Dynamics of Hot QCD Matter 2024 -- Hard Probes

TL;DR

The paper reviews recent experimental and theoretical advances in understanding the Quark-Gluon Plasma using hard probes like jets and heavy flavors, highlighting new insights and machine learning approaches from the HOT QCD Matter 2024 conference.

Contribution

It provides a comprehensive overview of current experimental data, theoretical models, and innovative methods such as machine learning in the study of QGP hard probes.

Findings

Enhanced understanding of jet quenching at RHIC and LHC

Refined models of heavy-flavor suppression in QGP

Introduction of machine learning techniques for heavy flavor analysis

Abstract

The hot and dense QCD matter, known as the Quark-Gluon Plasma (QGP), is explored through heavy-ion collision experiments at the LHC and RHIC. Jets and heavy flavors, produced from the initial hard scattering, are used as hard probes to study the properties of the QGP. Recent experimental observations on jet quenching and heavy-flavor suppression have strengthened our understanding, allowing for fine-tuning of theoretical models in hard probes. The second conference, HOT QCD Matter 2024, was organized to bring the community together for discussions on key topics in the field. This article comprises 15 sections, each addressing various aspects of hard probes in relativistic heavy-ion collisions, offering a snapshot of current experimental observations and theoretical advancements. The article begins with a discussion on memory effects in the quantum evolution of quarkonia in the quark-gluon plasma, followed by an experimental review, new insights on jet quenching at RHIC and LHC, and concludes with a machine learning approach to heavy flavor production at the Large Hadron Collider.