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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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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. |
format | Online Article Text |
id | pubmed-10217331 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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