Related papers: Jet Flavour Tagging for Future Colliders with Fast…
Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. To establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark…
Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this…
The goals of discovering quantum radiation dynamics in high-intensity laser-plasma interactions and engineering new laser-driven high-energy particle sources both require accurate and robust predictions. Experiments rely on particle-in-cell…
Standard jet finding techniques used in elementary particle collisions have not been successful in the high track density of heavy-ion collisions. This paper describes a modified cone-type jet finding algorithm developed for the complex…
Tracker detectors can be used to identify charged particles based on their global chi value obtained during track fitting with the Kalman filter. This approach builds upon the knowledge of detector material and local position resolution,…
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…
Deep learning techniques have the power to identify the degree of modification of high energy jets traversing deconfined QCD matter on a jet-by-jet basis. Such knowledge allows us to study jets based on their initial, rather than final…
The new CDFII detector incorporates a Time-of-Flight detector (TOF), employing plastic scintillator bars and fine-mesh photomultipliers. Since August 2001 the TOF system has been fully instrumented and integrated into the CDFII data…
A new Monte Carlo model of jet quenching in nuclear collisions, CUJET1.0, is applied to predict the jet flavor dependence of the nuclear modification factor for fragments {\it $f=\pi,D,B,e^-$} from quenched jet flavors {\it $g,u,c,b$} in…
We introduce an infinite set of jet substructure observables, derived as projections of $N$-point energy correlators, that are both convenient for experimental studies and maintain remarkable analytic properties derived from their…
We present a tool to compute the sensitivity of the Future Circular Electron--Positron Collider (FCC-ee) to the interactions of new, heavy particles via publicly available extensions to the smelli and flavio computer programs. We…
The ECCE detector has been recommended as the selected reference detector for the future Electron-Ion Collider (EIC). A series of simulation studies have been carried out to validate the physics feasibility of the ECCE detector. In this…
We propose an algorithm, deployable on a highly-parallelized graph computing architecture, to perform rapid reconstruction of charged-particle trajectories in the high energy collisions at the Large Hadron Collider and future colliders. We…
In particle physics experiments, identifying the types of particles registered in a detector is essential for the accurate reconstruction of particle collisions. At Thomas Jefferson National Accelerator Facility (Jefferson Lab), the GlueX…
This talk reviews some key developments that have taken place in hadron-collider jet finding over the past couple of years, including: technical advances such as the complete formulation of an infrared safe seedless cone algorithm and fast…
In this contribution the status of the flavour tagging performance for the LDCPrime detector model and studies of the track selection parameters and effects from beam backgrounds in flavour tagging using the LCFIVertex package are…
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.…
In collider physics, jet algorithms are a ubiquitous tool for clustering particles into discrete jet objects. Event shapes offer an alternative way to characterize jets, and one can define a jet multiplicity event shape, which can take on…
We present JetFormer, a versatile and scalable encoder-only Transformer architecture for particle jet tagging at the Large Hadron Collider (LHC). Unlike prior approaches that are often tailored to specific deployment regimes, JetFormer is…
The proposed high-energy and high-luminosity Electron-Ion Collider (EIC) will provide one of the cleanest environments to precisely determine the nuclear parton distribution functions (nPDFs) in a wide $x$-$Q^{2}$ range. Heavy flavor…