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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Autores principales: McAteer, R.T.J., Aschwanden, M.J., Dimitropoulou, M., Georgoulis, M.K., Pruessner, G., Morales, L., Ireland, J., Abramenko, V.
Formato: JOUR
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:http://hdl.handle.net/20.500.12110/paper_00386308_v198_n1-4_p217_McAteer
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Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_00386308_v198_n1-4_p217_McAteer
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spelling todo:paper_00386308_v198_n1-4_p217_McAteer2023-10-03T14:49:11Z 25 Years of Self-organized Criticality: Numerical Detection Methods McAteer, R.T.J. Aschwanden, M.J. Dimitropoulou, M. Georgoulis, M.K. Pruessner, G. Morales, L. Ireland, J. Abramenko, V. 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. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar 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
McAteer, R.T.J.
Aschwanden, M.J.
Dimitropoulou, M.
Georgoulis, M.K.
Pruessner, G.
Morales, L.
Ireland, J.
Abramenko, V.
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.
format JOUR
author McAteer, R.T.J.
Aschwanden, M.J.
Dimitropoulou, M.
Georgoulis, M.K.
Pruessner, G.
Morales, L.
Ireland, J.
Abramenko, V.
author_facet McAteer, R.T.J.
Aschwanden, M.J.
Dimitropoulou, M.
Georgoulis, M.K.
Pruessner, G.
Morales, L.
Ireland, J.
Abramenko, V.
author_sort McAteer, R.T.J.
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
url http://hdl.handle.net/20.500.12110/paper_00386308_v198_n1-4_p217_McAteer
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AT moralesl 25yearsofselforganizedcriticalitynumericaldetectionmethods
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