At the CERN LHC [1], an efficient classification of hadronic decays of heavy standard-model
(SM) particles (objects) that are reconstructed within a single jet would provide a significant …

In searches for new physics in the energy regime of the LHC, it is becoming increasingly
important to distinguish single-jet objects that originate from the merging of the decay …

Over the past decade, a large number of jet substructure observables have been proposed
in the literature, and explored at the LHC experiments. Such observables attempt to utilize …

Recent literature on deep neural networks for tagging of highly energetic jets resulting from
top quark decays has focused on image based techniques or multivariate approaches using …

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks
and W bosons in pp collisions at ss= 13 TeV recorded by the ATLAS experiment at the Large …

A method is introduced for distinguishing top jets (boosted, hadronically decaying top
quarks) from light-quark and gluon jets using jet substructure. The procedure involves …

We describe the construction of novel end-to-end jet image classifiers to discriminate quark-
versus gluon-initiated jets using the simulated CMS Open Data. These multi-detector images …

Classification of jets as originating from light-flavor or heavy-flavor quarks is an important
task for inferring the nature of particles produced in high-energy collisions. The large and …

We apply techniques from Bayesian generative statistical modeling to uncover hidden
features in jet substructure observables that discriminate between different a priori unknown …

A bstract This paper presents the application of a variety of techniques to study jet
substructure. The performance of various modified jet algorithms, or jet grooming …