相关论文: CNN-Based Online Trigger for QGP Event Selection

I develop and apply a Bayesian method for quantitatively estimating properties of the quark-gluon plasma (QGP), an extremely hot and dense state of fluid-like matter created in relativistic heavy-ion collisions. The QGP cannot be directly…

Jets of collimated particles serve a multitude of purposes in high energy collisions. Recently, studies of jet interaction with the quark-gluon plasma (QGP) created in high energy heavy ion collisions are of growing interest, particularly…

Convolutional Neural Networks are extensively used in a wide range of applications, commonly including computer vision tasks like image and video classification, recognition, and segmentation. Recent research results demonstrate that…

It has been theorized that if heavy nuclei (e.g. Au, Pb) are collided at sufficiently high energies, we might be to recreate the conditions that existed in the universe a few microseconds after the Big Bang. The kinetic energy of the…

An introduction to dynamical microscopic models of hadronic and nuclear interactions is presented. Special emphasis is put in the relation between multiparticle production and total cross-section contributions. In heavy ion collisions, some…

Quantum Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classical Graph Neural Networks (GNNs) are scalable and robust, existing QGNNs often lack…

We present a theory-informed reinforcement-learning framework that recasts the combinatorial assignment of final-state particles in hadron collider events as a Markov decision process. A transformer-based Deep Q-Network, rewarded at each…

Deep learning based on Convolutional Neural Network (CNN) has shown promising results in various vision-based applications, recently also in camera-based vital signs monitoring. The CNN-based Photoplethysmography (PPG) extraction has, so…

The classification of jets as quark- versus gluon-initiated is an important yet challenging task in the analysis of data from high-energy particle collisions and in the search for physics beyond the Standard Model. The recent integration of…

Understanding the properties of the quark-gluon plasma (QGP) that is produced in ultra-relativistic nucleus-nucleus collisions has been one of the top priorities of the heavy ion program at the LHC. Energetic jets are produced and…

We apply a well tested hybrid transport model, which couples viscous hydrodynamics to a hadronic afterburner, to describe bulk observables in proton-lead and lead-lead collisions at $\sqrt{s_{NN}}=5.02$ TeV. The quark-gluon plasma (QGP)…

Accurate classification of brain tumors from MRI scans is critical for effective treatment planning. This study presents a Hybrid Quantum Convolutional Neural Network (HQCNN) that integrates quantum feature-encoding circuits with depth-wise…

Ultra-peripheral heavy-ion collisions (UPCs) provide a distinct environment for high-energy QCD research, focusing on the production of vector mesons. This proceeding details recent advancements in the Sar$t$re Monte Carlo event generator,…

We present a fast simulation application based on a Deep Neural Network, designed to create large analysis-specific datasets. Taking as an example the generation of W+jet events produced in sqrt(s)= 13 TeV proton-proton collisions, we train…

Experimental probes of the Quark-Gluon Plasma (QGP) generated in heavy-ion collisions span a broad range in momentum scale: low transverse momentum (low $p_T$) measurements probe collective dynamics, while high $p_T$ measurements probe the…

One of the latest trends in the advancement of experimental high-energy physics is to identify the quark gluon plasma (QGP) predicted qualitatively by quantum chromodynamics (QCD). We discuss whether nuclear transparency effect which is…

Ultrarelativistic heavy ion collisions recreate in the laboratory the thermodynamical conditions prevailing in the early universe up to 10$^{-6}$ seconds, thereby allowing the study of the quark-gluon plasma (QGP), a state of quantum…

Wearable health devices have a strong demand in real-time biomedical signal processing. However traditional methods often require data transmission to centralized processing unit with substantial computational resources after collecting it…

Due to a high rate of overall data generation relative to data generation of interest, the CMS experiment at the Large Hadron Collider uses a combination of hardware- and software-based triggers to select data for capture. Accurate momentum…

The hydrodynamic (hydro) model has been extensively applied to heavy ion data from the relativistic heavy ion collider (RHIC). Results are interpreted to conclude that a dense QCD medium nearly opaque to most partons, a strongly-coupled…