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= Interfaces and manifolds =
= Interfaces and manifolds =


Many physical systems are governed by elastic manifolds embedded in a higher-dimensional
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.
medium. Typical examples include domain walls in ferromagnets, dislocations in crystals,
vortex lines in superconductors, and propagating fronts.


We introduce the following notation:
We introduce the following notation:


* <math>d</math>: internal dimension of the manifold
* <math>d</math>: internal dimension of the manifold
* <math>N</math>: dimension of the displacement (or height) field
* <math>N</math>: dimension of the displacement (or height) field
* <math>D</math>: dimension of the embedding space
* <math>D</math>: dimension of the embedding space


These satisfy
These satisfy
<center><math>D = d + N</math></center>
<math display="block">D = d + N</math>


Two important cases are:
Two important cases are:


* '''Interfaces''' (<math>N = 1</math>):
* '''Interfaces''' (<math>N = 1</math>):
The configuration is described by a scalar height field
The configuration 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.
<math>h(\vec r,t)</math>, where <math>\vec r \in \mathbb{R}^d</math> is the internal coordinate.


* '''Directed polymers''' (<math>d = 1</math>):
* '''Directed polymers''' (<math>d = 1</math>):
The configuration is described by a vector function <math>\vec x(t)</math> embedded in
The configuration is described by a vector function <math>\vec x(t)</math> embedded in <math>D = 1 + N</math> dimensions.
<math>D = 1 + N</math> dimensions.


'''Remark.'''
'''Remark.'''
With this notation, a one-dimensional interface (<math>d=1</math>, <math>N=1</math>)
With this notation, a one-dimensional interface (<math>d=1</math>, <math>N=1</math>) can be viewed both as an interface and as a directed polymer.
can be viewed both as an interface and as a directed polymer.


In this lecture we focus on thermal interfaces.
In this lecture we focus on thermal interfaces.


= Thermal interfaces: Langevin dynamics =
= Thermal interfaces: Langevin dynamics =


We consider an interface at thermal equilibrium at temperature <math>T</math>.
We consider an interface at thermal equilibrium at temperature <math>T</math>. Two assumptions are made:
Two assumptions are made:


* Overhangs and pinch-off are neglected, so <math>h(\vec r,t)</math> is single-valued.
* Overhangs and pinch-off are neglected, so <math>h(\vec r,t)</math> is single-valued.
Line 41: Line 33:


The Langevin equation of motion reads
The Langevin equation of motion reads
<center><math>
<math display="block">
\partial_t h(\vec r,t)
\partial_t h(\vec r,t)
= -\mu \frac{\delta E_{\mathrm{pot}}}{\delta h(\vec r,t)} + \eta(\vec r,t).
= -\mu \frac{\delta E_{\mathrm{pot}}}{\delta h(\vec r,t)} + \eta(\vec r,t).
</math></center>
</math>


Here <math>\mu</math> is the mobility and <math>\eta(\vec r,t)</math> is a Gaussian thermal noise,
Here <math>\mu</math> is the mobility and <math>\eta(\vec r,t)</math> is a Gaussian thermal noise, with
with
<math display="block">
<center><math>
\langle \eta(\vec r,t)\rangle = 0,
\langle \eta(\vec r,t)\rangle = 0,
\qquad
\qquad
\langle \eta(\vec r,t)\eta(\vec r',t')\rangle
\langle \eta(\vec r,t)\eta(\vec r',t')\rangle
= 2 d D \,\delta^d(\vec r-\vec r')\,\delta(t-t').
= 2 d D \,\delta^d(\vec r-\vec r')\,\delta(t-t').
</math></center>
</math>


The diffusion constant is fixed by the Einstein relation
The diffusion constant is fixed by the Einstein relation
<center><math>D = \mu k_B T.</math></center>
<math display="block">D = \mu k_B T.</math>


In the following we set <math>\mu = k_B = 1</math>.
In the following we set <math>\mu = k_B = 1</math>.


== Elastic energy and Edwards–Wilkinson equation ==
== Elastic energy and Edwards–Wilkinson equation ==


The elastic energy associated with surface tension can be written as
The elastic energy associated with surface tension can be written as
<center><math>
<math display="block">
E_{\mathrm{pot}}
E_{\mathrm{pot}}
= \nu \int d^d r \sqrt{1+(\nabla h)^2}
= \nu \int d^d r \sqrt{1+(\nabla h)^2}
\simeq \text{const.} + \frac{\nu}{2}\int d^d r (\nabla h)^2,
\simeq \text{const.} + \frac{\nu}{2}\int d^d r (\nabla h)^2,
</math></center>
</math>
where <math>\nu</math> is the stiffness.
where <math>\nu</math> is the stiffness.


Keeping only the lowest-order term in gradients, the equation of motion becomes
Keeping only the lowest-order term in gradients, the equation of motion becomes the Edwards–Wilkinson (EW) equation:
the Edwards–Wilkinson (EW) equation:
<math display="block">
<center><math>
\partial_t h(\vec r,t) = \nu \nabla^2 h(\vec r,t) + \eta(\vec r,t).
\partial_t h(\vec r,t) = \nu \nabla^2 h(\vec r,t) + \eta(\vec r,t).
</math></center>
</math>


=== 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 <math>h(\vec r,t) \to h(\vec r,t) + c</math>. This symmetry forbids any local term depending on the absolute height and ensures the absence of a characteristic length scale, leading to scale invariance of the form
<math>h(\vec r,t) \to h(\vec r,t) + c</math>. This symmetry forbids any local term depending on the absolute height and ensures the absence of a characteristic length scale, leading to scale invariance of the form
<math display="block">
<center><math>
h(b\vec r, b^z t) \overset{\text{in law}}{\sim} b^\alpha h(\vec r,t),
h(b\vec r, b^z t) \overset{\text{in law}}{\sim} b^\alpha h(\vec r,t),
</math></center>
</math>
where <math>z</math> is the dynamical exponent and <math>\alpha</math> the roughness exponent.
where <math>z</math> is the dynamical exponent and <math>\alpha</math> the roughness exponent.


A simple dimensional analysis gives
A simple dimensional analysis gives
<center><math>
<math display="block">
b^{\alpha-z}\partial_t h
b^{\alpha-z}\partial_t h
= b^{\alpha-2}\nabla^2 h + b^{-d/2-z/2}\eta.
= b^{\alpha-2}\nabla^2 h + b^{-d/2-z/2}\eta.
</math></center>
</math>


From this one finds
From this one finds
<center><math>
<math display="block">
z = 2,
z = 2,
\qquad
\qquad
\alpha = \frac{2-d}{2}.
\alpha = \frac{2-d}{2}.
</math></center>
</math>


Thus the interface is rough for <math>d<2</math> and marginal at <math>d=2</math>.
Thus the interface is rough for <math>d<2</math> and marginal at <math>d=2</math>.
Line 104: Line 91:
== Solution in Fourier space ==
== 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
 
<math display="block">
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)
\hat h_q(t)
= \frac{1}{L}\int_0^L dx\, e^{iqx} h(x,t),
= \frac{1}{L}\int_0^L dx\, e^{iqx} h(x,t),
\qquad
\qquad
h(x,t)=\sum_q e^{-iqx}\hat h_q(t),
h(x,t)=\sum_q e^{-iqx}\hat h_q(t),
</math></center>
</math>
with wavevectors
with wavevectors
<center><math>
<math display="block">
q=\frac{2\pi n}{L},
q=\frac{2\pi n}{L},
\qquad
\qquad
n=\ldots,-1,0,1,\ldots
n=\ldots,-1,0,1,\ldots
</math></center>
</math>


For these discrete wavevectors, the Fourier modes satisfy the orthogonality relation
For these discrete wavevectors, the Fourier modes satisfy the orthogonality relation
<math display="block">\int_0^L dx\, e^{i(q_1+q_2)x} = L\,\delta_{q_1,-q_2}.</math>


<center><math> \int_0^L dx\, e^{i(q_1+q_2)x} = L\,\delta_{q_1,-q_2}. </math></center>
Assuming a spatially and temporally white noise, <math>\langle \eta(x,t)\eta(x',t')\rangle = 2T\,\delta(x-x')\,\delta(t-t')</math>, one finds that the Fourier components of the noise satisfy
<math display="block">\langle \eta_{q_1}(t')\eta_{q_2}(t)\rangle = \frac{2T}{L}\,\delta_{q_1,-q_2}\,\delta(t-t').</math>


Assuming a spatially and temporally white noise, <math> \langle \eta(x,t)\eta(x',t')\rangle = 2T\,\delta(x-x')\,\delta(t-t'), </math> one finds that the Fourier cmponents of the noise satisfy
With these definitions, the Edwards–Wilkinson equation becomes diagonal in Fourier space:
 
