Transition prediction in the Ising-model.

Dynamical systems can be subject to critical transitions where a system's state abruptly shifts from one stable equilibrium to another. To a certain extent such transitions can be predicted with a set of methods known as early warning signals. These methods are often developed and tested on sys...

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Autores principales:	Manfred Füllsack, Daniel Reisinger
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8d42edce6e6f42ab9ecdbf63d4a820f9
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id	oai:doaj.org-article:8d42edce6e6f42ab9ecdbf63d4a820f9
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spelling	oai:doaj.org-article:8d42edce6e6f42ab9ecdbf63d4a820f92021-12-02T20:04:20ZTransition prediction in the Ising-model.1932-620310.1371/journal.pone.0259177https://doaj.org/article/8d42edce6e6f42ab9ecdbf63d4a820f92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0259177https://doaj.org/toc/1932-6203Dynamical systems can be subject to critical transitions where a system's state abruptly shifts from one stable equilibrium to another. To a certain extent such transitions can be predicted with a set of methods known as early warning signals. These methods are often developed and tested on systems simulated with equation-based approaches that focus on the aggregate dynamics of a system. Many ecological phenomena however seem to necessitate the consideration of a system's micro-level interactions since only there the actual reasons for sudden state transitions become apparent. Agent-based approaches that simulate systems from the bottom up by explicitly focusing on these micro-level interactions have only rarely been used in such investigations. This study compares the performance of a bifurcation estimation method for predicting state transitions when applied to data from an equation-based and an agent-based version of the Ising-model. The results show that the method can be applied to agent-based models and, despite its greater stochasticity, can provide useful predictions about state changes in complex systems.Manfred FüllsackDaniel ReisingerPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0259177 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Manfred Füllsack Daniel Reisinger Transition prediction in the Ising-model.
description	Dynamical systems can be subject to critical transitions where a system's state abruptly shifts from one stable equilibrium to another. To a certain extent such transitions can be predicted with a set of methods known as early warning signals. These methods are often developed and tested on systems simulated with equation-based approaches that focus on the aggregate dynamics of a system. Many ecological phenomena however seem to necessitate the consideration of a system's micro-level interactions since only there the actual reasons for sudden state transitions become apparent. Agent-based approaches that simulate systems from the bottom up by explicitly focusing on these micro-level interactions have only rarely been used in such investigations. This study compares the performance of a bifurcation estimation method for predicting state transitions when applied to data from an equation-based and an agent-based version of the Ising-model. The results show that the method can be applied to agent-based models and, despite its greater stochasticity, can provide useful predictions about state changes in complex systems.
format	article
author	Manfred Füllsack Daniel Reisinger
author_facet	Manfred Füllsack Daniel Reisinger
author_sort	Manfred Füllsack
title	Transition prediction in the Ising-model.
title_short	Transition prediction in the Ising-model.
title_full	Transition prediction in the Ising-model.
title_fullStr	Transition prediction in the Ising-model.
title_full_unstemmed	Transition prediction in the Ising-model.
title_sort	transition prediction in the ising-model.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/8d42edce6e6f42ab9ecdbf63d4a820f9
work_keys_str_mv	AT manfredfullsack transitionpredictionintheisingmodel AT danielreisinger transitionpredictionintheisingmodel
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Transition prediction in the Ising-model.

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