54,976 research outputs found
Dynamical evolution of clustering in complex network of earthquakes
The network approach plays a distinguished role in contemporary science of
complex systems/phenomena. Such an approach has been introduced into seismology
in a recent work [S. Abe and N. Suzuki, Europhys. Lett. 65, 581 (2004)]. Here,
we discuss the dynamical property of the earthquake network constructed in
California and report the discovery that the values of the clustering
coefficient remain stationary before main shocks, suddenly jump up at the main
shocks, and then slowly decay following a power law to become stationary again.
Thus, the network approach is found to characterize main shocks in a peculiar
manner.Comment: 10 pages, 3 figures, 1 tabl
Network of Earthquakes and Recurrences Therein
We quantify the correlation between earthquakes and use the same to
distinguish between relevant causally connected earthquakes. Our correlation
metric is a variation on the one introduced by Baiesi and Paczuski (2004). A
network of earthquakes is constructed, which is time ordered and with links
between the more correlated ones. Data pertaining to the California region has
been used in the study. Recurrences to earthquakes are identified employing
correlation thresholds to demarcate the most meaningful ones in each cluster.
The distribution of recurrence lengths and recurrence times are analyzed
subsequently to extract information about the complex dynamics. We find that
the unimodal feature of recurrence lengths helps to associate typical rupture
lengths with different magnitude earthquakes. The out-degree of the network
shows a hub structure rooted on the large magnitude earthquakes. In-degree
distribution is seen to be dependent on the density of events in the
neighborhood. Power laws are also obtained with recurrence time distribution
agreeing with the Omori law.Comment: 17 pages, 5 figure
Scale-Free Network of Earthquakes
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.Comment: 14 pages, 3 figures, substantial modification
An improved glimpse into earthquake activity in northeastern Alaska
The northeastern Brooks Range is long known to be seismically active, but meaningful analysis of the earthquake activity has been limited by the lack of instrumentation. The seismic record in the area dates back to the mid-1970s, and shows a broad northeast-trending zone of earthquake activity. Improvements made in the past 20 years to the permanent seismic network along with new data collected by the temporary USArray network of seismometers located throughout northeastern Alaska have dramatically lowered the earthquake detection threshold in the area. It is now possible to identify patterns within the earthquake data including spatial distribution and occurrence rates, which indicate the presence of previously unrecognized active fault systems. I highlight several such features within the data: a 110 km (60 mi) line of recurring earthquakes near the village of Beaver that strongly suggest a singular fault system; a cluster of earthquakes near the village of Venetie that are likely occurring on a complex active fault system; a years-long mainshock-aftershock sequence of earthquakes near the Draanjik River that began in 2006; and two swarms separated by 50 km (30 mi) in distance and 7 years near the Hulahula River.Ye
The Network of Epicenters of the Olami-Feder-Christensen Model of Earthquakes
We study the dynamics of the Olami-Feder-Christensen (OFC) model of
earthquakes, focusing on the behavior of sequences of epicenters regarded as a
growing complex network. Besides making a detailed and quantitative study of
the effects of the borders (the occurrence of epicenters is dominated by a
strong border effect which does not scale with system size), we examine the
degree distribution and the degree correlation of the graph. We detect sharp
differences between the conservative and nonconservative regimes of the model.
