Tenenbaum Joel N, Havlin Shlomo, Stanley H Eugene
Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Oct;86(4 Pt 2):046107. doi: 10.1103/PhysRevE.86.046107. Epub 2012 Oct 15.
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 kilometers, 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.
地震是一种复杂的时空现象,尽管经过数十年的研究与分析,其潜在机制仍未被完全理解。我们提出并开发了一种针对地震事件的网络方法。在这个网络中,一个节点代表一个空间位置,而两个节点之间的一条边代表两个不同位置的相似活动模式。边的强度与由该边连接的两个节点活动中的互相关强度成正比。我们将我们的网络方法应用于一个涵盖1985年至1998年这14年期间的日本地震目录。我们发现,代表相隔超过1000公里的位置模式之间存在高度相关性的强边,证实了先前关于地震相互作用没有特征长度尺度的观测结果。我们发现网络特征并非仅由偶然因素导致,包括大量的网络边、高节点 assortativity 以及随时间的强稳定性。