11 V. CONCLUSIONS FIG. 6: The distributions of the recurrent times for different m th values is shown here in panels ( a ) and ( b ) for the actual and shuffled catalogs respectively. Significant differences can be observed between the two distributions. However, the dependence of the distributions on m in the actual catalog is , a major departure from what is expected from a causal network [10]. time scales, the different distributions show a dependance on m . The power law exponent in this region is much less than 1 . 0 and varies from − 0 . 3 to − 0 . 45 as m$_{th}$ increases from 2 . 5 to 4 . 5. The range over which this smaller exponent holds good depends on m$_{th}$ and increases with it. This aspect of the recurrent time distributions is at variance with that observed for California, where the temporal distributions were found to be independent of m for the actual catalog and showed a single power law regime over almost the entire range. This behaviour was attributed to the causal features of seismicity. The recurrent time distributions for the shuffled catalog in fig. 6(b) shows a more prominent dependence on m , which is expected for a random network [10]. That the actual catalog for Japan too shows characteristics attributed to an acausal network signifies a random behaviour in the temporal distributions in the case of Japan. The general procedure that was introduced to infer causal structure from clusters of lo- calised events was illustrated on the earthquake catalog of California. Our results from adopting the procedure on the earthquake catalog of Japan confirms its robustness. The construction of the network involves establishing correlations between nodes without making any assumptions regarding the nature of the correlations. The distinctive features of the -10 -8 -6 -4 -2 0 -4 -2 0 2 4 6 log P m (t) log t(hr) (a) = 2.5 = 3.0 = 3.5 = 4.0 = 4.5 -1992 -4 -2 0 -4 0 4  log t 1.0 p m (t) log t(hr) -10 -8 -6 -4 -2 0 -4 -2 0 2 4 6 log P m (t) log t(hr) (b) = 2.5 = 3.0 = 3.5 = 4.0 = 4.5 -1992 -4 -2 0 -4 0 4  log t 1.0 p m (t) log t(hr)