Journal article 327 views 109 downloads
Phase transitions in particle physics
Progress in Particle and Nuclear Physics, Volume: 133, Start page: 104070
Swansea University Authors:
Gert Aarts , Chris Allton
, Biagio Lucini
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PDF | Accepted Manuscript
Open Access Statement – For the purpose of Open Access the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.
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DOI (Published version): 10.1016/j.ppnp.2023.104070
Abstract
Phase transitions in a non-perturbative regime can be studied by ab initio Lattice Field Theory methods. The status and future research directions for LFT investigations of Quantum Chromo-Dynamics under extreme conditions are reviewed, including properties of hadrons and of the hypothesized QCD axio...
Published in: | Progress in Particle and Nuclear Physics |
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ISSN: | 0146-6410 |
Published: |
Elsevier BV
2023
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Online Access: |
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URI: | https://cronfa.swan.ac.uk/Record/cronfa63930 |
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Abstract: |
Phase transitions in a non-perturbative regime can be studied by ab initio Lattice Field Theory methods. The status and future research directions for LFT investigations of Quantum Chromo-Dynamics under extreme conditions are reviewed, including properties of hadrons and of the hypothesized QCD axion as inferred from QCD topology in different phases. We discuss phase transitions in strong interactions in an extended parameter space, and the possibility of model building for Dark Matter and Electro-Weak Symmetry Breaking. Methodological challenges are addressed as well, including new developments in Artificial Intelligence geared towards the identification of different phases and transitions. |
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Item Description: |
GGI workshop "Phase Transitions in Particle Physics" review. |
Keywords: |
Strong interactions, Hadron physics, Lattice Field Theory, Functional Approaches, Effective Field Theories, Phase transitions, QCD phase diagram, QCD phenomenology, QCD topology, QCD axion, Quark Gluon Plasma, Conformal field theories, Machine Learning, Algorithmic developments |
College: |
Faculty of Science and Engineering |
Funders: |
STFC, Royal Society, Leverhulme Trust, European Commission
ST/T000813/1, WM170010, RF-2020-461\9, ERC 813942 |
Start Page: |
104070 |