Related papers: Exploring an image-based $b$-jet tagging method us…
The flavor dependence of jet quenching is a powerful handle to discriminate between models of parton energy loss in heavy-ion collisions. We demonstrate the capacity of CMS to identify jets initiated by bottom quarks using displaced…
We summarize measurements of b and c jet production at the LHC, which are an important signature and background for decays of massive particles such as H-to-b-bbar. These include measurements of the inclusive and dijet production of heavy…
We present a reanalysis of archived data from the ALEPH experiment at LEP in the $\mathrm{Z \to q\bar{q}}$ final state. We apply modern jet flavour tagging techniques to improve the separation between the different hadronic decay channels…
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 products of W bosons produced with high transverse momenta…
We study the efficiency of a neural-net filter and deconvolution method for estimating jet energies and spectra in high-background reactions such as nuclear collisions at the relativistic heavy-ion collider and the large hadron collider.…
Collisions of heavy ion nuclei at relativistic speeds (close to the speed of light) creates a high temperature and very dense form of matter, now known to consist of de-confined quarks and gluons, named the quark gluon plasma (QGP). In this…
We develop taggers for multi-pronged jets that are simple functions of jet substructure (so-called `subjettiness') variables. These taggers can be approximately decorrelated from the jet mass in a quite simple way. Specifically, we use a…
Charged-hadron distributions in heavy-flavor jets are measured in proton-proton collisions at a center-of-mass energy of $\sqrt{s}$ = 13 TeV collected by the LHCb experiment. Distributions of the longitudinal momentum fraction, transverse…
We present a detailed examination of the heavy flavor properties of jets produced at the Fermilab Tevatron collider. The data set, collected with the Collider Detector at Fermilab, consists of events with two or more jets with transverse…
Multijet events with heavy-flavors are of central importance at the LHC since many relevant processes -- such as $t\bar t$, $hh$, $t\bar t h$ and others -- have a preferred branching ratio for this final state. Current techniques for…
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…
Different types of high energy hard probes are used to extract the jet transport properties of the Quark-Gluon Plasma created in heavy-ion collisions, of which the heavy boson tagged jets are undoubtedly the most sophisticated due to its…
Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially…
Attention-based transformer models have become increasingly prevalent in collider analysis, offering enhanced performance for tasks such as jet tagging. However, they are computationally intensive and require substantial data for training.…
We study the prospects for probing the quark content of the photon using b tagging at high energy electron-photon colliders. We find that heavy quark tagging provides a sensitive and effective probe of the quark content of the photon. Using…
We study the tagging of Higgs exotic decay signals using different types of deep neural networks (DNNs), focusing on the $W^\pm h$ associated production channel followed by Higgs decaying into $n$ $b$-quarks with $n=4$, 6 and 8. All the…
Deep inelastic scattering on nuclei at the Electron-Ion Collider will open new opportunities to investigate the structure of matter. Heavy flavor-tagged jets are complementary probes of the partonic composition and transport coefficients of…
The identification and classification of collimated particle sprays, or jets, are essential for interpreting data from high-energy collider experiments. While deep learning has improved jet classification, it often lacks interpretability.…
The ubiquity of top-rich final states in the context of beyond the Standard Model (BSM) searches has led to their status as extensively studied signatures at the LHC. Over the past decade, numerous endeavours have been undertaken in the…
A novel deep neural network classifier, a ``Particle transformer'' (PaRT), is introduced for the identification of highly Lorentz-boosted resonances reconstructed as single, multipronged jets in measurements and searches performed by the…