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Starting with a reminder of what is strongly coupled Quark-Gluon Plasma (sQGP), we proceed to recent advances in jet quenching and heavy quark diffusion, with a brief summary of various results based on AdS/CFT correspondence. The conical…

Nuclear Theory · Physics 2008-11-26 Edward Shuryak

The modification and amplification of the gluon angular distribution produced along with hard jets in nuclear collisions is computed. We consider the limit of a thin quark-gluon plasma, where the number of rescatterings of the jet and…

High Energy Physics - Phenomenology · Physics 2009-10-09 Miklos Gyulassy , Peter Levai , Ivan Vitev

Jet quenching is considered to be one of the signatures of the formation of quark gluon plasma. In order to investigate the jet quenching, it is necessary to detect jets produced in relativistic heavy ion collisions, determine their…

Nuclear Theory · Physics 2009-11-10 S. C. Phatak , P. K. Sahu

We present a simple model for the development of shear layers between parallel flows in confining channels. Such flows are important across a wide range of topics from diffusers, nozzles and ducts to urban air flow and geophysical fluid…

Fluid Dynamics · Physics 2018-04-09 GP Benham , AA Castrejon-Pita , IJ Hewitt , CP Please , RW Style , P Bird

We present here the first result on the three-loop gluon jet function in perturbative QCD. Using the three-loop coefficient functions [1,2] for deep-inelastic scattering via the exchange of a virtual photon that couples to quarks or a…

High Energy Physics - Phenomenology · Physics 2018-11-28 Pulak Banerjee , Prasanna K. Dhani , V. Ravindran

We introduce ImitationFlow, a novel Deep generative model that allows learning complex globally stable, stochastic, nonlinear dynamics. Our approach extends the Normalizing Flows framework to learn stable Stochastic Differential Equations.…

Machine Learning · Computer Science 2020-10-27 Julen Urain , Michelle Ginesi , Davide Tateo , Jan Peters

Normalizing flows are bijective mappings between inputs and latent representations with a fully factorized distribution. They are very attractive due to exact likelihood valuation and efficient sampling. However, their effective capacity is…

Machine Learning · Computer Science 2021-11-03 Matej Grcić , Ivan Grubišić , Siniša Šegvić

Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approach to efficiently explore the configuration space of…

Materials Science · Physics 2025-11-12 Xiaoshan Luo , Zhenyu Wang , Qingchang Wang , Jian Lv , Lei Wang , Yanchao Wang , Yanming Ma

Recent developments and results on the comparison of gluon to quark jets are discussed. A most important topic is the introduction of explicit energy scales of the jets. The scaling violation of the fragmentation function and the increase…

High Energy Physics - Experiment · Physics 2007-05-23 Klaus Hamacher

Many physics analyses at the LHC are looking into processes where the signal jets are originating from quarks, while jets in the background are more gluon enriched. Based on observables sensitive to fundamental differences in the…

High Energy Physics - Experiment · Physics 2019-08-13 Tom Cornelis

Normalizing flows are an established approach for modelling complex probability densities through invertible transformations from a base distribution. However, the accuracy with which the target distribution can be captured by the…

Machine Learning · Statistics 2024-02-02 Harry Bevins , Will Handley , Thomas Gessey-Jones

A method is introduced for distinguishing top jets (boosted, hadronically decaying top quarks) from light quark and gluon jets using jet substructure. The procedure involves parsing the jet cluster to resolve its subjets, and then imposing…

High Energy Physics - Phenomenology · Physics 2008-11-26 David E. Kaplan , Keith Rehermann , Matthew D. Schwartz , Brock Tweedie

Recently normalizing flows (NFs) have demonstrated state-of-the-art performance on modeling 3D point clouds while allowing sampling with arbitrary resolution at inference time. However, these flow-based models still require long training…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Janis Postels , Mengya Liu , Riccardo Spezialetti , Luc Van Gool , Federico Tombari

Normalizing flows are prominent deep generative models that provide tractable probability distributions and efficient density estimation. However, they are well known to fail while detecting Out-of-Distribution (OOD) inputs as they directly…

Machine Learning · Computer Science 2021-11-17 Nishant Kumar , Pia Hanfeld , Michael Hecht , Michael Bussmann , Stefan Gumhold , Nico Hoffmann

In this paper, we present a new proposal on how to measure quark/gluon jet properties at the LHC. The measurement strategy takes advantage of the fact that the LHC has collected data at different energies. Measurements at two or more…

High Energy Physics - Phenomenology · Physics 2023-12-07 Petr Baroň , Michael H. Seymour , Andrzej Siódmok

Normalizing flows can transform a simple prior probability distribution into a more complex target distribution. Here, we evaluate the ability and efficiency of generative machine learning methods to sample the Boltzmann distribution of an…

Soft Condensed Matter · Physics 2024-09-16 Gerhard Jung , Giulio Biroli , Ludovic Berthier

The semi-inclusive decay processes of a top quark into a charged pseudo-scalar meson and a jet are studied within the framework of QCD factorization. The leading power of the decay matrix elements can be factorized into heavy-to-light quark…

High Energy Physics - Phenomenology · Physics 2025-04-02 Long-Shun Lu , Lei-Yi Li , Cai-Dian Lü

Algorithms based on the particle flow approach are becoming increasingly utilized in collider experiments due to their superior jet energy and missing energy resolution compared to the traditional calorimeter-based measurements. Such…

High Energy Physics - Experiment · Physics 2015-03-20 Andrey Elagin , Pavel Murat , Alexandre Pranko , Alexei Safonov

The sensitivity of many physics analyses can be enhanced by constructing discriminants that preferentially select signal events. Such discriminants become much more useful if they are uncorrelated with a set of protected attributes. In this…

High Energy Physics - Phenomenology · Physics 2022-12-16 Samuel Klein , Tobias Golling

This article presents, for the first time, the application of diffusion models for generating jet images corresponding to proton-proton collision events at the Large Hadron Collider (LHC). The kinematic variables of quark, gluon, W-boson,…

High Energy Physics - Phenomenology · Physics 2025-08-04 Victor D. Martinez , Vidya Manian , Sudhir Malik
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