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Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton

We develop the notion of Random Domino Automaton, a simple probabilistic cellular automaton model for earthquake statistics, in order to provide a mechanistic basis for the interrelation of Gutenberg–Richter law and Omori law with the waiting time distribution for earthquakes. In this work, we provi...

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Autores principales: Białecki, Mariusz, Gałka, Mateusz, Bagchi, Arpan, Gulgowski, Jacek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217331/
https://www.ncbi.nlm.nih.gov/pubmed/37238574
http://dx.doi.org/10.3390/e25050819
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author Białecki, Mariusz
Gałka, Mateusz
Bagchi, Arpan
Gulgowski, Jacek
author_facet Białecki, Mariusz
Gałka, Mateusz
Bagchi, Arpan
Gulgowski, Jacek
author_sort Białecki, Mariusz
collection PubMed
description We develop the notion of Random Domino Automaton, a simple probabilistic cellular automaton model for earthquake statistics, in order to provide a mechanistic basis for the interrelation of Gutenberg–Richter law and Omori law with the waiting time distribution for earthquakes. In this work, we provide a general algebraic solution to the inverse problem for the model and apply the proposed procedure to seismic data recorded in the Legnica-Głogów Copper District in Poland, which demonstrate the adequacy of the method. The solution of the inverse problem enables adjustment of the model to localization-dependent seismic properties manifested by deviations from Gutenberg–Richter law.
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spelling pubmed-102173312023-05-27 Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton Białecki, Mariusz Gałka, Mateusz Bagchi, Arpan Gulgowski, Jacek Entropy (Basel) Article We develop the notion of Random Domino Automaton, a simple probabilistic cellular automaton model for earthquake statistics, in order to provide a mechanistic basis for the interrelation of Gutenberg–Richter law and Omori law with the waiting time distribution for earthquakes. In this work, we provide a general algebraic solution to the inverse problem for the model and apply the proposed procedure to seismic data recorded in the Legnica-Głogów Copper District in Poland, which demonstrate the adequacy of the method. The solution of the inverse problem enables adjustment of the model to localization-dependent seismic properties manifested by deviations from Gutenberg–Richter law. MDPI 2023-05-19 /pmc/articles/PMC10217331/ /pubmed/37238574 http://dx.doi.org/10.3390/e25050819 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Białecki, Mariusz
Gałka, Mateusz
Bagchi, Arpan
Gulgowski, Jacek
Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title_full Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title_fullStr Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title_full_unstemmed Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title_short Modeling Exact Frequency-Energy Distribution for Quakes by a Probabilistic Cellular Automaton
title_sort modeling exact frequency-energy distribution for quakes by a probabilistic cellular automaton
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217331/
https://www.ncbi.nlm.nih.gov/pubmed/37238574
http://dx.doi.org/10.3390/e25050819
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