The ALICE experiment: a journey through QCD

ALICE Collaboration alice-publications@ cern … - The European Physical …, 2024 - Springer
The ALICE experiment was proposed in 1993, to study strongly-interacting matter at extreme
energy densities and temperatures. This proposal entailed a comprehensive investigation of …

[HTML][HTML] 50 Years of quantum chromodynamics: Introduction and Review

F Gross, E Klempt, SJ Brodsky, AJ Buras… - The European Physical …, 2023 - Springer
Quantum Chromodynamics, the theory of quarks and gluons, whose interactions can be
described by a local SU (3) gauge symmetry with charges called “color quantum numbers” …

[HTML][HTML] Science requirements and detector concepts for the electron-ion collider: EIC yellow report

RA Khalek, A Accardi, J Adam, D Adamiak, W Akers… - Nuclear Physics A, 2022 - Elsevier
This report describes the physics case, the resulting detector requirements, and the evolving
detector concepts for the experimental program at the Electron-Ion Collider (EIC). The EIC …

Machine learning in the search for new fundamental physics

G Karagiorgi, G Kasieczka, S Kravitz… - Nature Reviews …, 2022 - nature.com
Compelling experimental evidence suggests the existence of new physics beyond the well-
established and tested standard model of particle physics. Various current and upcoming …

Graph neural networks in particle physics

J Shlomi, P Battaglia, JR Vlimant - Machine Learning: Science …, 2020 - iopscience.iop.org
Particle physics is a branch of science aiming at discovering the fundamental laws of matter
and forces. Graph neural networks are trainable functions which operate on graphs—sets of …

[HTML][HTML] Review of top quark mass measurements in CMS

CMS collaboration - Physics Reports, 2025 - Elsevier
The top quark mass is one of the most intriguing parameters of the standard model (SM). Its
value indicates a Yukawa coupling close to unity, and the resulting strong ties to Higgs …

Exploring QCD matter in extreme conditions with Machine Learning

K Zhou, L Wang, LG Pang, S Shi - Progress in Particle and Nuclear Physics, 2024 - Elsevier
In recent years, machine learning has emerged as a powerful computational tool and novel
problem-solving perspective for physics, offering new avenues for studying strongly …

Jet tagging via particle clouds

H Qu, L Gouskos - Physical Review D, 2020 - APS
How to represent a jet is at the core of machine learning on jet physics. Inspired by the
notion of point clouds, we propose a new approach that considers a jet as an unordered set …

Precision studies of QCD in the low energy domain of the EIC

VD Burkert, L Elouadrhiri, A Afanasev… - Progress in particle and …, 2023 - Elsevier
Abstract This White Paper aims at highlighting the important benefits in the science reach of
the EIC. High luminosity operation is generally desirable, as it enables producing and …

A new era in the search for dark matter

G Bertone, TMP Tait - Nature, 2018 - nature.com
There is a growing sense of 'crisis' in the dark-matter particle community, which arises from
the absence of evidence for the most popular candidates for dark-matter particles—such as …