LBan-II: Difference between revisions

From Disordered Systems Wiki
Jump to navigation Jump to search
(Created page with "=Edwards Wilkinson: an interface with thermal fluctuations: = Consider domain wall <math> h(r,t)</math> fluctuating at equilibrium at the temparature <math> T</math>. Here <math> t</math> is time, <math> r </math> defines the d-dimensional coordinate of the interface and <math> h</math> is the scalar height field. Hence, the domain wall separating two phases in a film has <math> d=1, r \in \cal{R}</math>, in a solid instead <math> d=2, r \in \cal{R}^2</math>. Two...")
 
 
(6 intermediate revisions by the same user not shown)
Line 1: Line 1:
=Edwards Wilkinson: an interface with thermal fluctuations:  =
=Introduction: Interfaces and Directed Polymers=


Consider domain wall <math> h(r,t)</math> fluctuating at  equilibrium at the temparature <math> T</math>. Here <math> t</math> is  time, <math> r </math> defines the d-dimensional coordinate of the interface and <math> h</math> is the scalar height field. Hence, the domain wall separating two phases in a film has <math> d=1, r \in \cal{R}</math>, in a solid instead <math> d=2, r \in \cal{R}^2</math>.  
The physical properties of many materials are governed by manifolds embedded in them. Examples include: dislocations in crystals, domain walls in ferromagnets or vortex lines in superconductors. We fix the following notation:
- <math>D</math>: spatial dimension of the embedding medium
– <math>d</math>: internal dimension of the manifold
<math>N</math>: dimension of the displacement (or height) field
 
These satisfy the relation:
<center><math>D = d + N</math></center>
 
We focus on two important cases:
== Directed Polymers (''d = 1'')==
The configuration is described by a vector function:
<math>\vec{x}(t)</math>,
where <math>t</math> is the internal coordinate. The polymer lives in <math>D = 1 + N</math> dimensions.
 
Examples: vortex lines, DNA strands,  fronts.
 
Although polymers may form loops, we restrict to directed polymers, i.e., configurations without overhangs or backward turns.
 
==Interfaces (''N = 1'')==
 
The interface is described by a scalar height field:
<math>h(\vec{r}, t)</math>,
where <math>\vec{r} \in \mathbb{R}^d</math> is the internal coordinate and <math>t</math> represents time.
 
Examples: domain walls and propagating fronts
 
Again we neglect overhangs or pinch-off: <math>h(\vec{r}, t)</math> is single-valued
 
'''Note''' that using our notation the 1D front is both an interface and a directed polymer
 
=Thermal Interfaces=


Two assumptions are done:
* Overhangs, pinch-off are neglected,  so that <math> h(r,t)</math> is a scalar univalued function.
* The dynamics is overdamped, so that we can neglect the inertial term.
* The dynamics is overdamped, so that we can neglect the inertial term.
===Derivation===
The Langevin equation of motion is
The Langevin equation of motion is
<center> <math>
<center> <math>
  \partial_t h(r,t)= - \mu \frac{\delta E_{pot}}{\delta h(r,t)} + \eta(r,t)
  \partial_t h(r,t)= - \mu \frac{\delta E_{pot}}{\delta h(r,t)} + \eta(r,t)
</math></center>
</math></center>
The first term <math> -  \delta E_{pot}/\delta h(r,t) </math> is the elastic force trying to smooth the interface, the mobility <math> \mu </math> is inversily proportional to the viscosity. The second term is the Langevin Gaussian noise defined by the correlations
The first term <math> -  \delta E_{pot}/\delta h(r,t) </math> is the elastic force trying to smooth the interface, the mobility <math> \mu </math> is the inverse of the viscosity. The second term is the Langevin noise. It is Guassian and defined by  
<center> <math>
<center> <math>
\langle \eta(r,t) \rangle =0, \; \langle \eta(r',t')\eta(r,t) \rangle = 2 d D \delta^d(r-r') \delta(t-t')  
\langle \eta(r,t) \rangle =0, \; \langle \eta(r',t')\eta(r,t) \rangle = 2 d D \delta^d(r-r') \delta(t-t')  
</math></center>
</math></center>
The symbol <math> \langle \ldots \rangle</math> indicates the average over the thermal noise.
The symbol <math> \langle \ldots \rangle</math> indicates the average over the thermal noise and the diffusion constant is fixed by the Einstein relation <math>
The diffusion constant is fixed by the Eistein relation (fluctuation-dissipation theorem):
<center> <math>
   D= \mu K_B T
   D= \mu K_B T
</math></center>
</math>. We set  <math> \mu= K_B=1</math>
We set  <math> \mu= K_B=1</math>


