Zheng Zeyu, Yamasaki Kazuko, Tenenbaum Joel, Podobnik Boris, Tamura Yoshiyasu, Stanley H Eugene
Department of Environmental Sciences, Tokyo University of Information Sciences, Chiba 265-8501, Japan.
Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jul;86(1 Pt 1):011107. doi: 10.1103/PhysRevE.86.011107. Epub 2012 Jul 6.
It has been observed that discrete earthquake events possess memory, i.e., that events occurring in a particular location are dependent on the history of that location. We conduct an analysis to see whether continuous real-time data also display a similar memory and, if so, whether such autocorrelations depend on the size of earthquakes within close spatiotemporal proximity. We analyze the seismic wave form database recorded by 64 stations in Japan, including the 2011 "Great East Japan Earthquake," one of the five most powerful earthquakes ever recorded, which resulted in a tsunami and devastating nuclear accidents. We explore the question of seismic memory through use of mean conditional intervals and detrended fluctuation analysis (DFA). We find that the wave form sign series show power-law anticorrelations while the interval series show power-law correlations. We find size dependence in earthquake autocorrelations: as the earthquake size increases, both of these correlation behaviors strengthen. We also find that the DFA scaling exponent α has no dependence on the earthquake hypocenter depth or epicentral distance.
据观察，离散地震事件具有记忆性，即特定地点发生的事件取决于该地点的历史情况。我们进行了一项分析，以查看连续实时数据是否也显示出类似的记忆性，如果是，这种自相关性是否取决于时空邻近范围内地震的大小。我们分析了日本64个台站记录的地震波形数据库，其中包括2011年“东日本大地震”，这是有记录以来五次最强烈的地震之一，它引发了海啸并造成了毁灭性的核事故。我们通过使用平均条件间隔和去趋势波动分析（DFA）来探讨地震记忆问题。我们发现波形符号序列显示出幂律反相关性，而间隔序列显示出幂律相关性。我们发现地震自相关性存在大小依赖性：随着地震规模的增加，这两种相关行为都会增强。我们还发现DFA标度指数α与地震震源深度或震中距离无关。
