Related papers: Pileup Subtraction and Jet Energy Prediction Using…
We present next-to-leading order QCD predictions for single-inclusive and di-jet observables, relevant to the collisions of two on-shell photons, obtained with a recently completed computation based upon the subtraction method. We compare…
A key question for machine learning approaches in particle physics is how to best represent and learn from collider events. As an event is intrinsically a variable-length unordered set of particles, we build upon recent machine learning…
The striking suppression and modification patterns that are observed in jet observables measured in heavy-ion collisions with respect to the proton-proton baseline have the potential to constrain the spatio-temporal branching process of…
Hard scattered partons are predicted to be well calibrated probes of the hot and dense medium produced in heavy ion collisions. Interactions of these partons with the medium w ill result in modifications of internal jet structure in Au+Au…
A strong enhancement of deuteron production in jets has been recently observed in proton-proton collisions at LHC. We show that the effect is due to two independent factors: a collimation of jet nucleons and a smallness of nucleon source…
We study the suppressions of high transverse momentum single hadron and dihadron productions in high-energy heavy-ion collisions based on the framework of a next-to-leading-order perturbative QCD parton model combined with the higher-twist…
First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range…
Jet-matter interaction remains a central question and a theoretical challenge in heavy-ion physics and might become important in high-multiplicity events in proton-proton collisions at LHC energies. Full jet measurement at LHC offer the…
The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of…
The suppression of single inclusive hadron spectra in heavy-ion collision as compared to the scaled expectation from proton-proton collisions has long been regarded as an interesting tool to study properties of the bulk matter in heavy-ion…
Full jet reconstruction in heavy-ion collisions is expected to provide more sensitive measurements of jet quenching in hot QCD matter at RHIC. In this paper we review recent studies of jets utilizing modern jet reconstruction algorithms and…
The ALICE Collaboration reports a search for jet quenching effects in high-multiplicity (HM) proton$-$proton collisions at $\sqrt{s}$ = 13 TeV, using the semi-inclusive azimuthal-difference distribution $\Delta\varphi$ of charged-particle…
Jet quenching in heavy-ion collisions probes parton energy loss in the quark--gluon plasma (QGP), but the extracted transport properties may not be universally constrained across centrality, beam energy, and observable class. In this work,…
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require…
One- and two-jet inclusive quantities in hadron collisions have already been calculated to next-to-leading order accuracy, using both the subtraction and the cone method. Since the one-loop corrections have recently been obtained for all…
The classification of events involving jets as signal-like or background-like can depend strongly on the jet algorithm used and its parameters. This is partly due to the fact that standard jet algorithms yield a single partition of the…
Machine-learning (ML) techniques are explored to identify and classify hadronic decays of highly Lorentz-boosted W/Z/Higgs bosons and top quarks. Techniques without ML have also been evaluated and are included for comparison. The…
We build a deep neural network based on the Mask R-CNN framework to detect the Higgs jets and top quark jets in any event image. We propose an algorithm to assign the top quark final states at the ground truth level so that the network can…
Interactions of high momentum partons with Quark-Gluon Plasma created in relativistic heavy-ion collisions provide an excellent tomography tool for this new form of matter. Recent measurements for charged hadrons and unidentified jets at…
Jets at high energy colliders are complicated objects to identify. Even if jets are widely separated, there is no reason for jets to have the same size. A single reconstruction, or interpretation, of each event can only extract a limited…