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Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression

Sam Offler, Gert Aarts Orcid Logo, Chris Allton Orcid Logo, Benjamin Jaeger, Seyong Kim, Maria Paola Lombardo, Ben Page, Sinead Ryan, Jon-Ivar Skullerud, Thomas Spriggs

Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021), Volume: 396, Start page: 509

Swansea University Authors: Sam Offler, Gert Aarts Orcid Logo, Chris Allton Orcid Logo

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DOI (Published version): 10.22323/1.396.0509

Abstract

We discuss results for bottomonium at nonzero temperature obtained using NRQCD on Fastsum Generation 2L ensembles, as part of the Fastsum collaboration’s programme to determine the spectrum of the bottomonium system as a function of temperature using a variety of approaches. Here we give an update o...

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Published in: Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021)
ISSN: 1824-8039
Published: Trieste, Italy Sissa Medialab 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa69021
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spelling 2025-04-24T10:36:12.2397067 v2 69021 2025-03-04 Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression d05d1e268521f7cd301d47852e36e734 Sam Offler Sam Offler true false 1ba0dad382dfe18348ec32fc65f3f3de 0000-0002-6038-3782 Gert Aarts Gert Aarts true false de706a260fa1e1e47430693e135f41c7 0000-0003-0795-124X Chris Allton Chris Allton true false 2025-03-04 BGPS We discuss results for bottomonium at nonzero temperature obtained using NRQCD on Fastsum Generation 2L ensembles, as part of the Fastsum collaboration’s programme to determine the spectrum of the bottomonium system as a function of temperature using a variety of approaches. Here we give an update on results for spectral functions obtained using Kernel Ridge Regression. We pay in particular attention to the generation of training data and introduce the notion of using lattice QCD ensembles to learn how to improve the generation of training data. A practical implementation is given. Conference Paper/Proceeding/Abstract Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021) 396 509 Sissa Medialab Trieste, Italy 1824-8039 8 7 2022 2022-07-08 10.22323/1.396.0509 COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University This work is supported by STFC grant ST/T000813/1. SK is supported by the National Research Foundation of Korea under grant NRF-2021R1A2C1092701 funded by the Korean government (MEST). BP has been supported by a Swansea University Research Excellence Scholarship (SURES). This work used the DiRACExtremeScalingserviceatthe University of Edinburgh, operated by the Edinburgh Parallel Computing Centre on behalf of the STFC DiRAC HPC Facility (www.dirac.ac.uk). This equipment was funded by BEIS capital funding via STFC capital grant ST/R00238X/1 and STFC DiRAC Operations grant ST/R001006/1. 2025-04-24T10:36:12.2397067 2025-03-04T11:46:46.8894329 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Physics Sam Offler 1 Gert Aarts 0000-0002-6038-3782 2 Chris Allton 0000-0003-0795-124X 3 Benjamin Jaeger 4 Seyong Kim 5 Maria Paola Lombardo 6 Ben Page 7 Sinead Ryan 8 Jon-Ivar Skullerud 9 Thomas Spriggs 10 69021__34077__d4e39600f0e04913baed60690765d46a.pdf 69021.VoR.pdf 2025-04-24T10:34:00.1317576 Output 532883 application/pdf Version of Record true ©Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0). true eng https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en
title Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
spellingShingle Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
Sam Offler
Gert Aarts
Chris Allton
title_short Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
title_full Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
title_fullStr Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
title_full_unstemmed Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
title_sort Reconstruction of bottomonium spectral functions in thermal QCD using Kernel Ridge Regression
author_id_str_mv d05d1e268521f7cd301d47852e36e734
1ba0dad382dfe18348ec32fc65f3f3de
de706a260fa1e1e47430693e135f41c7
author_id_fullname_str_mv d05d1e268521f7cd301d47852e36e734_***_Sam Offler
1ba0dad382dfe18348ec32fc65f3f3de_***_Gert Aarts
de706a260fa1e1e47430693e135f41c7_***_Chris Allton
author Sam Offler
Gert Aarts
Chris Allton
author2 Sam Offler
Gert Aarts
Chris Allton
Benjamin Jaeger
Seyong Kim
Maria Paola Lombardo
Ben Page
Sinead Ryan
Jon-Ivar Skullerud
Thomas Spriggs
format Conference Paper/Proceeding/Abstract
container_title Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021)
container_volume 396
container_start_page 509
publishDate 2022
institution Swansea University
issn 1824-8039
doi_str_mv 10.22323/1.396.0509
publisher Sissa Medialab
college_str Faculty of Science and Engineering
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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
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description We discuss results for bottomonium at nonzero temperature obtained using NRQCD on Fastsum Generation 2L ensembles, as part of the Fastsum collaboration’s programme to determine the spectrum of the bottomonium system as a function of temperature using a variety of approaches. Here we give an update on results for spectral functions obtained using Kernel Ridge Regression. We pay in particular attention to the generation of training data and introduce the notion of using lattice QCD ensembles to learn how to improve the generation of training data. A practical implementation is given.
published_date 2022-07-08T05:46:11Z
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