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Meson spectroscopy at non-zero temperature using lattice QCD / SERGIO GARCIA-MASCARAQUE

Swansea University Author: SERGIO GARCIA-MASCARAQUE

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DOI (Published version): 10.23889/SUthesis.62707

Abstract

This thesis explores two main topics: the effects of the temperature on several Quantum Chromodynamics mesonic observables, with a concrete focus on the tem-perature dependence of the mesonic mass spectrum, and numerical spectral recon-struction of lattice correlation functions employing deep neural...

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Published: Swansea 2023
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Hands, Simon ; Aarts, Gert; Burns, Timothy
URI: https://cronfa.swan.ac.uk/Record/cronfa62707
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first_indexed 2023-02-21T13:36:17Z
last_indexed 2023-02-22T04:16:21Z
id cronfa62707
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spelling 2023-02-21T13:46:52.5332953 v2 62707 2023-02-21 Meson spectroscopy at non-zero temperature using lattice QCD a506df3acb6cd4bf1acfca396c08b618 SERGIO GARCIA-MASCARAQUE SERGIO GARCIA-MASCARAQUE true false 2023-02-21 This thesis explores two main topics: the effects of the temperature on several Quantum Chromodynamics mesonic observables, with a concrete focus on the tem-perature dependence of the mesonic mass spectrum, and numerical spectral recon-struction of lattice correlation functions employing deep neural networks. In the first two chapters, a brief introduction to standard lattice Quantum Chromodynamics and non-zero temperature field theory is provided. Using the tools presented in the intro-ductory chapters, a complete spectroscopy analysis of the temperature dependence of several mesonic ground state masses is developed. From this study, novel results in the restoration of chiral symmetry as a function of the temperature are obtained by studying the degree of degeneracy between the ρ(770) and a1(1260) states. Ad-ditionally, a complete study of the thermal effects affecting the mesonic D(s)-sector below the pseudocritical temperature of the system is provided. A self-contained chapter discussing the pion velocity in the medium is also included in the document. The pion velocity is estimated as a function of the temperature using non-zero tem-perature lattice Quantum Chromodynamics. In addition, after providing a detailed introduction to the field of neural networks, their application to numerical spectral reconstruction is studied. A simple implementation in which deep neural networks are applied to numerical spectral reconstruction is tested in order to explore its limits and applicability. E-Thesis Swansea Thermal field theory, QCD, lattice QCD, spectral reconstruction, high energy physics 10 2 2023 2023-02-10 10.23889/SUthesis.62707 COLLEGE NANME COLLEGE CODE Swansea University Hands, Simon ; Aarts, Gert; Burns, Timothy Doctoral Ph.D STFC-CDT 2023-02-21T13:46:52.5332953 2023-02-21T13:27:18.1160283 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Physics SERGIO GARCIA-MASCARAQUE 1 62707__26649__7c09d3b0df09410c842047fbc9115836.pdf ChavesGarciaMascaraque_Sergio_PhD_Thesis_Final_Cronfa.pdf 2023-02-21T13:39:34.1311025 Output 2528854 application/pdf E-Thesis – open access true Copyright: The author, Sergio Chaves García-Mascaraque, 2023. true eng
title Meson spectroscopy at non-zero temperature using lattice QCD
spellingShingle Meson spectroscopy at non-zero temperature using lattice QCD
SERGIO GARCIA-MASCARAQUE
title_short Meson spectroscopy at non-zero temperature using lattice QCD
title_full Meson spectroscopy at non-zero temperature using lattice QCD
title_fullStr Meson spectroscopy at non-zero temperature using lattice QCD
title_full_unstemmed Meson spectroscopy at non-zero temperature using lattice QCD
title_sort Meson spectroscopy at non-zero temperature using lattice QCD
author_id_str_mv a506df3acb6cd4bf1acfca396c08b618
author_id_fullname_str_mv a506df3acb6cd4bf1acfca396c08b618_***_SERGIO GARCIA-MASCARAQUE
author SERGIO GARCIA-MASCARAQUE
author2 SERGIO GARCIA-MASCARAQUE
format E-Thesis
publishDate 2023
institution Swansea University
doi_str_mv 10.23889/SUthesis.62707
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Physics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Physics
document_store_str 1
active_str 0
description This thesis explores two main topics: the effects of the temperature on several Quantum Chromodynamics mesonic observables, with a concrete focus on the tem-perature dependence of the mesonic mass spectrum, and numerical spectral recon-struction of lattice correlation functions employing deep neural networks. In the first two chapters, a brief introduction to standard lattice Quantum Chromodynamics and non-zero temperature field theory is provided. Using the tools presented in the intro-ductory chapters, a complete spectroscopy analysis of the temperature dependence of several mesonic ground state masses is developed. From this study, novel results in the restoration of chiral symmetry as a function of the temperature are obtained by studying the degree of degeneracy between the ρ(770) and a1(1260) states. Ad-ditionally, a complete study of the thermal effects affecting the mesonic D(s)-sector below the pseudocritical temperature of the system is provided. A self-contained chapter discussing the pion velocity in the medium is also included in the document. The pion velocity is estimated as a function of the temperature using non-zero tem-perature lattice Quantum Chromodynamics. In addition, after providing a detailed introduction to the field of neural networks, their application to numerical spectral reconstruction is studied. A simple implementation in which deep neural networks are applied to numerical spectral reconstruction is tested in order to explore its limits and applicability.
published_date 2023-02-10T04:23:01Z
_version_ 1763663918579843072
score 11.035874

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