Scale-Free Network of Earthquakes

Physics – Condensed Matter – Disordered Systems and Neural Networks

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

14 pages, 3 figures, substantial modifications

Scientific paper

The district of southern California and Japan are divided into small cubic cells, each of which is regarded as a vertex of a graph if earthquakes occur therein. Two successive earthquakes define an edge and a loop, which replace the complex fault-fault interaction. In this way, the seismic data are mapped to a random graph. It is discovered that an evolving random graph associated with earthquakes behaves as a scale-free network of the Barabasi-Albert type. The distributions of connectivities in the graphs thus constructed are found to decay as a power law, showing a novel feature of earthquake as a complex critical phenomenon. This result can be interpreted in view of the facts that frequency of earthquakes with large values of moment also decays as a power law (the Gutenberg-Richter law) and aftershocks associated with a mainshock tend to return to the locus of the mainshock, contributing to the large degree of connectivity of the vertex of the mainshock. It is also found that the exponent of the distribution of connectivities is characteristic for a plate under investigation.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Scale-Free Network of Earthquakes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Scale-Free Network of Earthquakes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Scale-Free Network of Earthquakes will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-411925

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.