<math display="block">
<center><math> \langle \eta_{q_1}(t')\eta_{q_2}(t)\rangle = \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)
\partial_t \hat h_q(t)
= -\nu q^2 \hat h_q(t) + \eta_q(t).
= -\nu q^2 \hat h_q(t) + \eta_q(t).
</math></center>
</math>


The solution of this linear equation is
The solution of this linear equation is
<center><math>
<math display="block">
\hat h_q(t)
\hat h_q(t)
= \hat h_q(0)e^{-\nu q^2 t}
= \hat h_q(0)e^{-\nu q^2 t}
+ \int_0^t ds\, e^{-\nu q^2(t-s)}\eta_q(s).
+ \int_0^t ds\, e^{-\nu q^2(t-s)}\eta_q(s).
</math></center>
</math>


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>
<math display="block">
\langle \hat h_q(t)\hat h_{-q}(t)\rangle
\langle \hat h_q(t)\hat h_{-q}(t)\rangle
=
=
Line 154: Line 134:
& q=0.
& q=0.
\end{cases}
\end{cases}
</math></center>
</math>


The mode <math>q=0</math> corresponds to the spatial average of the height, i.e.\
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,
to the center-of-mass position of the interface.
<math display="block">
Its fluctuations grow diffusively,
<center><math>
\langle \hat h_0(t)^2\rangle = \frac{2T}{L}\,t,
\langle \hat h_0(t)^2\rangle = \frac{2T}{L}\,t,
</math></center>
</math>
with a diffusion constant proportional to <math>1/L</math>, reflecting the fact
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.
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
The modes with <math>q\neq 0</math> describe internal fluctuations of the interface. The relaxation time of a mode of wavevector <math>q</math> scales as
interface. The relaxation time of a mode of wavevector <math>q</math> scales as
<math display="block">\tau_q \sim \frac{1}{\nu q^2}.</math>
<center><math>
\tau_q \sim \frac{1}{\nu q^2}.
</math></center>


Since <math>q</math> has the dimension of an inverse length, this relaxation time suggests the existence of a growing dynamical length scale
Since <math>q</math> has the dimension of an inverse length, this relaxation time suggests the existence of a growing dynamical length scale
<center><math>
<math display="block">
\ell(t) \sim t^{1/z},
\ell(t) \sim t^{1/z},
\qquad z=2,
\qquad z=2,
</math></center>
</math>
such that modes with wavelength smaller than <math>\ell(t)</math>
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. Form dimensional analysis, the equilibrium decay <math>\sim 1/(L q^2)</math> is consistent with the roughness exponent <math>\alpha = 1/2</math>, as expected for the Edwards–Wilkinson universality class in one dimension.
(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.
Form dimensional analysis, the equilibrium decay <math>\sim 1/(L q^2)</math> is consistent with the
roughness exponent <math>\alpha = 1/2</math>, as expected for the
Edwards–Wilkinson universality class in one dimension.


== Width of the interface ==
== Width of the interface ==


The squared width of the interface is defined as
The squared width of the interface is defined as
<center><math>
<math display="block">
w_2(t)
w_2(t)
= \int_0^L \frac{dr}{L}
= \int_0^L \frac{dr}{L}
Line 192: Line 161:
h(r,t) - \int_0^L \frac{dr}{L} h(r,t)
h(r,t) - \int_0^L \frac{dr}{L} h(r,t)
\right]^2.
\right]^2.
</math></center>
</math>


Using the Fourier decomposition and Parseval’s theorem, one finds
Using the Fourier decomposition and Parseval’s theorem, one finds
<center><math>
<math display="block">w_2(t) = \sum_{q\neq 0} |\hat h_q(t)|^2.</math>
w_2(t) = \sum_{q\neq 0} |\hat h_q(t)|^2.
</math></center>


Taking the average over the thermal noise yields
Taking the average over the thermal noise yields
<center><math>
<math display="block">
\langle w_2(t)\rangle
\langle w_2(t)\rangle
= \frac{T}{L\nu}
= \frac{T}{L\nu}
\sum_{q\neq 0}\frac{1-e^{-2\nu q^2 t}}{q^2}.
\sum_{q\neq 0}\frac{1-e^{-2\nu q^2 t}}{q^2}.
</math></center>
</math>


