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Out-of-equilibrium dynamical fluctuations in glassy systems.
C Chamon1, P Charbonneau, L F Cugliandolo
1Department of Physics, Boston University, 590 Commonwealth Avenue, Boston, Massachusetts 02215, USA. chamon@buphy.bu.edu
The Journal of Chemical Physics
|November 20, 2004
Summary
Glassy systems without disorder exhibit similar fluctuation scaling to those with disorder, driven by a critical dynamical correlation length. This behavior is explained by evolving extreme value distributions derived from an effective sigma model.
Area of Science:
- Condensed Matter Physics
- Statistical Mechanics
- Complex Systems
Background:
- Understanding out-of-equilibrium dynamics in glassy systems is crucial for materials science.
- Previous studies focused on quenched disorder, limiting applicability to certain models.
- Mesoscopic fluctuations in glassy systems require further theoretical and computational investigation.
Purpose of the Study:
- To investigate out-of-equilibrium mesoscopic fluctuations in glassy systems without quenched disorder.
- To compare fluctuation scaling in disordered and non-disordered glassy models.
- To develop a theoretical framework for describing these fluctuations.
Main Methods:
- Extensive computer simulations of glassy models.
- Analysis of local two-time correlators and their probability distributions.
- Development of an effective sigma model approach.
Main Results:
- Glassy models without quenched disorder show similar scaling of two-time correlators as models with short-ranged quenched interactions.
- A critical-like dynamical correlation length is identified as the key factor for these scaling properties.
- A time-evolving extreme value distribution successfully describes the observed data collapse.
Conclusions:
- The presence of quenched disorder is not essential for observing specific scaling behaviors in mesoscopic fluctuations.
- Dynamical correlation length plays a fundamental role in the out-of-equilibrium dynamics of glassy systems.
- The developed effective sigma model provides a theoretical basis for understanding extreme value distributions in these systems.