Related papers: Fuzzy Jets
Clustering algorithms build jets though the iterative application of single particle and pairwise metrics. This leads to phase space constraints that are extremely complicated beyond the lowest orders in perturbation theory, and in practice…
The Large Hadron Collider, LHC, collides bunches of protons resulting in multiple interactions that occur practically simultaneously. This creates a pileup effect that distorts physics measurements due to the products of pileup collisions.…
Jet clustering is traditionally an unsupervised learning task because there is no unique way to associate hadronic final states with the quark and gluon degrees of freedom that generated them. However, for uncolored particles like $W$, $Z$,…
To precisely measure jets over a large background such as pile up in high luminosity p+p collisions at LHC, a new generation of jet reconstruction algorithms is developed. These algorithms are also applicable to reconstruct jets in the…
Experiments in the high-luminosity runs at the Large Hadron Collider face the challenges of very large pile-up. Primary techniques to deal with this are based on precise vertex and track reconstruction. Outside tracker acceptances, however,…
At the LHC, tagging boosted heavy particle resonances which decay hadronically, such as top quarks and Higgs bosons, can play an essential role in new physics searches. In events with high multiplicity, however, the standard approach to tag…
Jet finding is a type of optimization problem, where hadrons from a high-energy collision event are grouped into jets based on a clustering criterion. As three interesting examples, one can form a jet cluster that (1) optimizes the overall…
The Large Hadron Collider (LHC) is the first machine that provides high enough energy to produce large numbers of boosted top quarks. The decay products of these top quarks are confined to a cone in the top quark flight direction and can be…
We introduce a new class of event shapes to characterize the jet-like structure of an event. Like traditional event shapes, our observables are infrared/collinear safe and involve a sum over all hadrons in an event, but like a jet…
Minijets provide useful information on parton interactions in the low transverse-momentum (low-$p_T$) region. Because minijets produce clusters, we study the clustering properties of produced particles in high-energy $pp$ collisions as a…
A jet algorithm must specify how to (re-)combine different partons or towers into a single four-vector. Various recombination schemes have been used experimentally to examine the transverse energy profile of jets in hadron colliders.…
Jets are one of the most prominent physics signatures of high energy proton proton (p-p) collisions at the Large Hadron Collider (LHC). They are key physics objects for precision measurements and searches for new phenomena. This review…
This article presents, for the first time, the application of diffusion models for generating jet images corresponding to proton-proton collision events at the Large Hadron Collider (LHC). The kinematic variables of quark, gluon, W-boson,…
The CMS experiment makes use of a large variety of algorithms to identify the origin of particle jets measured in the detector. Through the study of jet substructure properties, jets originating from quarks, gluons, W/Z/Higgs bosons, top…
A jet algorithm based on the k-means clustering procedure is proposed which can be used for the invariant-mass reconstruction of heavy states decaying to hadronic jets. The proposed algorithm was tested by reconstructing E+ E- to ttbar to 6…
Quantum computing holds the promise of substantially speeding up computationally expensive tasks, such as solving optimization problems over a large number of elements. In high-energy collider physics, quantum-assisted algorithms might…
To maximise the potential for new measurements and discoveries at the LHC, the machine delivers as high as possible collision rates. As a consequence, multiple proton-proton collisions occur whenever two bunches cross. Interesting…
The conventional clustering algorithms have difficulties in handling the challenges posed by the collection of natural data which is often vague and uncertain. Fuzzy clustering methods have the potential to manage such situations…
I describe a class of iterative jet algorithms that are based on maximizing a fixed function of the total 4-momentum rather than clustering of pairs of jets. I describe some of the properties of the simplest examples of this class,…
We study the case where quantum computing could improve jet clustering by considering two new quantum algorithms that might speed up classical jet clustering algorithms. The first one is a quantum subroutine to compute a Minkowski-based…