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Corrections to scaling in the phase-ordering dynamics of a vector order parameter
1Department of Physics and Astronomy, The University, Manchester M13 9PL, United Kingdom.
Summary
This study investigates corrections to scaling in phase-ordering kinetics for systems with O(n) symmetry. Researchers calculated the correction-to-scaling exponent and function, revealing dependencies on system dimensionality and order parameter components.
Area of Science:
- Condensed Matter Physics
- Statistical Mechanics
- Phase Transitions
Background:
- Phase-ordering kinetics describes how systems with multiple stable phases evolve over time.
- Scaling theories simplify complex systems by relating different states through a characteristic length scale.
- Deviations from ideal scaling behavior can arise from initial conditions and require further analysis.
Purpose of the Study:
- To investigate corrections to scaling in systems with O(n) symmetry at zero temperature.
- To analyze the impact of order parameter deviations on scaling morphology.
- To calculate the correction-to-scaling exponent and function for various system types.
Main Methods:
- Utilizing the approximate Gaussian closure theory developed by Mazenko.
- Calculating the equal-time pair correlation function including scaling corrections.
- Applying methods to both nonconserved and conserved order parameter systems.
Main Results:
- The equal-time pair correlation function was expressed including scaling corrections: C(r,t)=f0(r/L)+L(-omega)f1(r/L).
- The correction-to-scaling exponent (omega) was found to be nontrivial and dependent on system dimensionality (d) and order parameter components (n).
- Exact solutions for corrections to scaling were derived for the nonconserved one-dimensional XY model.
Conclusions:
- Corrections to scaling are significant in phase-ordering kinetics, particularly for systems with O(n) symmetry.
- The derived exponent (omega) and function (f1) provide a more accurate description of system evolution beyond simple scaling.
- The study offers valuable insights into the dynamics of pattern formation and coarsening in complex materials.