  The stability of a granular material is a collective phenomenon controlled by
individual particles through their interactions. Forecasting when granular
materials will undergo an abrupt failure is an ongoing challenge due to the
intricate interactions between particles. Here, we report experiments on
photoelastic disks undergoing intermittent stick-slip dynamics in a quasi-2D
annular shear apparatus, with the evolving network of contact forces made
visible via polarized light. We characterize the system by interpreting the
interparticle forces as a multilayer network, and apply GenLouvin community
detection to identify strongly correlated groups of particles. We observe that
the community structure becomes increasingly volatile as the material
approaches failure, and that this volatility provides a forecast that precedes
what is detectable by considering the forces alone. We additionally observe
that both weak and strong forces contribute to the strength of this forecast.
These findings provide a new approach to detect patterns of causality and
forecast impending failures.
