Patricio Venegas-Aravena , Davide Zaccagnino

Large earthquakes have been viewed as highly chaotic events regardless of their magnitude, making their prediction intrinsically challenging. Here, we develop a mathematical tool to incorporate multiscale physics, capable of describing both deterministic and chaotic systems, to model earthquake rupture. Our findings suggest that the chaotic behavior of seismic dynamics, that is, its sensitivity to initial and boundary conditions, is inversely related to its magnitude. To validate this hypothesis, we performed numerical simulations with heterogeneous fault conditions. Our results indicate that large earthquakes, usually occurring in regions with higher residual energy and lower b-value (i.e., the exponent of the Gutenberg-Richter law), are less susceptible to perturbations. This suggests that a higher variability in earthquake magnitudes (larger b-values) may be indicative of structural complexity of the fault network and heterogeneous stress conditions. To further validate our findings, we compare our theoretical predictions with real seismicity in Southern California; specifically, the relationship between the b-value and the fractal dimension of hypocenters with our model predictions finding good agreement. The statistical similarities observed between the simulated and real earthquakes support the hypothesis that large earthquakes may be less chaotic than smaller ones; hence, more predictable.