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Microstructure and velocity of field-driven Ising interfaces moving under a soft stochastic dynamic
1Center for Materials Research and Technology, School of Computational Science and Information Technology, Florida State University, Tallahassee, Florida 32306-4350, USA. rikvold@csit.fsu.edu
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|October 26, 2005
Summary
We studied Ising interfaces using soft dynamics, finding properties similar to the solid-on-solid model. Unlike hard dynamics, the interface width does not diverge with increasing field.
Area of Science:
- Statistical Mechanics
- Condensed Matter Physics
- Computational Physics
Background:
- Investigating non-equilibrium systems is crucial for understanding complex phenomena.
- Ising models and solid-on-solid (SOS) models are fundamental for studying interfaces.
- Stochastic dynamics, like Glauber and Metropolis, are essential for simulating these systems.
Purpose of the Study:
- To analyze the mobility and microscopic structure of (1+1)-dimensional Ising interfaces.
- To explore the behavior of interfaces under an applied field using a "soft" stochastic dynamic.
- To compare the soft dynamic in the Ising model with previous studies using hard dynamics and the SOS model.
Main Methods:
- Theoretical analysis.
- Dynamic Monte Carlo simulations.
- Single-spin-flip stochastic dynamics with factorizing transition rates (soft dynamic).
Main Results:
- The Ising model with soft dynamics exhibits properties closely resembling the SOS model with the same dynamic.
- The local interface width in the Ising model with soft dynamics does not diverge as the applied field increases.
- The interface skewness at nonzero fields is weak and has an opposite sign compared to results from hard dynamics.
Conclusions:
- Soft stochastic dynamics in Ising interfaces lead to distinct behaviors compared to hard dynamics.
- The Ising model with soft dynamics offers a simplified yet insightful approach to studying interface phenomena.
- Findings contribute to a deeper understanding of non-equilibrium statistical mechanics and interface dynamics.
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