Predicting activation-barrier and plasticity-onset statistics in a model of glasses

Abstract

A recently introduced anharmonic mean-field model unifiedly reproduced a broad range of low-temperature glass phenomena --- including harmonic nonphononic spectral properties, linear micromechanics and strongly driven elasto-plastic dynamics --- indicating that its underlying energy landscape is intrinsically glassy. Here, we apply a nonlinear modes framework to the model and derive analytic predictions for the asymptotic distributions of activation barriers $p(Δ{U})\!\sim\!(Δ{U})^{1/4}$ and the external force needed for the onset of plasticity $p(f_{\rm c})\sim f_{\rm c}^{2/3}$, for their extreme-value scaling and for $\langleΔ{U}\rangle$ beyond the asymptotic regime. These predictions are expected to equally apply to the mean-field model and to finite-dimensional glasses. We develop efficient algorithms for sampling minima and saddles of the model's glassy potential energy landscape, and quantitatively confirm the theoretical predictions. This progress is enabled by identifying a subset of collective degrees of freedom that are physically relevant for activated glassy dynamics, which like the theoretical predictions should apply to realistic glasses.