Related papers: Machine Learning-Based b-Jet Tagging in pp Collisi…
Deep neural networks trained for jet tagging are typically specific to a narrow range of transverse momenta or jet masses. Given the large phase space that the LHC is able to probe, the potential benefit of classifiers that are effective…
The multiplicity dependence of jet production in pp collisions at the centre-of-mass energy of $\sqrt{s} = 13\ \mathrm{TeV}$ is studied for the first time. Jets are reconstructed from charged particles using the anti-$k_\mathrm{T}$…
Jet point cloud images are high dimensional data structures that needs to be transformed to a separable feature space for machine learning algorithms to distinguish them with simple decision boundaries. In this article, the authors focus on…
We present a new scheme for tagging high-$p_{T}$ bottom and charm jets using energetic muons. Contemporary track-based $b$ tags lose their ability to reject light jet background as jet $p_{T}\rightarrow\mathcal{O}(\mathrm{TeV})$, where the…
The first measurement of jet shapes, defined as the fractional transverse momentum radial distribution, for inclusive jets produced in heavy-ion collisions is presented. Data samples of PbPb and pp collisions, corresponding to integrated…
Currently, newly developed artificial intelligence techniques, in particular convolutional neural networks, are being investigated for use in data-processing and classification of particle physics collider data. One such challenging task is…
Identification of hadronic jets originating from heavy-flavor quarks is extremely important to several physics analyses in High Energy Physics, such as studies of the properties of the top quark and the Higgs boson, and searches for new…
At the Relativistic Heavy Ion Collider, jets have been a useful tool to probe the properties of the hot, dense matter created. At the Large Hadron Collider, collisions of Pb+Pb at $\sqrt{s_{NN}}$ = 5.5 TeV will provide a large cross section…
The first results of single jet observables in Pb+Pb collisions at sqrt(s_NN)=2.76 TeV measured with the ATLAS detector at the LHC are presented. Full jets are reconstructed with the anti-kt algorithm with R= 0.2 and 0.4, using an…
The jet radial structure and particle transverse momentum ($p_{\rm{T}}$) composition within jets are presented in centrality-selected Pb-Pb collisions at $\sqrt{s_{\rm NN}}$ = 2.76 TeV. Track-based jets, which are also called charged jets,…
Jet measurements in heavy ion collisions can provide constraints on the properties of the quark gluon plasma, but the kinematic reach is limited by a large, fluctuating background. We present a novel application of symbolic regression to…
We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN Large Hadron Collider (LHC). Collision events produced at the LHC and represented as…
Jet tagging has become an essential tool for new physics searches at the high-energy frontier. For jets that contain energetic charged leptons we introduce Feature Extended Supervised Tagging (FEST) which, in addition to jet substructure,…
The production of a strongly interacting medium in heavy-ion collisions is identified through suppression of high transverse momentum jets leading to an effect known as jet quenching. Detailed measurements of nuclear modification factors…
Jet classification is an important ingredient in measurements and searches for new physics at particle coliders, and secondary vertex reconstruction is a key intermediate step in building powerful jet classifiers. We use a neural network to…
We apply both cut-based and machine learning techniques using the same inputs to the challenge of hadronic jet substructure recognition, utilizing classical subjettiness variables within the Delphes parameterized detector simulation…
Jets clustered from heavy ion collision measurements combine a dense background of particles with those actually resulting from a hard partonic scattering. The background contribution to jet transverse momentum ($p_{T}$) may be corrected by…
Deep learning techniques have shown the capability to identify the degree of energy loss of high-energy jets traversing hot QCD medium on a jet-by-jet basis. The average amount of quenching of quark and gluon jets in hot QCD medium actually…
We examine the problem of jet reconstruction at heavy-ion colliders using jet-area-based background subtraction tools as provided by FastJet. We use Monte Carlo simulations with and without quenching to study the performance of several jet…
This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, $H \rightarrow b\bar{b}$, for proton-proton collision data collected by the ATLAS detector at the Large…