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| '''Note''' that using our notation the 1D front is both an interface and a directed polymer | | '''Note''' that using our notation the 1D front is both an interface and a directed polymer |
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| =Thermal Interfaces=
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|
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| The dynamics is overdamped, so that we can neglect the inertial term. The Langevin equation of motion is
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| <center> <math>
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| \partial_t h(r,t)= - \mu \frac{\delta E_{pot}}{\delta h(r,t)} + \eta(r,t)
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| </math></center>
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| 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
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| <center> <math>
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| \langle \eta(r,t) \rangle =0, \; \langle \eta(r',t')\eta(r,t) \rangle = 2 d D \delta^d(r-r') \delta(t-t')
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| </math></center>
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| 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>
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| D= \mu K_B T
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| </math>. We set <math> \mu= K_B=1</math>
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|
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| The potential energy of surface tension (<math>\nu </math> is the stiffness) can be expanded at the lowest order in the gradient:
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| <center> <math>
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| E_{pot} \sim \text{const.} + \frac{\nu}{2} \int d^d r (\nabla h)^2
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| </math></center>
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| Hence, we have the Edwards Wilkinson equation:
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| <center> <math>
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| \partial_t h(r,t)= \nu \nabla^2 h(r,t) + \eta(r,t)
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| </math></center>
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| === Scaling Invariance===
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| 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:
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| <center> <math>
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| h(b r, b^z t) \overset{in law}{\sim} b^{\alpha} h(r,t)
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| </math></center>
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| Here <math>
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| z, \alpha
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| </math> are the dynamic and the roughness exponent respectively. From dimensional analysis
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| <center> <math>
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| b^{\alpha-z} \partial_t h(r,t)= b^{\alpha-2} \nabla^2 h(r,t) +b^{-d/2-z/2} \eta(r,t)
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| </math></center>
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| 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>.
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|
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| == Width of the interface ==
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|
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| Consider a 1-dimensional line of size L with periodic boundary conditions.
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| We consider the width square of the interface
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| <center> <math>
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| w_2(t) = \left[\int_0^L \frac{d r}{L} \left(h(r,t) - \int_0^L \frac{dr}{L} h(r,t)\right)\right]^2
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| </math></center>
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| It is useful to introduce the Fourier modes:
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| <center> <math>
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| \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)
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| </math></center>
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| 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>.
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| using de Parseval theorem for the Fourier series
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| <center> <math>
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| w_2(t) = \sum_{q\ne 0} |\hat h_q(t)|^2 =\sum_{q\ne 0} \left(\hat h_q(t) \hat h_{-q}(t)\right) ^2
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| </math></center>
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| In the last step we used that <math>
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| \hat h_q^*(t)= \hat h_{-q}(t)
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| </math>.
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|
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| === Solution in the Fourier space===
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| show that the EW equation writes
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| <center> <math>
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| \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')
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| </math></center>
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| The solution of this first order linear equation writes
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| <center> <math>
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| \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)
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| </math></center>
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|
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| * Assume that the interface is initially flat, namely <math> \hat h_q(0) =0 </math>. Show that
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| <center> <math>
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| \langle \hat h_q(t) \hat h_{-q}(t) \rangle =\begin{cases}
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| \dfrac{T(1 - e^{-2\nu q^{2}t})}{L \nu q^{2}}, & q \neq 0, \\[1.2em]
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| \frac{2 T}{L} t, & q = 0.
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| \end{cases}
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| </math></center>
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|
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| *The mean width square grows at short times and saturates at long times:
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| <center> <math>
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| \langle w_2(t)\rangle = \dfrac{T}{L \nu }\sum_{q\ne 0} \dfrac{1 - e^{-2\nu q^{2}t}}{q^{2}} =\begin{cases}
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| T \sqrt{\frac{2 t}{\pi \nu}}, & t\ll L^2, \\[1.2em]
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| \frac{T}{ \nu} \frac{L}{12} , & t\gg L^2.
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| \end{cases}
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| </math></center>
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| =Directed polymers in random media= | | =Directed polymers in random media= |
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
Directed polymers in random media
We now reanalyze the previous problem in the presence of quenched disorder.
Instead of discussing the case of interfaces, we will focus on directed polymers.
Let us consider polymers
of length
.
The energy associated with a given polymer configuration can be written as
The first term describes the elastic energy of the polymer,
while the second one is the disordered potential, which we assume to be
where 'D' is the disorder strength.
Polymer partition function and propagator of a quantum particle
Let us consider polymers starting in
, ending in
and at thermal equilibrium at temperature
. The partition function of the model writes as
Here, the partition function is written as a sum over all possible paths, corresponding to all possible polymer configurations that start at
and end at
, weighted by the appropriate Boltzmann factor.
Let's perform the following change of variables:
. We also identifies
with
and
as the time.
Note that
is the classical action of a particle with kinetic energy
and time dependent potential
, evolving from time zero to time
.
From the Feymann path integral formulation,
is the propagator of the quantum particle.
Feynman-Kac formula
Let's derive the Feyman Kac formula for
in the general case:
- First, focus on free paths and introduce the following probability
- Second, the moments generating function
- Third, consider free paths evolving up to
and reaching
:
Here
is the average over all free paths, while
is the average over the last jump, namely
and
.
- At the lowest order we have
Replacing
we obtain the partition function is the solution of the Schrodinger-like equation:
Remark 1:
This equation is a diffusive equation with multiplicative noise
. Edwards Wilkinson is instead a diffusive equation with additive noise.
Remark 2:
This hamiltonian is time dependent because of the multiplicative noise
. For a time independent hamiltonian, we can use the spectrum of the operator. In general we will have to parts:
- A discrete set of eigenvalues
with the eigenstates 
- A continuum part where the states
have energy
. We define the density of states
, such that the number of states with energy in (
) is
.
In this case
can be written has the sum of two contributions:
In absence of disorder, one can find the propagator of the free particle, that, in the original variables, writes:
