Extracting Correlations in Earthquake Time Series Using Visibility Graph Analysis

Recent observation studies have revealed that earthquakes are classified into several different categories. Each category might be characterized by the unique statistical feature in time series, but present understanding is still limited due to their nonlinear and nonstationary nature. Here we utilize complex network theory shed new light on properties of earthquake series. We investigate two kinds which magnitude inter-event (IET), for three categories earthquakes: regular earthquakes, swarms, tectonic tremors. Following criterion visibility graph, series mapped a considering each seismic event as node determining links. As opposed current common belief, it found not statistically equivalent random The IET exhibit correlations similar fractional Brownian motion all earthquakes. Furthermore, show can distinguished topology associated graph. Analysis assortativity coefficient also reveals swarms more intermittent than