Related papers: Dynamic Radius Jet Clustering Algorithm
We discuss non-perturbative QCD contributions to jet observables, computing their dependence on the jet radius R, and on the colour and transverse momentum of the parton initiating the jet. We show, using analytic QCD models of power…
Jet substructure is typically studied using clustering algorithms, such as kT, which arrange the jets' constituents into trees. Instead of considering a single tree per jet, we propose that multiple trees should be considered, weighted by…
We introduce a new jet clustering algorithm named SIFT (Scale-Invariant Filtered Tree) that maintains the resolution of substructure for collimated decay products at large boosts. The scale-invariant measure combines properties of kT and…
The advent of high-energy hadron colliders necessitates efficient and accurate computation of multi-jet production processes, both as QCD processes in their own right and as backgrounds for other physics. The algorithm that performs these…
We propose a modified definition of the jet charge, the "dynamic jet charge", where the constant jet momentum fraction weighting parameter, $\kappa$, in the standard jet charge definition is generalized to be a function of a dynamical…
Subjet distributions were measured in neutral current deep inelastic ep scattering with the ZEUS detector at HERA using an integrated luminosity of 81.7 pb-1. Jets were identified using the kT cluster algorithm in the laboratory frame.…
We propose a method to organize experimental data from particle collision experiments in a general format which can enable a simple visualisation and effective classification of collision data using machine learning techniques. The method…
In the present contribution we introduce a strategy to quantify the performance of modern infrared and collinear safe jet clustering algorithms in processes which involve the reconstruction of heavy object decays. We determine optimal…
Identifying the origin of high-energy hadronic jets ('jet tagging') has been a critical benchmark problem for machine learning in particle physics. Jets are ubiquitous at colliders and are complex objects that serve as prototypical examples…
Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images. In this work, we present a novel class of recursive neural networks built instead upon an analogy between QCD and…
Results from a model study on the formation of exotic quark clusters at the hadronization stage of a heavy ion collision are presented. The dynamical quark molecular dynamics (qMD) model which is used is sketched, and results for exotica…
The observation of jets in a variety of hard-scattering processes has allowed the quantitative study of perturbative quantum chromodynamics (PQCD) by comparing detailed theoretical predictions with a wide range of experimental data. This…
In the past years significant progress has been made toward achieving a quantitative understanding of jets and their substructure in high-energy proton-proton collisions from first principles in QCD. Precise measurements have become…
The working group on jets and high-Et phenomena of the Future physics at HERA Workshop studied subjects ranging from next-to-leading order (NLO) corrections in deeply inelastic scattering (DIS) and photoproduction with the corresponding…
Jet reconstruction remains a critical task in the analysis of data from HEP colliders. We describe in this paper a new, highly performant, Julia package for jet reconstruction, JetReconstruction.jl, which integrates into the growing…
Machine Learning algorithms have played an important role in hadronic jet classification problems. The large variety of models applied to Large Hadron Collider data has demonstrated that there is still room for improvement. In this context…
Jets are expected to play a prominent role in the ongoing efforts to characterize the hot and dense QCD medium created in ultrarelativistic heavy ion collisions. The success of this program depends crucially on the existence of a full…
A novel method is proposed here to precisely model the multi-dimensional features of QCD multi-jet events in hadron collisions. The method relies on the schematization of high-pT QCD processes as 2->2 reactions made complex by sub-leading…
Embedding symmetries in the architectures of deep neural networks can improve classification and network convergence in the context of jet substructure. These results hint at the existence of symmetries in jet energy depositions, such as…
Next-to-leading order corrections to jet cross sections in deep inelastic scattering at HERA are studied. The predicted jet rates allow for a precise determination of $\alpha_s(\mu_R)$ at HERA over a wide range of $\mu_R$. We argue, that…