Publication
Marginal Stability in Structural, Spin, and Electron Glasses
Abstract
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. © 2015 by Annual Reviews.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Ontological neighbourhood
Related concepts (32)
Normal distribution
In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.
Cauchy distribution
The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution. It is also known, especially among physicists, as the Lorentz distribution (after Hendrik Lorentz), Cauchy–Lorentz distribution, Lorentz(ian) function, or Breit–Wigner distribution. The Cauchy distribution is the distribution of the x-intercept of a ray issuing from with a uniformly distributed angle. It is also the distribution of the ratio of two independent normally distributed random variables with mean zero.
Stable distribution
In probability theory, a distribution is said to be stable if a linear combination of two independent random variables with this distribution has the same distribution, up to location and scale parameters. A random variable is said to be stable if its distribution is stable. The stable distribution family is also sometimes referred to as the Lévy alpha-stable distribution, after Paul Lévy, the first mathematician to have studied it. Of the four parameters defining the family, most attention has been focused on the stability parameter, (see panel).
Related publications (127)
A story of two transitions: From adhesive to abrasive wear and from ductile to brittle regime
Jean-François Molinari, Sacha Zenon Wattel
Atomistic simulations performed with a family of model potential with tunable hardness have proven to be a great tool for advancing the understanding of wear processes at the asperity level. They have been instrumental in finding a critical length scale, w ...
2024System for automated and dynamic cell culture
The present relates to a system for automated cell culture, the system comprising an inflow module, a cell culture plate and an outflow module, said inflow module being in fluid connection with the outflow module via the cell culture plate, the inflow modu ...
2023swissALPS: a Dataset for Imbalanced Land Cover Mapping in Alpine Regions
Our dataset consists of very high-resolution aerial images (50cm) and a digital elevation model (50cm) that covers approx. 2300 km2 of land above 2000m altitude in the southwestern part of Switzerland. Our land cover labels focus on alpine land cover that ...
IEEE DataPort2023Related MOOCs (12)
Advanced statistical physics
We explore statistical physics in both classical and open quantum systems. Additionally, we will cover probabilistic data analysis that is extremely useful in many applications.
Advanced statistical physics
We explore statistical physics in both classical and open quantum systems. Additionally, we will cover probabilistic data analysis that is extremely useful in many applications.
Selected Topics on Discrete Choice
Discrete choice models are used extensively in many disciplines where it is important to predict human behavior at a disaggregate level. This course is a follow up of the online course “Introduction t