Investigating Precursors in Complex Systems: Insights from the Fiber Bundle Model and the 2017 México MW8.2 Earthquake

Abstract

Complex systems are characterized by self-organization, where interactions among constituent elements give rise to emergent patterns and critical transitions. In geophysics, earthquakes can be interpreted within this framework, where the analysis of precursor parameters provides critical insights into impending systemic instabilities. Among these, the temporal evolution of the b-value, derived from the Gutenberg-Richter frequency-magnitude scaling law, serves as a principal metric, with strong parallels drawn to Acoustic Emission (AE) studies in material failure. This work investigates critical-state precursors in two complementary case studies. The first employs AE time series generated from Fiber Bundle Model (FBM) simulations implemented via a Lattice Discrete Element Method (LDEM), enabling the characterization of progressive fracture and failure. The second examines the seismic sequence preceding the Mw 8.2 earthquake that struck Mexico in 2017. In both cases, the b- value and the Method of Critical Fluctuations (MCF-B) are applied to track the evolution of criticality. Results demonstrate that b-value variations consistently capture the transition to a critical regime, both in simulated and real seismic data. In contrast, MCF-B shows limited applicability in complex tectonic settings dominated by large, isolated events. These findings highlight the robustness of b-value analysis as a precursor, while also indicating the need for refining complementary approaches. The multiscale perspective adopted here contributes to advancing the identification of critical states in both acoustic and seismic domains, with implications for earthquake forecasting.