25 Years of Self-organized Criticality: Numerical Detection Methods

The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have pla...

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Autor principal:	Morales, Laura Fernanda
Publicado:	2016
Materias:	Numerical methods Self organized criticality Criticality (nuclear fission) Application-oriented Autocorrelation methods Comfort zone Detection methods Event detection Scientific researches Self-organized criticality Spatial temporals
Acceso en línea:	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00386308_v198_n1-4_p217_McAteer http://hdl.handle.net/20.500.12110/paper_00386308_v198_n1-4_p217_McAteer
Aporte de:	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

id	paper:paper_00386308_v198_n1-4_p217_McAteer
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spelling	paper:paper_00386308_v198_n1-4_p217_McAteer2023-06-08T15:03:05Z 25 Years of Self-organized Criticality: Numerical Detection Methods Morales, Laura Fernanda Numerical methods Self organized criticality Criticality (nuclear fission) Application-oriented Autocorrelation methods Comfort zone Detection methods Event detection Scientific researches Self-organized criticality Spatial temporals Numerical methods The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century. © 2015, Springer Science+Business Media Dordrecht. Fil:Morales, L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2016 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00386308_v198_n1-4_p217_McAteer http://hdl.handle.net/20.500.12110/paper_00386308_v198_n1-4_p217_McAteer
institution	Universidad de Buenos Aires
institution_str	I-28
repository_str	R-134
collection	Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic	Numerical methods Self organized criticality Criticality (nuclear fission) Application-oriented Autocorrelation methods Comfort zone Detection methods Event detection Scientific researches Self-organized criticality Spatial temporals Numerical methods
spellingShingle	Numerical methods Self organized criticality Criticality (nuclear fission) Application-oriented Autocorrelation methods Comfort zone Detection methods Event detection Scientific researches Self-organized criticality Spatial temporals Numerical methods Morales, Laura Fernanda 25 Years of Self-organized Criticality: Numerical Detection Methods
topic_facet	Numerical methods Self organized criticality Criticality (nuclear fission) Application-oriented Autocorrelation methods Comfort zone Detection methods Event detection Scientific researches Self-organized criticality Spatial temporals Numerical methods
description	The detection and characterization of self-organized criticality (SOC), in both real and simulated data, has undergone many significant revisions over the past 25 years. The explosive advances in the many numerical methods available for detecting, discriminating, and ultimately testing, SOC have played a critical role in developing our understanding of how systems experience and exhibit SOC. In this article, methods of detecting SOC are reviewed; from correlations to complexity to critical quantities. A description of the basic autocorrelation method leads into a detailed analysis of application-oriented methods developed in the last 25 years. In the second half of this manuscript space-based, time-based and spatial-temporal methods are reviewed and the prevalence of power laws in nature is described, with an emphasis on event detection and characterization. The search for numerical methods to clearly and unambiguously detect SOC in data often leads us outside the comfort zone of our own disciplines—the answers to these questions are often obtained by studying the advances made in other fields of study. In addition, numerical detection methods often provide the optimum link between simulations and experiments in scientific research. We seek to explore this boundary where the rubber meets the road, to review this expanding field of research of numerical detection of SOC systems over the past 25 years, and to iterate forwards so as to provide some foresight and guidance into developing breakthroughs in this subject over the next quarter of a century. © 2015, Springer Science+Business Media Dordrecht.
author	Morales, Laura Fernanda
author_facet	Morales, Laura Fernanda
author_sort	Morales, Laura Fernanda
title	25 Years of Self-organized Criticality: Numerical Detection Methods
title_short	25 Years of Self-organized Criticality: Numerical Detection Methods
title_full	25 Years of Self-organized Criticality: Numerical Detection Methods
title_fullStr	25 Years of Self-organized Criticality: Numerical Detection Methods
title_full_unstemmed	25 Years of Self-organized Criticality: Numerical Detection Methods
title_sort	25 years of self-organized criticality: numerical detection methods
publishDate	2016
url	https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00386308_v198_n1-4_p217_McAteer http://hdl.handle.net/20.500.12110/paper_00386308_v198_n1-4_p217_McAteer
work_keys_str_mv	AT moraleslaurafernanda 25yearsofselforganizedcriticalitynumericaldetectionmethods
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25 Years of Self-organized Criticality: Numerical Detection Methods

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