Removing border effects, the conservative regime exhibits a Poisson-like degree
statistics and is uncorrelated, while the nonconservative has a broad
power-law-like distribution of degrees (if the smallest events are ignored),
which reproduces the observed behavior of real earthquakes. In this regime the
graph has also a unusually strong degree correlation among the vertices with
higher degree, which is the result of the existence of temporary attractors for
the dynamics: as the system evolves, the epicenters concentrate increasingly on
fewer sites, exhibiting strong synchronization, but eventually spread again
over the lattice after a series of sufficiently large earthquakes. We propose
an analytical description of the dynamics of this growing network, considering
a Markov process network with hidden variables, which is able to account for
the mentioned properties.Comment: 9 pages, 10 figures. Smaller number of figures, and minor text
corrections and modifications. For version with full resolution images see
http://fig.if.usp.br/~tpeixoto/cond-mat-0602244.pd
Earthquake networks based on similar activity patterns
Earthquakes are a complex spatiotemporal phenomenon, the underlying mechanism
for which is still not fully understood despite decades of research and
analysis. We propose and develop a network approach to earthquake events. In
this network, a node represents a spatial location while a link between two
nodes represents similar activity patterns in the two different locations. The
strength of a link is proportional to the strength of the cross-correlation in
activities of two nodes joined by the link. We apply our network approach to a
Japanese earthquake catalog spanning the 14-year period 1985-1998. We find
strong links representing large correlations between patterns in locations
separated by more than 1000 km, corroborating prior observations that
earthquake interactions have no characteristic length scale. We find network
characteristics not attributable to chance alone, including a large number of
network links, high node assortativity, and strong stability over time.Comment: 8 pages text, 9 figures. Updated from previous versio
Networks as Renormalized Models for Emergent Behavior in Physical Systems
Networks are paradigms for describing complex biological, social and
technological systems. Here I argue that networks provide a coherent framework
to construct coarse-grained models for many different physical systems. To
elucidate these ideas, I discuss two long-standing problems. The first concerns
the structure and dynamics of magnetic fields in the solar corona, as
exemplified by sunspots that startled Galileo almost 400 years ago. We
discovered that the magnetic structure of the corona embodies a scale free
network, with spots at all scales. A network model representing the
three-dimensional geometry of magnetic fields, where links rewire and nodes
merge when they collide in space, gives quantitative agreement with available
data, and suggests new measurements. Seismicity is addressed in terms of
relations between events without imposing space-time windows. A metric
estimates the correlation between any two earthquakes. Linking strongly
correlated pairs, and ignoring pairs with weak correlation organizes the
spatio-temporal process into a sparse, directed, weighted network. New scaling
laws for seismicity are found. For instance, the aftershock decay rate
decreases as 1/t in time up to a correlation time, t[omori]. An estimate from
the data gives t[omori] to be about one year for small magnitude 3 earthquakes,
about 1400 years for the Landers event, and roughly 26,000 years for the
earthquake causing the 2004 Asian tsunami. Our results confirm Kagan's
conjecture that aftershocks can rumble on for centuries.Comment: For the Proceedings of the Erice workshop on Complexity,
Metastability and Nonextensivity (2004), 12 page
Complex networks of earthquakes and aftershocks
We invoke a metric to quantify the correlation between any two earthquakes.
This provides a simple and straightforward alternative to using space-time
windows to detect aftershock sequences and obviates the need to distinguish
main shocks from aftershocks. Directed networks of earthquakes are constructed
by placing a link, directed from the past to the future, between pairs of
events that are strongly correlated. Each link has a weight giving the relative
strength of correlation such that the sum over the incoming links to any node
equals unity for aftershocks, or zero if the event had no correlated
predecessors. A correlation threshold is set to drastically reduce the size of
the data set without losing significant information. Events can be aftershocks
of many previous events, and also generate many aftershocks. The probability
distribution for the number of incoming and outgoing links are both scale free,
and the networks are highly clustered. The Omori law holds for aftershock rates
up to a decorrelation time that scales with the magnitude, , of the
initiating shock as with .
Another scaling law relates distances between earthquakes and their aftershocks
to the magnitude of the initiating shock. Our results are inconsistent with the
hypothesis of finite aftershock zones. We also find evidence that seismicity is
dominantly triggered by small earthquakes. Our approach, using concepts from
the modern theory of complex networks, together with a metric to estimate
correlations, opens up new avenues of research, as well as new tools to
understand seismicity.Comment: 12 pages, 12 figures, revtex
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