Understanding the swap Monte Carlo algorithm in a size-polydisperse model glassformer
The dynamics of a polydisperse model glassformer are investigated by augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC). Three variants of the SMC algorithm are analyzed with regard to convergence and performance. We elucidate the microscopic mechanism responsible for the dras...
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| creator | Küchler, Niklas Horbach, Jürgen |
| description | The dynamics of a polydisperse model glassformer are investigated by
augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC).
Three variants of the SMC algorithm are analyzed with regard to convergence and
performance. We elucidate the microscopic mechanism responsible for the drastic
speed-up of structural relaxation at low temperature. It manifests in a
stepwise increase of the mean squared displacement when the time scale between
the application of swap sweeps is significantly larger than a characteristic
microscopic time scale. Compared to Newtonian dynamics, with the hybrid MD-SMC
dynamics the glass transition shifts to a lower temperature and a different
temperature dependence of the localization length is found. |
| doi_str_mv | 10.48550/arxiv.2305.03838 |
| format | Article |
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augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC).
Three variants of the SMC algorithm are analyzed with regard to convergence and
performance. We elucidate the microscopic mechanism responsible for the drastic
speed-up of structural relaxation at low temperature. It manifests in a
stepwise increase of the mean squared displacement when the time scale between
the application of swap sweeps is significantly larger than a characteristic
microscopic time scale. Compared to Newtonian dynamics, with the hybrid MD-SMC
dynamics the glass transition shifts to a lower temperature and a different
temperature dependence of the localization length is found.</description><identifier>DOI: 10.48550/arxiv.2305.03838</identifier><language>eng</language><subject>Physics - Data Analysis, Statistics and Probability ; Physics - Disordered Systems and Neural Networks ; Physics - Soft Condensed Matter ; Physics - Statistical Mechanics</subject><creationdate>2023-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2305.03838$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2305.03838$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Küchler, Niklas</creatorcontrib><creatorcontrib>Horbach, Jürgen</creatorcontrib><title>Understanding the swap Monte Carlo algorithm in a size-polydisperse model glassformer</title><description>The dynamics of a polydisperse model glassformer are investigated by
augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC).
Three variants of the SMC algorithm are analyzed with regard to convergence and
performance. We elucidate the microscopic mechanism responsible for the drastic
speed-up of structural relaxation at low temperature. It manifests in a
stepwise increase of the mean squared displacement when the time scale between
the application of swap sweeps is significantly larger than a characteristic
microscopic time scale. Compared to Newtonian dynamics, with the hybrid MD-SMC
dynamics the glass transition shifts to a lower temperature and a different
temperature dependence of the localization length is found.</description><subject>Physics - Data Analysis, Statistics and Probability</subject><subject>Physics - Disordered Systems and Neural Networks</subject><subject>Physics - Soft Condensed Matter</subject><subject>Physics - Statistical Mechanics</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotz71OwzAUhmEvDKj0Apg4N5DgxHbijCjiTypiaefotD5OLTl2ZEdAe_VAYfqm95Mexm4rXkqtFL_H9OU-ylpwVXKhhb5mu10wlPKCwbgwwnIkyJ84w1sMC0GPyUdAP8bkluMELgBCdmcq5uhPxuX5pyWYoiEPo8ecbUwTpRt2ZdFnWv_vim2fHrf9S7F5f37tHzYFNq0uWk6VkpIrVZmWkCvbWcNrXTUHyxsl1V61KLvK6s7KQ0dGcm2M3CPVFkXdiBW7-7u9uIY5uQnTafj1DRef-AZXgUv9</recordid><startdate>20230505</startdate><enddate>20230505</enddate><creator>Küchler, Niklas</creator><creator>Horbach, Jürgen</creator><scope>GOX</scope></search><sort><creationdate>20230505</creationdate><title>Understanding the swap Monte Carlo algorithm in a size-polydisperse model glassformer</title><author>Küchler, Niklas ; Horbach, Jürgen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a678-70e15440551d7ea05f9fd02816cf06545b57a491f89f4c9ed408dd4bae2fa3263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Physics - Data Analysis, Statistics and Probability</topic><topic>Physics - Disordered Systems and Neural Networks</topic><topic>Physics - Soft Condensed Matter</topic><topic>Physics - Statistical Mechanics</topic><toplevel>online_resources</toplevel><creatorcontrib>Küchler, Niklas</creatorcontrib><creatorcontrib>Horbach, Jürgen</creatorcontrib><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Küchler, Niklas</au><au>Horbach, Jürgen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Understanding the swap Monte Carlo algorithm in a size-polydisperse model glassformer</atitle><date>2023-05-05</date><risdate>2023</risdate><abstract>The dynamics of a polydisperse model glassformer are investigated by
augmenting molecular dynamics (MD) simulation with swap Monte Carlo (SMC).
Three variants of the SMC algorithm are analyzed with regard to convergence and
performance. We elucidate the microscopic mechanism responsible for the drastic
speed-up of structural relaxation at low temperature. It manifests in a
stepwise increase of the mean squared displacement when the time scale between
the application of swap sweeps is significantly larger than a characteristic
microscopic time scale. Compared to Newtonian dynamics, with the hybrid MD-SMC
dynamics the glass transition shifts to a lower temperature and a different
temperature dependence of the localization length is found.</abstract><doi>10.48550/arxiv.2305.03838</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Physics - Data Analysis, Statistics and Probability Physics - Disordered Systems and Neural Networks Physics - Soft Condensed Matter Physics - Statistical Mechanics |
| title | Understanding the swap Monte Carlo algorithm in a size-polydisperse model glassformer |
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