L2 ICFP: Difference between revisions

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== Solution in Fourier space ==
== Solution in Fourier space ==


The EW equation in Fourier space reads
=== Solution in Fourier space ===
 
We now focus on a one-dimensional interface (<math>d=1</math>) of size <math>L</math>
with periodic boundary conditions.
 
We use the Fourier decomposition
<center><math>
\hat h_q(t)
= \frac{1}{L}\int_0^L dx\, e^{iqx} h(x,t),
\qquad
h(x,t)=\sum_q e^{-iqx}\hat h_q(t),
</math></center>
with wavevectors
<center><math>
<center><math>
\partial_t \hat h_q(t)
q=\frac{2\pi n}{L},
= -\nu q^2 \hat h_q(t) + \eta_q(t),
\qquad
n=\ldots,-1,0,1,\ldots
</math></center>
</math></center>
with noise correlations
 
The Fourier components of the noise satisfy
<center><math>
<center><math>
\langle \eta_{q_1}(t')\eta_{q_2}(t)\rangle
\langle \eta_{q_1}(t')\eta_{q_2}(t)\rangle
= \frac{2T}{L}\delta_{q_1,-q_2}\delta(t-t').
= \frac{2T}{L}\,\delta_{q_1,-q_2}\,\delta(t-t').
</math></center>
 
With these definitions, the Edwards–Wilkinson equation becomes diagonal in
Fourier space:
<center><math>
\partial_t \hat h_q(t)
= -\nu q^2 \hat h_q(t) + \eta_q(t).
</math></center>
</math></center>


The solution is
The solution of this linear equation is
<center><math>
<center><math>
\hat h_q(t)
\hat h_q(t)
Line 155: Line 176:
</math></center>
</math></center>


Assuming a flat initial condition <math>\hat h_q(0)=0</math>, one finds
Assuming a flat initial condition, <math>\hat h_q(0)=0</math>, one finds
<center><math>
<center><math>
\langle \hat h_q(t)\hat h_{-q}(t)\rangle
\langle \hat h_q(t)\hat h_{-q}(t)\rangle
=
=
\begin{cases}
\begin{cases}
\dfrac{T(1-e^{-2\nu q^2 t})}{L\nu q^2}, & q\neq 0,\\[1.2em]
\dfrac{T\bigl(1-e^{-2\nu q^2 t}\bigr)}{L\nu q^2},
\dfrac{2T}{L}t, & q=0.
& q\neq 0, \\[1.2em]
\dfrac{2T}{L}\,t,
& q=0.
\end{cases}
\end{cases}
</math></center>
</math></center>


---
The mode <math>q=0</math> corresponds to the spatial average of the height, i.e.\
to the center-of-mass position of the interface.
Its fluctuations grow diffusively,
<center><math>
\langle \hat h_0(t)^2\rangle = \frac{2T}{L}\,t,
</math></center>
with a diffusion constant proportional to <math>1/L</math>, reflecting the fact
that the interface is composed of <math>L</math> degrees of freedom.
 
The modes with <math>q\neq 0</math> describe internal fluctuations of the
interface.
Since <math>q</math> has the dimension of an inverse length, the relaxation time
of a mode of wavevector <math>q</math> scales as
<center><math>
\tau_q \sim \frac{1}{\nu q^2}.
</math></center>
 
This suggests the existence of a growing dynamical length scale
<center><math>
\ell(t) \sim t^{1/z},
\qquad z=2,
</math></center>
such that modes with wavelength smaller than <math>\ell(t)</math>
(i.e. <math>q \gg 1/\ell(t)</math>) have already equilibrated, while at longer
wavelengths the interface still retains memory of the initial flat condition.
 
Note that the dimension of the observable
<math>\langle |\hat h_q(t)|^2 \rangle</math>
is that of <math>h^2 \times \text{length}</math>.
The equilibrium decay <math>\sim 1/q^2</math> is therefore consistent with the
roughness exponent <math>\zeta = 1/2</math>, as expected for the
Edwards–Wilkinson universality class in one dimension.


== Growth and saturation of the width ==
== Growth and saturation of the width ==

Revision as of 20:11, 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:

  • d: internal dimension of the manifold
  • N: dimension of the displacement (or height) field
  • D: dimension of the embedding space

These satisfy

D=d+N

Two important cases are:

  • Interfaces (N=1):

The configuration is described by a scalar height field h(r,t), where rd is the internal coordinate.

