When applying mechanical stress to a bulk metallic glass it responds with elastic and/or plastic deformations. A comprehensive microscopic theory for the plasticity of amorphous solids remains an open task. Shear transformation zones consisting of dozens of atoms have been identified as smallest units of deformation. The connexion between local formation of shear transformations zones and the creation of macroscopic shear bands can be made using statistical analysis of stress/energy drops or strain slips during mechanical loading. Numerical work has proposed a power law dependence of those energy drops. Here we present an approach to circumvent the experimental resolution problem using a waiting time analysis. We report on the power law-distributed deformation behaviour and the observation of a crossover in the waiting times statistics. This crossover indicates a transition in the plastic deformation behaviour from three-dimensional random activity to a two-dimensional nano shear band sliding.

Large scale simulations of two-dimensional bidisperse granular fluids allow us to determine spatial correlations of slow particles via the four-point structure factor S 4 (q,t). Both cases, elastic (ε = 1) as well as inelastic (ε < 1) collisions, are studied. As the fluid approaches structural arrest, i.e. for packing fractions in the range 0.6 ≤ φ ≤ 0.805, scaling is shown to hold: S 4 (q,t)/χ 4 (t) = s(qξ (t)). Both the dynamic susceptibility, χ 4 (τ α ), as well as the dynamic correlation length, ξ (τ α ), evaluated at the α relaxation time, τ α , can be fitted to a power law divergence at a critical packing fraction. The measured ξ (τ α ) widely exceeds the largest one previously observed for hard sphere 3d fluids. The number of particles in a slow cluster and the correlation length are related by a robust power law, χ 4 (τ α ) ≈ ξ d−p (τ α ), with an exponent d − p ≈ 1.6. This scaling is remarkably independent of ε, even though the strength of the dynamical heterogeneity increases dramatically as ε grows.Viscous liquids, colloidal suspensions, and granular fluids are all capable of undergoing dynamical arrest, either by reducing the temperature in the case of viscous liquids, or by increasing the density in the cases of colloidal suspensions and of granular systems [1][2][3][4]. As the dynamical arrest is approached, not only does the dynamics become dramatically slower, but it becomes increasingly heterogeneous [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. One of the most common ways to characterize the heterogeneity in the dynamics is to probe its fluctuations [4]. Since probing the dynamics requires observing the system at two times, probing the spatial fluctuations in the dynamics naturally leads to defining quantities that correlate the changes in the state of the system between two times, at two spatial points, i.e. four-point functions. Those quantities include the dynamic susceptibility χ 4 (t), which gives a spatially integrated measurement of the total fluctuations, and the four point structure factor S 4 (q,t), which is the Fourier transform of the spatial correlation function describing the local fluctuations in the dynamics [4,12,15]. From the small wave-vector behavior of S 4 (q,t), a correlation length ξ (t) can be extracted, and it has been found in simulations of viscous liquids and dense colloidal suspensions that this correlation length grows as dynamical arrest is approached [4,12,15,16]. For granular matter, on the other hand, the jamming transition has been analyzed extensively, but studies on dynamic heterogeneity (DH) are few. Two experimental groups have investigated driven 2d granular beds in the context of DH. These studies are restricted to small systems of order a few thousand particles [13,14,[17][18][19][20][21]. χ 4 (t) has been measured, but spatial correlations have not been investigated systematically due to small system size. Instead, compact regions of correlated particles are usually assumed, χ 4 (t) ∼ ξ d (t), thereby determining a correlation len...

Dynamical heterogeneities -strong fluctuations near the glass transition -are believed to be crucial to explain much of the glass transition phenomenology. One possible hypothesis for their origin is that they emerge from soft (Goldstone) modes associated with a broken continuous symmetry under time reparametrizations. To test this hypothesis, we use numerical simulation data from four glass-forming models to construct coarse grained observables that probe the dynamical heterogeneity, and decompose the fluctuations of these observables into two transverse components associated with the postulated time-fluctuation soft modes and a longitudinal component unrelated to them. We find that as temperature is lowered and timescales are increased, the time reparametrization fluctuations become increasingly dominant, and that their correlation volumes grow together with the correlation volumes of the dynamical heterogeneities, while the correlation volumes for longitudinal fluctuations remain small.