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| Titel |
Earthquake sequencing: Chimera states with Kuramoto model dynamics on directed graphs |
| VerfasserIn |
K. Vasudevan, M. Cavers, A. Ware |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
2198-5634
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 2, no. 1 ; Nr. 2, no. 1 (2015-02-20), S.361-398 |
| Datensatznummer |
250115151
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| Publikation (Nr.) |
 copernicus.org/npgd-2-361-2015.pdf |
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| Zusammenfassung |
| Earthquake sequencing studies allow us to investigate empirical
relationships among spatio-temporal parameters describing the
complexity of earthquake properties. We have recently studied the
relevance of Markov chain models to draw information from global
earthquake catalogues. In these studies, we considered directed
graphs as graph theoretic representations of the Markov chain model,
and analyzed their properties. Here, we look at earthquake
sequencing itself as a directed graph. In general, earthquakes are
occurrences resulting from significant stress-interactions among
faults. As a result, stress-field fluctuations evolve
continuously. We propose that they are akin to the dynamics of the
collective behaviour of weakly-coupled non-linear oscillators. Since
mapping of global stress-field fluctuations in real time at all
scales is an impossible task, we consider an earthquake zone as
a proxy for a collection of weakly-coupled oscillators, the dynamics
of which would be appropriate for the ubiquitous Kuramoto model. In
the present work, we apply the Kuramoto model to the non-linear
dynamics on a directed graph of a sequence of earthquakes. For
directed graphs with certain properties, the Kuramoto model yields
synchronization, and inclusion of non-local effects evokes the
occurrence of chimera states or the co-existence of synchronous and
asynchronous behaviour of oscillators. In this paper, we show how we
build the directed graphs derived from global seismicity data. Then,
we present conditions under which chimera states could occur and
subsequently, point out the role of Kuramoto model in understanding
the evolution of synchronous and asynchronous regions. |
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