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== Symmetries and scaling invariance == | === Symmetries and scaling invariance === | ||
The EW equation is invariant under global height shifts | The EW equation is invariant under global height shifts | ||
Revision as of 17:32, 23 January 2026
Interfaces and manifolds
Many physical systems are governed by elastic manifolds embedded in a higher-dimensional medium. Typical examples include domain walls in ferromagnets, dislocations in crystals, vortex lines in superconductors, and propagating fronts.
We introduce the following notation:
- : internal dimension of the manifold
- : dimension of the displacement (or height) field
- : dimension of the embedding space
These satisfy
Two important cases are:
- Interfaces ():
The configuration is described by a scalar height field , where is the internal coordinate.
- Directed polymers ():
The configuration is described by a vector function embedded in dimensions.
Remark. With this notation, a one-dimensional interface (, ) can be viewed both as an interface and as a directed polymer.
In this lecture we focus on thermal interfaces.
Thermal interfaces: Langevin dynamics
We consider an interface at thermal equilibrium at temperature . Two assumptions are made:
- Overhangs and pinch-off are neglected, so is single-valued.
- The dynamics is overdamped; inertial effects are neglected.
The Langevin equation of motion reads
Here is the mobility and is a Gaussian thermal noise, with
The diffusion constant is fixed by the Einstein relation
In the following we set .
Elastic energy and Edwards–Wilkinson equation
The elastic energy associated with surface tension can be written as
where is the stiffness.
Keeping only the lowest-order term in gradients, the equation of motion becomes the Edwards–Wilkinson (EW) equation:
Symmetries and scaling invariance
The EW equation is invariant under global height shifts . This symmetry leads to scale invariance of the form
where is the dynamical exponent and the roughness exponent.
A simple dimensional analysis gives
From this one finds
Thus the interface is rough for and marginal at .
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Width of the interface
We now focus on a one-dimensional interface () of size with periodic boundary conditions.
The squared width is defined as
Introduce Fourier modes
with .
Using Parseval’s theorem one finds
---
Solution in Fourier space
The EW equation in Fourier space reads
with noise correlations
The solution is
Assuming a flat initial condition , one finds
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Growth and saturation of the width
The mean squared width evolves as
In the continuum limit this gives
At short times the interface roughens algebraically, while at long times the width saturates due to the finite system size.