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Subtraction of the large background in reconstruction is a key ingredient in jet studies in high-energy heavy-ion collisions at RHIC and the LHC. Here we address the question to which extent the most commonly used subtraction techniques are…

High Energy Physics - Phenomenology · Physics 2015-06-12 Liliana Apolinário , Néstor Armesto , Leticia Cunqueiro

We examine the problem of jet reconstruction at heavy-ion colliders using jet-area-based background subtraction tools as provided by FastJet. We use Monte Carlo simulations with and without quenching to study the performance of several jet…

High Energy Physics - Phenomenology · Physics 2011-02-11 Matteo Cacciari , Juan Rojo , Gavin P. Salam , Gregory Soyez

Measurements of jet substructure in ultra-relativistic heavy-ion collisions indicate that interactions with the quark-gluon plasma quench the jet showering process. Modern data-driven methods have shown promise in probing these…

High Energy Physics - Phenomenology · Physics 2024-12-02 Umar Sohail Qureshi , Raghav Kunnawalkam Elayavalli

We present an analysis of the role that the quark-gluon plasma (QGP) resolution length, the minimal distance by which two nearby colored charges in a jet must be separated such that they engage with the plasma independently, plays in…

High Energy Physics - Phenomenology · Physics 2020-02-19 J. Casalderrey-Solana , G. Milhano , D. Pablos , K. Rajagopal

We present a new model for jet quenching in a quark gluon plasma (QGP). The jet energy loss has two steps. The initial jet parton with a high virtuality loses energy by a perturbative vacuum parton shower modified by medium interactions…

High Energy Physics - Phenomenology · Physics 2025-02-27 Iurii Karpenko , Alexander Lind , Martin Rohrmoser , Joerg Aichelin , Pol-Bernard Gossiaux

Jets serve as powerful tomographic probes of the quark-gluon plasma (QGP) created in relativistic heavy-ion collisions. While the expanding landscape of jet observables reveals multi-faceted aspects of jet-medium interactions, a precise and…

Nuclear Theory · Physics 2026-02-12 Yichao Dang , Wen-Jing Xing , Shanshan Cao , Guang-You Qin

Machine learning, particularly deep neural networks, has been widely used in high-energy physics, demonstrating remarkable results in various applications. Furthermore, the extension of machine learning to quantum computers has given rise…

High Energy Physics - Phenomenology · Physics 2025-01-23 Yi-An Chen , Kai-Feng Chen

A modification of the internal structure of jets is expected due to the production of a dense QCD medium, the Quark Gluon Plasma, in heavy-ion collisions. We discuss some aspects of jet reconstruction in p+p and A+A collisions and emphasize…

Nuclear Experiment · Physics 2009-10-15 M. Estienne

The precise reconstruction of jet transverse momenta in heavy-ion collisions is a challenging task. A major obstacle is the large number of uncorrelated (mainly) low-$p_\mathrm{T}$ particles overlaying the jets. Strong region-to-region…

Nuclear Experiment · Physics 2019-09-05 Rüdiger Haake

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…

Nuclear Experiment · Physics 2019-08-13 Sevil Salur

The task of reconstructing particles from low-level detector response data to predict the set of final state particles in collision events represents a set-to-set prediction task requiring the use of multiple features and their correlations…

We discuss jet substructure in recombination algorithms for QCD jets and single jets from heavy particle decays. We demonstrate that the jet algorithm can introduce significant systematic effects into the substructure. By characterizing…

High Energy Physics - Phenomenology · Physics 2014-11-20 Stephen D. Ellis , Christopher K. Vermilion , Jonathan R. Walsh

We study, in a pQCD calculation augmented by nuclear effects, the jet energy loss needed to reproduce the pi^0 spectra in Au+Au collisions at large p_T, measured by PHENIX at RHIC. The transverse width of the parton momentum distributions…

High Energy Physics - Phenomenology · Physics 2007-05-23 G. Fai , G. G. Barnafoldi , M. Gyulassy , P. Levai , G. Papp , I. Vitev , Y. Zhang

Recently, interest in quantum computing has significantly increased, driven by its potential advantages over classical techniques. Quantum machine learning (QML) exemplifies one of the important quantum computing applications that are…

Jets produced by the initial hard scattering in heavy ion collision events lose energy due to interactions with the color-deconfined medium formed around them: the quark-gluon plasma (QGP). Jet-medium interactions constitute an important…

High Energy Physics - Phenomenology · Physics 2023-03-17 Shuzhe Shi , Rouzbeh Modarresi Yazdi , Charles Gale , Sangyong Jeon

We study the impact of selection biases on jet structure and substructure observables and separate these effects from effects caused by jet quenching. We use the angular separation $\Delta R$ of the hardest splitting in a jet as the primary…

High Energy Physics - Phenomenology · Physics 2022-03-09 Jasmine Brewer , Quinn Brodsky , Krishna Rajagopal

We compare the performance of a convolutional neural network (CNN) trained on jet images with dense neural networks (DNNs) trained on n-subjettiness variables to study the distinguishing power of these two separate techniques applied to top…

High Energy Physics - Phenomenology · Physics 2019-09-25 Liam Moore , Karl Nordström , Sreedevi Varma , Malcolm Fairbairn

The modification of hard jets in the Quark Gluon Plasma (QGP) is studied using the MATTER event generator. Based on the higher twist formalism of energy loss, the MATTER event generator simulates the evolution of highly virtual partons…

Nuclear Theory · Physics 2017-02-24 Michael Kordell , Abhijit Majumder

In the particle-flow approach information from all available sub-detector systems is combined to reconstruct all stable particles. The global event reconstruction has been shown to improve, in particular, the resolution of jet energy and…

Nuclear Experiment · Physics 2019-08-13 Matthew Nguyen

Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images. In this work, we present a novel class of recursive neural networks built instead upon an analogy between QCD and…

High Energy Physics - Phenomenology · Physics 2020-02-25 Gilles Louppe , Kyunghyun Cho , Cyril Becot , Kyle Cranmer