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Ergodicity of the LLR method for the Density of States

Guido Cossu, Biagio Lucini Orcid Logo, Roberto Pellegrini, Antonio Rago

EPJ Web of Conferences, Volume: 175, Start page: 02005

Swansea University Author: Biagio Lucini Orcid Logo

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DOI (Published version): 10.1051/epjconf/201817502005

Abstract

The LLR method is a novel algorithm that enables us to evaluate the density of states in lattice gauge theory. We present our study of the ergodicity properties of the LLR algorithm for the model of Yang-Mills SU(3). We show that the use of the replica exchange method alleviates significantly the to...

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Published in: EPJ Web of Conferences
ISSN: 2100-014X
Published: 2018
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URI: https://cronfa.swan.ac.uk/Record/cronfa39244
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first_indexed 2018-03-28T13:32:04Z
last_indexed 2018-04-13T19:28:57Z
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spelling 2018-04-13T14:15:39.1644487 v2 39244 2018-03-28 Ergodicity of the LLR method for the Density of States 7e6fcfe060e07a351090e2a8aba363cf 0000-0001-8974-8266 Biagio Lucini Biagio Lucini true false 2018-03-28 SMA The LLR method is a novel algorithm that enables us to evaluate the density of states in lattice gauge theory. We present our study of the ergodicity properties of the LLR algorithm for the model of Yang-Mills SU(3). We show that the use of the replica exchange method alleviates significantly the topological freeze-out that severely affects other algorithms. Journal Article EPJ Web of Conferences 175 02005 2100-014X 26 3 2018 2018-03-26 10.1051/epjconf/201817502005 https://www.epj-conferences.org/articles/epjconf/abs/2018/10/epjconf_lattice2018_02005/epjconf_lattice2018_02005.html COLLEGE NANME Mathematics COLLEGE CODE SMA Swansea University RCUK,Institution,Royal Society, Wolfson Fundation, ERDF 2018-04-13T14:15:39.1644487 2018-03-28T11:42:14.9280823 Faculty of Science and Engineering School of Mathematics and Computer Science - Mathematics Guido Cossu 1 Biagio Lucini 0000-0001-8974-8266 2 Roberto Pellegrini 3 Antonio Rago 4 0039244-28032018114406.pdf epjconf_lattice2018_02005.pdf 2018-03-28T11:44:06.2200000 Output 236069 application/pdf Version of Record true 2018-03-28T00:00:00.0000000 Released under the terms of a Creative Commons Attribution License 4.0 (CC-BY). true eng
title Ergodicity of the LLR method for the Density of States
spellingShingle Ergodicity of the LLR method for the Density of States
Biagio Lucini
title_short Ergodicity of the LLR method for the Density of States
title_full Ergodicity of the LLR method for the Density of States
title_fullStr Ergodicity of the LLR method for the Density of States
title_full_unstemmed Ergodicity of the LLR method for the Density of States
title_sort Ergodicity of the LLR method for the Density of States
author_id_str_mv 7e6fcfe060e07a351090e2a8aba363cf
author_id_fullname_str_mv 7e6fcfe060e07a351090e2a8aba363cf_***_Biagio Lucini
author Biagio Lucini
author2 Guido Cossu
Biagio Lucini
Roberto Pellegrini
Antonio Rago
format Journal article
container_title EPJ Web of Conferences
container_volume 175
container_start_page 02005
publishDate 2018
institution Swansea University
issn 2100-014X
doi_str_mv 10.1051/epjconf/201817502005
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 Mathematics and Computer Science - Mathematics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Mathematics
url https://www.epj-conferences.org/articles/epjconf/abs/2018/10/epjconf_lattice2018_02005/epjconf_lattice2018_02005.html
document_store_str 1
active_str 0
description The LLR method is a novel algorithm that enables us to evaluate the density of states in lattice gauge theory. We present our study of the ergodicity properties of the LLR algorithm for the model of Yang-Mills SU(3). We show that the use of the replica exchange method alleviates significantly the topological freeze-out that severely affects other algorithms.
published_date 2018-03-26T03:49:49Z
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score 11.037603

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