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Article: Understanding earthquake precursors: from subcritical instabilities to catastrophic events

TitleUnderstanding earthquake precursors: from subcritical instabilities to catastrophic events
Authors
Keywordscatastrophic
collapse
dynamic
excitable systems
mechanisms
subcritical instabilities
tensor networks
Issue Date9-Apr-2024
PublisherIOP Publishing
Citation
Physica Scripta, 2024, v. 99, n. 5 How to Cite?
Abstract

The collapse of man-made and natural structures is a complex phenomenon that has been studied for centuries. Existing models often focus on a ‘critical point’ where failure becomes imminent. This work presents a radically different perspective: large earthquakes may not arise from critical states, but instead develop dynamically from the subcritical regime as rare, extreme events. Our approach hinges on an extension of Onsager’s reciprocal theorem, allowing us to delve into this subcritical realm. We demonstrate that within such a regime, excitable systems, like those underlying earthquakes, are dynamically renormalised towards a nonlocal equilibrium. For these systems, the maximum entropy production of at least two interacting phases is used to replace the local equilibrium assumption for the subcritical state. Typically, dissipative processes at larger scales arrest these self-amplifying feedbacks. However, in rare instances, they can morph into intricate tensor networks of instabilities that ripple from microscopic scales to the entire system, culminating in an extreme event like a catastrophic earthquake. This novel framework offers a potentially deeper understanding of earthquake precursors and paves the way for exploring earthquake prediction based on the statistics of subcritical dynamics.


Persistent Identifierhttp://hdl.handle.net/10722/346217
ISSN
2023 Impact Factor: 2.6
2023 SCImago Journal Rankings: 0.415

 

DC FieldValueLanguage
dc.contributor.authorRegenauer-Lieb, Klaus-
dc.contributor.authorHu, Manman-
dc.date.accessioned2024-09-12T00:30:54Z-
dc.date.available2024-09-12T00:30:54Z-
dc.date.issued2024-04-09-
dc.identifier.citationPhysica Scripta, 2024, v. 99, n. 5-
dc.identifier.issn0031-8949-
dc.identifier.urihttp://hdl.handle.net/10722/346217-
dc.description.abstract<p>The collapse of man-made and natural structures is a complex phenomenon that has been studied for centuries. Existing models often focus on a ‘critical point’ where failure becomes imminent. This work presents a radically different perspective: large earthquakes may not arise from critical states, but instead develop dynamically from the subcritical regime as rare, extreme events. Our approach hinges on an extension of Onsager’s reciprocal theorem, allowing us to delve into this subcritical realm. We demonstrate that within such a regime, excitable systems, like those underlying earthquakes, are dynamically renormalised towards a nonlocal equilibrium. For these systems, the maximum entropy production of at least two interacting phases is used to replace the local equilibrium assumption for the subcritical state. Typically, dissipative processes at larger scales arrest these self-amplifying feedbacks. However, in rare instances, they can morph into intricate tensor networks of instabilities that ripple from microscopic scales to the entire system, culminating in an extreme event like a catastrophic earthquake. This novel framework offers a potentially deeper understanding of earthquake precursors and paves the way for exploring earthquake prediction based on the statistics of subcritical dynamics.</p>-
dc.languageeng-
dc.publisherIOP Publishing-
dc.relation.ispartofPhysica Scripta-
dc.subjectcatastrophic-
dc.subjectcollapse-
dc.subjectdynamic-
dc.subjectexcitable systems-
dc.subjectmechanisms-
dc.subjectsubcritical instabilities-
dc.subjecttensor networks-
dc.titleUnderstanding earthquake precursors: from subcritical instabilities to catastrophic events-
dc.typeArticle-
dc.identifier.doi10.1088/1402-4896/ad36f2-
dc.identifier.scopuseid_2-s2.0-85190067351-
dc.identifier.volume99-
dc.identifier.issue5-
dc.identifier.eissn1402-4896-
dc.identifier.issnl0031-8949-

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