  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. Recurrences to earthquakes are identified
employing correlation thresholds to demarcate the most meaningful ones in each
cluster. Data pertaining to three different seismic regions, viz. California,
Japan and Himalayas, are comparatively analyzed using such a network model. The
distribution of recurrence lengths and recurrence times are two of the key
features analyzed to draw conclusions about the universal aspects of such a
network model. We find that the unimodal feature of recurrence length
distribution, which helps to associate typical rupture lengths with different
magnitude earthquakes, is robust across the different seismic regions. The
out-degree of the networks 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, with two regimes having different
exponents, are obtained with recurrence time distribution. This is in agreement
with the Omori law for aftershocks and extends it to spatial recurrences. The
crossover to the second power law regime can be taken to be signalling the end
of aftershock regime in an objective fashion.