For periodic boundary conditions, with <math>q = 2\pi n/L</math>, this can be
For periodic boundary conditions, with <math>q = 2\pi n/L</math>, this can be rewritten as
rewritten as
<math display="block">
<center><math>
\langle w_2(t)\rangle
\langle w_2(t)\rangle
= \frac{T L}{2\pi^2\nu}
= \frac{T L}{2\pi^2\nu}
\sum_{n=1}^{\infty}
\sum_{n=1}^{\infty}
\frac{1-e^{-8\pi^2\nu t n^2/L^2}}{n^2}.
\frac{1-e^{-8\pi^2\nu t n^2/L^2}}{n^2}.
</math></center>
</math>
 
 


=== Long-time behavior ===
=== Long-time behavior ===


At long times, <math>t \gg L^2</math>, all modes have relaxed and the exponential
At long times, <math>t \gg L^2</math>, all modes have relaxed and the exponential term can be neglected. One obtains
term can be neglected. One obtains
<math display="block">
<center><math>
\langle w_2(t)\rangle
\langle w_2(t)\rangle
\sim \frac{T L}{2\pi^2\nu}
\sim \frac{T L}{2\pi^2\nu}
\sum_{n=1}^{\infty}\frac{1}{n^2}
\sum_{n=1}^{\infty}\frac{1}{n^2}
= \frac{T}{\nu}\frac{L}{12}.
= \frac{T}{\nu}\frac{L}{12}.
</math></center>
</math>


Thus the width saturates at a value proportional to the system size.
Thus the width saturates at a value proportional to the system size.
Line 232: Line 195:
=== Short-time behavior ===
=== Short-time behavior ===


At short times, <math>t \ll L^2</math>, the sum can be approximated by an integral.
At short times, <math>t \ll L^2</math>, the sum can be approximated by an integral. Replacing <math>\sum_n \to \frac{L}{2\pi}\int dq</math>, one finds
Replacing
<math display="block">
<math>\sum_n \to \frac{L}{2\pi}\int dq</math>, one finds
<center><math>
\langle w_2(t)\rangle
\langle w_2(t)\rangle
\simeq \frac{T}{\nu}
\simeq \frac{T}{\nu}
\int_0^{\infty} \frac{dq}{2\pi}
\int_0^{\infty} \frac{dq}{2\pi}
\frac{1-e^{-2\nu q^2 t}}{q^2}.
\frac{1-e^{-2\nu q^2 t}}{q^2}.
</math></center>
</math>


Evaluating the integral gives
Evaluating the integral gives
<center><math>
<math display="block">
\langle w_2(t)\rangle
\langle w_2(t)\rangle
\sim T\sqrt{\frac{2t}{\pi\nu}},
\sim T\sqrt{\frac{2t}{\pi\nu}},
\qquad t \ll L^2.
\qquad t \ll L^2.
</math></center>
</math>

Latest revision as of 15:41, 1 March 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 forbids any local term depending on the absolute height and ensures the absence of a characteristic length scale, leading 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.

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,

For these discrete wavevectors, the Fourier modes satisfy the orthogonality relation 0Ldxei(q1+q2)x=Lδq1,q2.

Assuming a spatially and temporally white noise, η(x,t)η(x,t)=2Tδ(xx)δ(tt), one finds that 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. The relaxation time of a mode of wavevector q scales as τq1νq2.

Since q has the dimension of an inverse length, this relaxation time 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. Form dimensional analysis, the equilibrium decay 1/(Lq2) is consistent with the roughness exponent α=1/2, as expected for the Edwards–Wilkinson universality class in one dimension.

Width of the interface

The squared width of the interface is defined as w2(t)=0LdrL[h(r,t)0LdrLh(r,t)]2.

Using the Fourier decomposition and Parseval’s theorem, one finds w2(t)=q0|h^q(t)|2.

Taking the average over the thermal noise yields w2(t)=TLνq01e2νq2tq2.

For periodic boundary conditions, with q=2πn/L, this can be rewritten as w2(t)=TL2π2νn=11e8π2νtn2/L2n2.

Long-time behavior

At long times, tL2, all modes have relaxed and the exponential term can be neglected. One obtains w2(t)TL2π2νn=11n2=TνL12.

Thus the width saturates at a value proportional to the system size.

Short-time behavior

At short times, tL2, the sum can be approximated by an integral. Replacing nL2πdq, one finds w2(t)Tν0dq2π1e2νq2tq2.

Evaluating the integral gives w2(t)T2tπν,tL2.