Computational Modeling of Spin Dynamics

The Ising model, originally developed in the 1920’s to analyse ferromagnetic properties has since found a myriad of other seemingly unrelated applications. An updated Ising model, Glauber’s spin dynamics, is used to examine phase changes in ferromagnetic materials and other systems. In the Glauber s...

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Published: eCommons 2019
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Online Access:https://ecommons.udayton.edu/stander_posters/1629
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spelling ftdaytonuniv:oai:ecommons.udayton.edu:stander_posters-2629 2023-06-11T04:09:35+02:00 Computational Modeling of Spin Dynamics 2019-04-24T07:00:00Z https://ecommons.udayton.edu/stander_posters/1629 unknown eCommons https://ecommons.udayton.edu/stander_posters/1629 Stander Symposium Projects Stander Symposium project text 2019 ftdaytonuniv 2023-05-08T07:03:11Z The Ising model, originally developed in the 1920’s to analyse ferromagnetic properties has since found a myriad of other seemingly unrelated applications. An updated Ising model, Glauber’s spin dynamics, is used to examine phase changes in ferromagnetic materials and other systems. In the Glauber spin model, a system starts with some initial condition and over time the state of the undergoes small fluctuations that increase as more energy is put into the system. Then, there is a critical point where the system loses its initial condition and changes phase. Glauber’s spin model has been used to examine the changes that melt ponds in the arctic undergo over time. The model has been used in chemistry to determine whether polymer chains will form. Glauber’s model has even found uses in information theory. The goal of this project is to create an Ising model using Python then display some of the properties of the Ising model with a feedback mechanism coupling Glauber's spin dynamics and the external forcing on the system. The one dimensional and two dimensional Ising models are examined. It is shown, as Ising did, that the one dimensional model does not predict any phase changes. It is also shown that the Glauber spin model does predict phase changes for a system. Text Arctic University of Dayton: eCommons Arctic
institution Open Polar
collection University of Dayton: eCommons
op_collection_id ftdaytonuniv
language unknown
topic Stander Symposium project
spellingShingle Stander Symposium project
Computational Modeling of Spin Dynamics
topic_facet Stander Symposium project
description The Ising model, originally developed in the 1920’s to analyse ferromagnetic properties has since found a myriad of other seemingly unrelated applications. An updated Ising model, Glauber’s spin dynamics, is used to examine phase changes in ferromagnetic materials and other systems. In the Glauber spin model, a system starts with some initial condition and over time the state of the undergoes small fluctuations that increase as more energy is put into the system. Then, there is a critical point where the system loses its initial condition and changes phase. Glauber’s spin model has been used to examine the changes that melt ponds in the arctic undergo over time. The model has been used in chemistry to determine whether polymer chains will form. Glauber’s model has even found uses in information theory. The goal of this project is to create an Ising model using Python then display some of the properties of the Ising model with a feedback mechanism coupling Glauber's spin dynamics and the external forcing on the system. The one dimensional and two dimensional Ising models are examined. It is shown, as Ising did, that the one dimensional model does not predict any phase changes. It is also shown that the Glauber spin model does predict phase changes for a system.
format Text
title Computational Modeling of Spin Dynamics
title_short Computational Modeling of Spin Dynamics
title_full Computational Modeling of Spin Dynamics
title_fullStr Computational Modeling of Spin Dynamics
title_full_unstemmed Computational Modeling of Spin Dynamics
title_sort computational modeling of spin dynamics
publisher eCommons
publishDate 2019
url https://ecommons.udayton.edu/stander_posters/1629
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source Stander Symposium Projects
op_relation https://ecommons.udayton.edu/stander_posters/1629
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