The potential energy of surface tension can be expanded at the lowest order in the gradient:  
The potential energy of surface tension (<math>\nu </math> is the stiffness) can be expanded at the lowest order in the gradient:  
<center> <math>  
<center> <math>  
E_{pot} = \nu \int d^d r\sqrt{1 +(\nabla h)^2} \sim \text{const.} + \frac{\nu}{2} \int d^d r (\nabla h)^2
E_{pot} = \nu \int d^d r\sqrt{1 +(\nabla h)^2} \sim \text{const.} + \frac{\nu}{2} \int d^d r (\nabla h)^2
Line 31: Line 54:
  \partial_t h(r,t)= \nu \nabla^2 h(r,t) + \eta(r,t)
  \partial_t h(r,t)= \nu \nabla^2 h(r,t) + \eta(r,t)
</math></center>
</math></center>
=== Scaling Invariance===
The equation enjoys of a continuous symmetry because <math> h(r,t) </math> and <math> h(r,t)+c </math>  cannot be distinguished. This is a condition of scale invariance:
<center> <math>
h(b r, b^z t) \overset{in law}{\sim}  b^{\alpha} h(r,t)
</math></center>
Here <math>
z, \alpha
</math> are the dynamic and the roughness exponent respectively. From dimensional analysis
<center> <math>
b^{\alpha-z} \partial_t h(r,t)= b^{\alpha-2} \nabla^2 h(r,t) +b^{-d/2-z/2} \eta(r,t)
</math></center>
From which you get <math> z=2 </math> in any dimension and a rough interface below <math> d=2 </math> with <math> \alpha =(2-d)/2 </math>.
== Explicit Solution ==
For simplicity, consider a 1-dimensional line of size L with periodic boundary conditions. It is useful to introduce the Fourier modes:
<center> <math>
\hat h_q(t)= \frac{1}{L} \int_0^L e^{iqr} h(r,t), \quad h(r,t)= \sum_q e^{-iqr} \hat h_q(t)
</math></center>
Here <math> q=2 \pi n/L, n=\ldots ,-1,0,1,\ldots</math> and recall <math> \int_0^L d r e^{iqr}= L \delta_{q,0} </math>.
*  Show that the EW equation writes
<center> <math>
\partial_t \hat h_q(t)= -\nu q^2 \hat h_q(t) + \eta_q(t), \quad \text{with} \; \langle \eta_{q_1}(t')  \eta_{q_2}(t)\rangle =\frac{2 T}{L} \delta_{q_1,-q_2}\delta(t-t') 
</math></center>
The solution of this first order linear equation writes
<center> <math>
\hat h_q(t)= \hat h_q(0) e^{-\nu q^2  t} +\int_0^t d s e^{- \nu q^2 (t-s)} \eta_q(s)
</math></center>
Assume that the interface is initially flat, namely <math> \hat h_q(0) =0 </math>. 
* Compute the width  <math> \langle h(x,t)^2\rangle = \sum_q \langle h_q(t)h_{-q}(t) \rangle  </math>. Comment about the roughness and the short times growth.

Latest revision as of 15:18, 7 August 2025

Introduction: Interfaces and Directed Polymers

The physical properties of many materials are governed by manifolds embedded in them. Examples include: dislocations in crystals, domain walls in ferromagnets or vortex lines in superconductors. We fix the following notation: - : spatial dimension of the embedding medium – : internal dimension of the manifold – : dimension of the displacement (or height) field

These satisfy the relation:

We focus on two important cases:

Directed Polymers (d = 1)

The configuration is described by a vector function: , where is the internal coordinate. The polymer lives in dimensions.

Examples: vortex lines, DNA strands, fronts.

Although polymers may form loops, we restrict to directed polymers, i.e., configurations without overhangs or backward turns.

Interfaces (N = 1)

The interface is described by a scalar height field: , where is the internal coordinate and represents time.

Examples: domain walls and propagating fronts

Again we neglect overhangs or pinch-off: is single-valued

Note that using our notation the 1D front is both an interface and a directed polymer

Thermal Interfaces

  • The dynamics is overdamped, so that we can neglect the inertial term.

The Langevin equation of motion is

The first term is the elastic force trying to smooth the interface, the mobility is the inverse of the viscosity. The second term is the Langevin noise. It is Guassian and defined by

The symbol indicates the average over the thermal noise and the diffusion constant is fixed by the Einstein relation . We set

The potential energy of surface tension ( is the stiffness) can be expanded at the lowest order in the gradient:

Hence, we have the Edwards Wilkinson equation:

Scaling Invariance

The equation enjoys of a continuous symmetry because and cannot be distinguished. This is a condition of scale invariance:

Here are the dynamic and the roughness exponent respectively. From dimensional analysis

From which you get in any dimension and a rough interface below with .

Explicit Solution

For simplicity, consider a 1-dimensional line of size L with periodic boundary conditions. It is useful to introduce the Fourier modes:

Here and recall .

  • Show that the EW equation writes

The solution of this first order linear equation writes

Assume that the interface is initially flat, namely .

  • Compute the width . Comment about the roughness and the short times growth.