Related papers: Fuzzy Jets
We address the issues of clustering and non-global logarithms for jet shapes in the process of production of a Higgs/vector boson associated with a single hard jet at hadron colliders. We perform an analytical fixed-order calculation up to…
We present a machine learning (ML) method to calibrate hadronic jet energy in real-time trigger systems of the High-Luminosity Large Hadron Collider (HL-LHC) using an efficient implementation on field programmable gate arrays (FPGA).…
Recent experiments have observed large anisotropic collective flows in high multiplicity proton-lead collisions at the Large Hadron Collider (LHC), which indicates the possible formation of mini quark-gluon plasma (QGP) in small collision…
Precise measurements of the energy of jets emerging from particle collisions at the LHC are essential for a vast majority of physics searches at the CMS experiment. In this study, we leverage well-established deep learning models for point…
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…
We introduce a search technique that is sensitive to a broad class of signals with large final state multiplicities. Events are clustered into large radius jets and jet substructure techniques are used to count the number of subjets within…
Hard processes in collider experiments typically produce QCD jets, which have long served as precision tests of QCD in the vacuum. More recently, heavy-ion programs at RHIC and the LHC have offered a novel perspective on jets, establishing…
Underexpanded jets are present in various engineering applications; in recent years, they have gained special attention because of the development of gas-fueled propulsion systems. In these apparatuses, the direct injection of fuels such as…
Cluster analysis which focuses on the grouping and categorization of similar elements is widely used in various fields of research. Inspired by the phenomenon of atomic fission, a novel density-based clustering algorithm is proposed in this…
In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with transformers which are well suited to the task of generating…
We reframe common tasks in jet physics in probabilistic terms, including jet reconstruction, Monte Carlo tuning, matrix element - parton shower matching for large jet multiplicity, and efficient event generation of jets in complex,…
We study high-pt jets from QCD and from highly-boosted massive particles such as tops, W, Z and Higgs, and argue that infrared-safe observables can help reduce QCD backgrounds. Jets from QCD are characterized by different patterns of energy…
Image-based jet analysis is built upon the jet image representation of jets that enables a direct connection between high energy physics and the fields of computer vision and deep learning. Through this connection, a wide array of new jet…
Previous experimental studies have shown that when a layer of solid particles is explosively dispersed, the particles often develop a non-uniform spatial distribution. The instabilities within the particle bed and at the particle layer…
We review selected results from a recent in-depth study of jet shapes and jet cross sections in ultra-relativistic reactions with heavy nuclei at the LHC arXiv:0810.2807 [hep-ph]. We demonstrate that at the highest collider energies these…
Head-on collisions between nuclei of different size at Fermi energies may give rise to extremely deformed dynamical regimes and patterns. Those latter, may suddenly turn into a stream of nuclear clusters, resembling collimated jets. Because…
The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on…
Even though jet substructure was not an original design consideration for the Large Hadron Collider (LHC) experiments, it has emerged as an essential tool for the current physics program. We examine the role of jet substructure on the…
Modern machine learning techniques, such as convolutional, recurrent and recursive neural networks, have shown promise for jet substructure at the Large Hadron Collider. For example, they have demonstrated effectiveness at boosted top or W…
The theoretical description of the physics of multi-jets in hadronic collisions at high energies is based on "merging" methods, which combine short-timescale production of jets with long-timescale evolution of partonic showers. We point out…