  • Directed polymers (d=1):

The configuration is described by a vector function x(t) embedded in D=1+N dimensions.

Remark. With this notation, a one-dimensional interface (d=1, N=1) 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 T. Two assumptions are made:

  • Overhangs and pinch-off are neglected, so h(r,t) is single-valued.
  • The dynamics is overdamped; inertial effects are neglected.

The Langevin equation of motion reads

th(r,t)=μδEpotδh(r,t)+η(r,t).

Here μ is the mobility and η(r,t) is a Gaussian thermal noise, with

η(r,t)=0,η(r,t)η(r,t)=2dDδd(rr)δ(tt).

The diffusion constant is fixed by the Einstein relation

D=μkBT.

In the following we set μ=kB=1.


Elastic energy and Edwards–Wilkinson equation

The elastic energy associated with surface tension can be written as

Epot=νddr1+(h)2const.+ν2ddr(h)2,

where ν is the stiffness.

Keeping only the lowest-order term in gradients, the equation of motion becomes the Edwards–Wilkinson (EW) equation:

th(r,t)=ν2h(r,t)+η(r,t).

Symmetries and scaling invariance

The EW equation is invariant under global height shifts h(r,t)h(r,t)+c. This symmetry leads to scale invariance of the form

h(br,bzt)in lawbαh(r,t),

where z is the dynamical exponent and α the roughness exponent.

A simple dimensional analysis gives

bαzth=bα22h+bd/2z/2η.

From this one finds

z=2,α=2d2.

Thus the interface is rough for d<2 and marginal at d=2.

---

Width of the interface

We now focus on a one-dimensional interface (d=1) of size L with periodic boundary conditions.

The squared width is defined as

w2(t)=0LdrL(h(r,t)0LdrLh(r,t))2.

Introduce Fourier modes

h^q(t)=1L0Ldreiqrh(r,t),h(r,t)=qeiqrh^q(t),

with q=2πn/L.

Using Parseval’s theorem one finds

w2(t)=q0|h^q(t)|2.

---

Solution in Fourier space

Solution in Fourier space

We now focus on a one-dimensional interface (d=1) of size L with periodic boundary conditions.

We use the Fourier decomposition

h^q(t)=1L0Ldxeiqxh(x,t),h(x,t)=qeiqxh^q(t),

with wavevectors

q=2πnL,n=,1,0,1,

The Fourier components of the noise satisfy

ηq1(t)ηq2(t)=2TLδq1,q2δ(tt).

With these definitions, the Edwards–Wilkinson equation becomes diagonal in Fourier space:

th^q(t)=νq2h^q(t)+ηq(t).

The solution of this linear equation is

h^q(t)=h^q(0)eνq2t+0tdseνq2(ts)ηq(s).

Assuming a flat initial condition, h^q(0)=0, one finds

h^q(t)h^q(t)={T(1e2νq2t)Lνq2,q0,2TLt,q=0.

The mode q=0 corresponds to the spatial average of the height, i.e.\ to the center-of-mass position of the interface. Its fluctuations grow diffusively,

h^0(t)2=2TLt,

with a diffusion constant proportional to 1/L, reflecting the fact that the interface is composed of L degrees of freedom.

The modes with q0 describe internal fluctuations of the interface. Since q has the dimension of an inverse length, the relaxation time of a mode of wavevector q scales as

τq1νq2.

This suggests the existence of a growing dynamical length scale

(t)t1/z,z=2,

such that modes with wavelength smaller than (t) (i.e. q1/(t)) have already equilibrated, while at longer wavelengths the interface still retains memory of the initial flat condition.

Note that the dimension of the observable |h^q(t)|2 is that of h2×length. The equilibrium decay 1/q2 is therefore consistent with the roughness exponent ζ=1/2, as expected for the Edwards–Wilkinson universality class in one dimension.

Growth and saturation of the width

The mean squared width evolves as

w2(t)=TLνq01e2νq2tq2.

In the continuum limit this gives

w2(t)={T2tπν,tL2,TνL12,tL2.

At short times the interface roughens algebraically, while at long times the width saturates due to the finite system size.