables are defined which characterize both fractal and scale-dependent contributions to the distribution of hadrons in a jet. These infrared safe observables, named Extended Fractal Observables (EFOs), have been applied to quark–gluon discrimination to demonstrate their potential utility. The EFOs are found to be individually discriminating and only weakly correlated to variables used in existing discriminators. Consequently, their inclusion improves discriminator performance, as here demonstrated with particle level simulation from the parton shower.
Highlights
A hadronic jet is produced from an initial parton via a sequence of perturbative QCD branching interactions, followed by the non-perturbative conversion of partons to the hadrons we observe in experiments
A Markov chain description of the parton shower suggests the spatial distribution of partons will exhibit some fractal character [1,2,3,4,5,6], and this will be inherited by the final hadron distribution
3 Performance in Quark–Gluon discrimination. We investigate whether these observables might be a useful new tool in the important and challenging problem of distinguishing light quarks from gluon jets
Summary
A hadronic jet is produced from an initial parton via a sequence of perturbative QCD branching interactions (the parton shower), followed by the non-perturbative conversion of partons to the hadrons we observe in experiments (hadronization). We would like to demonstrate the use of such observables in the discrimination of quark and gluon jets. Our construction of pixel-based jet observables resonates with the recent development of the jet image paradigm [25,26], in which the energy measured in each detector cell is interpreted as the intensity of a pixel in a 2D image. Within this approach, powerful machine-learning algorithms for classifying images have been brought to bear on a range of jet classification problems.
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