TBan-II: Difference between revisions
(Created page with "==Dijkstra Algorithm and transfer matrix== thumb|left|Sketch of the discrete Directed Polymer model. At each time the polymer grows either one step left either one step right. A random energy <math> V(\tau,x)</math> is associated at each node and the total energy is simply <math> E[x(\tau)] =\sum_{\tau=0}^t V(\tau,x)</math>. We introduce a lattice model for the directed polymer (see figure). In a companion notebook we provide the implementa...") |
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= | =Thermal Interfaces= | ||
The dynamics is overdamped, so that we can neglect the inertial term. The Langevin equation of motion is | |||
<center> <math> | |||
\partial_t h(r,t)= - \mu \frac{\delta E_{pot}}{\delta h(r,t)} + \eta(r,t) | |||
</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 the inverse of the viscosity. The second term is the Langevin noise. It is Guassian and defined by | |||
<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') | |||
</math></center> | |||
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> | |||
D= \mu K_B T | |||
</math>. We set <math> \mu= K_B=1</math> | |||
The potential energy of surface tension (<math>\nu </math> is the stiffness) can be expanded at the lowest order in the gradient: | |||
<center> <math> | |||
E_{pot} \sim \text{const.} + \frac{\nu}{2} \int d^d r (\nabla h)^2 | |||
</math></center> | |||
Hence, we have the Edwards Wilkinson equation: | |||
<center> <math> | <center> <math> | ||
\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> | |||
<center> | h(b r, b^z t) \overset{in law}{\sim} b^{\alpha} h(r,t) | ||
<math> | </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> | </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>. | |||
== Width of the interface == | |||
< | Consider a 1-dimensional line of size L with periodic boundary conditions. | ||
We consider the width square of the interface | |||
<center> <math> | |||
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 | |||
</math></center> | |||
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>. | |||
using de Parseval theorem for the Fourier series | |||
<center> <math> | |||
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 | |||
</math></center> | |||
In the last step we used that <math> | |||
\hat h_q^*(t)= \hat h_{-q}(t) | |||
</math>. | |||
< | === Solution in the Fourier space=== | ||
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>. Show that | ||
<center> <math> | |||
\langle \hat h_q(t) \hat h_{-q}(t) \rangle =\begin{cases} | |||
\dfrac{T(1 - e^{-2\nu q^{2}t})}{L \nu q^{2}}, & q \neq 0, \\[1.2em] | |||
\frac{2 T}{L} t, & q = 0. | |||
\end{cases} | |||
</math></center> | |||
*The mean width square grows at short times and saturates at long times: | |||
<center> | <center> <math> | ||
<math> | \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} | ||
\ | T \sqrt{\frac{2 t}{\pi \nu}}, & t\ll L^2, \\[1.2em] | ||
\frac{T}{ \nu} \frac{L}{12} , & t\gg L^2. | |||
\end{cases} | |||
\ | |||
</math></center> | </math></center> | ||
Latest revision as of 04:44, 16 September 2025
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 .
Width of the interface
Consider a 1-dimensional line of size L with periodic boundary conditions. We consider the width square of the interface
It is useful to introduce the Fourier modes:
Here and recall . using de Parseval theorem for the Fourier series
In the last step we used that .
Solution in the Fourier space
show that the EW equation writes
The solution of this first order linear equation writes
- Assume that the interface is initially flat, namely . Show that
- The mean width square grows at short times and saturates at long times: