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 systems...

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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/7571bde4d9e5411cbf25aaf1f638b05c
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spelling	oai:doaj.org-article:7571bde4d9e5411cbf25aaf1f638b05c2021-11-11T07:14:38ZTransition prediction in the Ising-model1932-6203https://doaj.org/article/7571bde4d9e5411cbf25aaf1f638b05c2021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8568180/?tool=EBIhttps://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 (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/7571bde4d9e5411cbf25aaf1f638b05c
work_keys_str_mv	AT manfredfullsack transitionpredictionintheisingmodel AT danielreisinger transitionpredictionintheisingmodel
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Transition prediction in the Ising-model

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