Related papers: Machine Learning-Based b-Jet Tagging in pp Collisi…
Recently machine learning algorithms based on deep layered artificial neural networks (DNNs) have been applied to a wide variety of high energy physics problems such as jet tagging or event classification. We explore a simple but effective…
The production of $\Lambda$ baryons and ${\rm K}^{0}_{\rm S}$ mesons (${\rm V}^{0}$ particles) was measured in p-Pb collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV and pp collisions at $\sqrt{s} = 7$ TeV with ALICE at the LHC. The production…
Nowadays, there has been a growing trend in the field of high-energy physics (HEP), in both its experimental and phenomenological studies, to incorporate machine learning (ML) and its specialized branch, deep learning (DL). This review…
A new algorithm for jet finding in hadronic collisions is presented. The algorithm, based on a Gaussian filter in $(\eta,\phi)$, is specifically intended for use in heavy ion collisions and/or for detectors with limited acceptance. The…
Large transverse momentum jets provide unique tools to study dense QCD matter in high-energy heavy-ion collisions. Results from RHIC on suppression of high transverse momentum particles in Au+Au collisions indicate a significant energy loss…
Jets are collimated sprays of particles produced from the fragmentation and hadronization of hard-scattered partons in high energy hadronic and nuclear collisions. Jet properties are sensitive to details of parton showering processes and…
Understanding the inner working of the quark-gluon plasma requires complete and precise jet substructure studies in heavy ion collisions. In this proceeding we discuss the use of quark and gluon jets as independent probes, and how their…
This paper presents the application of a variety of techniques to study jet substructure. The performance of various modified jet algorithms, or jet grooming techniques, for several jet types and event topologies is investigated for jets…
Central lead-lead collisions at the LHC energies may pose a particular challenge for jet identification as multiple jets are produced per each collision event. We simulate the jet evolution in central Pb-Pb events at $\sqrt{s_{\rm NN}} =…
The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a…
The per-event yield of the highest transverse momentum charged particle and charged-particle jet, integrated above a given pt(min) threshold starting at pt(min) = 0.8 and 1 GeV, respectively, is studied in pp collisions at sqrt(s) = 8 TeV.…
Jet charge is an estimator of the electric charge of a quark, antiquark, or gluon initiating a jet. It is based on the momentum-weighted sum of the electric charges of the jet constituents. Measurements of three charge observables of the…
A search for heavy resonances decaying into a Higgs boson (H) or a Z boson and a photon ($\gamma$), with the H or Z bosons decaying to a bottom quark-antiquark pair ($\mathrm{b\bar{b}}$) is presented. The analysis is performed using…
We report measurements of two jet shapes, the ratio of 2-Subjettiness to 1-Subjettiness ($\it{\tau_{2}}/\it{\tau_{1}}$) and the opening angle between the two axes of the 2-Subjettiness jet shape, which is obtained by reclustering the jet…
New particles at the TeV scale can decay hadronically with strongly collimated jets, thus the standard reconstruction methods based on invariant-masses of well-separated jets can fail. We discuss how to identify such particles in pp…
A deep-learning approach based on the transformer architecture is developed to distinguish between jets originating from quarks and gluons. The algorithm operates on jets with transverse momentum $p_{\text{T}} > 20$ and pseudorapidity…
We present a measurement of b jet transverse momentum (pt) spectra in proton-lead (pPb) collisions using a dataset corresponding to about 35 inverse nanobarns collected with the CMS detector at the LHC. Jets from b quark fragmentation are…
A significant challenge in the tagging of boosted objects via machine-learning technology is the prohibitive computational cost associated with training sophisticated models. Nevertheless, the universality of QCD suggests that a large…
With deep learning techniques, the degree of modification of energetic jets that traversed hot QCD medium can be identified on a jet-by-jet basis. Due to the strong correlations between the degree of jet modification and its traversed…
We study the performance of the Particle Transformer (ParT) for jet flavor tagging using ILD full simulation events (1M jets) as well as fast simulation samples (10M and 1M jets). We perform 3-category ($b/c/d$), 6-category ($b/c/d/u/s/g$),…