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We compute resummed and matched predictions for jet angularities in hadronic dijet and Z+jet events with and without grooming the candidate jets using the SoftDrop technique. Our theoretical predictions also account for non-perturbative…

High Energy Physics - Phenomenology · Physics 2022-03-23 Daniel Reichelt , Simone Caletti , Oleh Fedkevych , Simone Marzani , Steffen Schumann , Gregory Soyez

In the present contribution we introduce a strategy to quantify the performance of modern infrared and collinear safe jet clustering algorithms in processes which involve the reconstruction of heavy object decays. We determine optimal…

High Energy Physics - Phenomenology · Physics 2008-06-25 Juan Rojo

We present data-driven methods for the full reconstruction of jets in heavy ion collisions, for inclusive and co-incidence jet measurements at both RHIC and LHC. The complex structure of heavy ion events generates a large background of…

High Energy Physics - Experiment · Physics 2012-10-05 G. O. V. de Barros , Bo Fenton-Olsen , Peter Jacobs , Mateusz Ploskon

The properties of quark and gluon jets depend on jet definitions and event selection. I discuss how these can be included in calculations and present jet definitions designed to give unbiased jets.

High Energy Physics - Phenomenology · Physics 2016-09-06 P. Eden

The measurement of jets recoiling from a trigger hadron in heavy-ion collisions can be used to understand the properties of the Quark Gluon Plasma. Jet-medium interactions cause jets to lose energy in the medium and may modify the jet…

High Energy Physics - Experiment · Physics 2019-01-10 Jaime Norman

A measurement of jet shapes in top-quark pair events using 1.8 fb(-1) of sqrt(s) = 7 TeV pp collision data recorded by the ATLAS detector at the LHC is presented. Samples of top-quark pair events are selected in both the single-lepton and…

High Energy Physics - Experiment · Physics 2013-12-23 ATLAS Collaboration

In recent years, the study of dihadron correlations has been one of the primary methods used to investigate the propagation and modification of hard-scattered partons through the QGP. Due to recent advances in jet-finding algorithms, it is…

Nuclear Experiment · Physics 2019-08-13 Alice Ohlson

Deep Learning approaches are becoming the go-to methods for data analysis in High Energy Physics (HEP). Nonetheless, most physics-inspired modern architectures are computationally inefficient and lack interpretability. This is especially…

Computational Physics · Physics 2023-01-31 Jose M Munoz , Ilyes Batatia , Christoph Ortner

Low-energy strong interactions are a major source of background at hadron colliders, and methods of subtracting the associated energy flow are well established in the field. Traditional approaches treat the contamination as diffuse, and…

Data Analysis, Statistics and Probability · Physics 2014-12-22 Federico Colecchia

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…

High Energy Physics - Phenomenology · Physics 2015-06-23 Yang-Ting Chien

Being able to distinguish parton pair type in a dijet event could significantly improve the search for new particles that are predicted by the theories beyond the Standard Model at the Large Hadron Collider. To explore whether parton pair…

High Energy Physics - Phenomenology · Physics 2014-10-31 Sertac Ozturk

Full jet reconstruction has traditionally been thought to be difficult in heavy ion events due to large multiplicity backgrounds. The search for new physics in high luminosity p+p collisions at the LHC similarly requires the precise…

Nuclear Experiment · Physics 2009-11-18 Sevil Salur

Jet substructure observables serve as essential tools for probing the quark-gluon plasma produced in relativistic heavy-ion collisions. Their interpretation, however, is often complicated by edge effects, which arise when correlated…

High Energy Physics - Phenomenology · Physics 2025-12-12 Carlota Andres , Jack Holguin , Benjamin Kimelman , Raghav Kunnawalkam Elayavalli , Jussi Viinikainen , Zhong Yang

We study multiple scatterings of jets on constituents of quark gluon plasma and introduce energy--energy correlations to quantify their effects. The effects from a longitudinally expanding plasma on medium as well as high energy jets are…

High Energy Physics - Phenomenology · Physics 2009-10-28 Jicai Pan , Charles Gale

Interest in deep learning in collider physics has been growing in recent years, specifically in applying these methods in jet classification, anomaly detection, particle identification etc. Among those, jet classification using neural…

High Energy Physics - Phenomenology · Physics 2024-08-05 Camellia Bose , Amit Chakraborty , Shreecheta Chowdhury , Saunak Dutta

The search for new physics at high energy accelerators has been at the crossroads with very little hint of signals suggesting otherwise. The challenges at a hadronic machine such as the LHC is compounded by the fact that final states are…

High Energy Physics - Phenomenology · Physics 2024-06-12 Aruna Kumar Nayak , Santosh Kumar Rai , Tousik Samui

Hard scattered partons are predicted to be well calibrated probes of the hot and dense medium produced in heavy ion collisions. Interactions of these partons with the medium w ill result in modifications of internal jet structure in Au+Au…

Nuclear Experiment · Physics 2019-08-13 Jan Kapitan

The ability to identify jets containing B hadrons is important for the high-pT physics program of a general-purpose experiment such as ATLAS. b-tagging is in particular useful for selecting very pure top quark samples, for studying standard…

High Energy Physics - Experiment · Physics 2008-11-04 Marc Lehmacher

We present a new tagger which aims at identifying partially reconstructed objects, in which only some of the constituents are collected in a single jet. As an example, we focus on top decays in which either part of the hadronically decaying…

High Energy Physics - Phenomenology · Physics 2016-08-31 Marat Freytsis , Tomer Volansky , Jonathan R. Walsh

Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of…

High Energy Physics - Phenomenology · Physics 2026-03-27 Vinicius Mikuni , Benjamin Nachman