A complex network model for seismicity based on mutual information

Seismicity is the product of the interaction between the different parts of the lithosphere. Here, we model each part of the Earth as a cell that is constantly communicating its state to its environment. As a neuron is stimulated and produces an output, the different parts of the lithosphere are constantly stimulated by both other cells and the ductile part of the lithosphere, and produce an output in the form of a stress transfer or an earthquake. This output depends on the properties of each part of the Earth’s crust and the magnitude of the inputs. In this study, we propose an approach to the quantification of this communication, with the aid of the Information Theory, and model seismicity as a Complex Network. We have used data from California, and this new approach gives a better understanding of the processes involved in the formation of seismic patterns in that region.

► We have shown how information is transmitted in a seismically active region. ► Seismicity is modeled as a weighted complex network links are the mutual information. ► The information is transmitted from North to South in the California case. ► The networks are not random. ► There is a different behavior for short periods of time and for long time intervals.