Marginal Stability in Structural, Spin, and Electron Glasses

By M. Muller, Matthieu Wyart. 2014

204 citations recorded by the source corpus.

We revisit the concept of marginal stability in glasses and determine its range of applicability in the context of an avalanche-type response to slow external driving. We argue that there is an intimate connection between a pseudogap in the distribution of local fields and crackling in systems with long-range interactions. We classify glassy systems according to the presence or absence of marginal stability, providing a unifying perspective on the phenomenology of systems as diverse as spin and electron glasses, hard spheres, pinned elastic interfaces, and soft amorphous solids undergoing plastic deformation.

Subfields: Condensed Matter Physics, Materials Chemistry, Natural Language Processing

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Citations in the corpus

The jamming transition as a paradigm to understand the loss landscape of deep neural networks (2018, background): “The inequality comes from arguments on the stability of jammed packings, and the fact that it is saturated (which can be proven for certain dynamics [43]) implies that such systems are marginally stable: they display an abundance of low-energy excitations and are prone to avalanche dynamics and crac”
Deformation and flow of amorphous solids: Insights from elastoplastic models (2017, background): “The latter are most probably governed by different physics, in which spatially extended rearrangements may occur under vanishing loading (Müller and Wyart, 2015).”
Mean-field avalanches in jammed spheres. (2016, background): “ledependent local minima that are deformed non-uniformly when the system is slightly perturbed. Upon increasing an external perturbation, a step-wise and sample-dependent response is usually observed [1, 2, 3, 4, 5, 6, 7, 8, 9], giving rise to jumps in several observables, called avalanches. An inte”
Micro-plasticity and recent insights from intermittent and small-scale plasticity (2017, background): “pow er-law distribution in a quantity that characterizes the onset of a driven instability. In the context of marginal stability, such power-law distributions are referred to as psuedo -gap functions [230] . Importantly, if the system is in a state of criticality prior to and during initial loading,”