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| =Exercise 1: Back to REM=
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| The Random Energy Model (REM) exhibits two distinct phases:
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| * '''High-Temperature Phase:'''
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| : At high temperatures, the system is in a paramagnetic phase where the entropy is extensive, and the occupation probability of a configuration is approximately <math>\sim 1/M</math>.
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| * '''Low-Temperature Phase:'''
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| : Below a critical freezing temperature <math>T_f</math>, the system transitions into a glassy phase. In this phase, the entropy becomes subextensive (i.e., the extensive contribution vanishes), and only a few configurations are visited with finite, <math>M</math>-independent probabilities.
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| ''' Calculating the Freezing Temperature <math>T_f</math>'''
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| Thanks to the computation of <math>\overline{n(x)}</math>, we can identify the fingerprints of the glassy phase and calculate <math>T_f</math>.
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| Let's compare the weight of the ground state against the weight of all other states:
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| <center>
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| <math>
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| \frac{\sum_\alpha z_\alpha}{z_{\alpha_{\min}}} = 1 + \sum_{\alpha \ne \alpha_{\min}} \frac{z_\alpha}{z_{\alpha_{\min}}} = 1 + \sum_{\alpha \ne \alpha_{\min}} e^{-\beta(E_\alpha - E_\min)} \sim 1 + \int_0^\infty dx\, \frac{d\overline{n(x)}}{dx} \, e^{-\beta x}= 1+ \int_0^\infty dx\, \frac{e^{x/b_M}}{b_M} \, e^{-\beta x}
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| </math>
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| </center>
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| === Behavior in Different Phases:===
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| * '''High-Temperature Phase (<math> T > T_f= b_M = 1/\sqrt{2 \log2}</math>):'''
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| : In this regime, the weight of the excited states diverges. This indicates that the ground state is not deep enough to render the system glassy.
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| * '''Low-Temperature Phase (<math> T < T_f= b_M = 1/\sqrt{2 \log2}</math>):'''
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| : In this regime, the integral is finite:
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| <center>
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| <math>
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| \int_0^\infty dx \, e^{ (1/b_M-\beta) x}/b_M = \frac{1}{\beta b_M-1} = \frac{T}{T_f - T}
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| </math>
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| </center>
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| This result implies that below the freezing temperature <math>T_f</math>, the weight of all excited states is of the same order as the weight of the ground state. Consequently, the ground state is occupied with a finite probability, reminiscent of Bose-Einstein condensation.
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| = Exercise 2: Edwards-Wilkinson Interface with Stationary Initial Condition = | | = Exercise 2: Edwards-Wilkinson Interface with Stationary Initial Condition = |
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| '''Questions:''' | | '''Questions:''' |
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| # '''Compute''' the ensemble average of the Gaussian initial condition:
| | * '''Compute''' the ensemble average of the Gaussian initial condition: |
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| <center><math> | | <center><math> |
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| </math></center> | | </math></center> |
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| *Hint:* Write the integral in terms of Fourier modes and use <math>\int_0^L dx \, e^{iqx} = L \delta_{q,0}</math>.
| | '''Hint:''' Write the integral in terms of Fourier modes and use <math>\int_0^L dx \, e^{iqx} = L \delta_{q,0}</math>. |
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| # '''Show''' that:
| | * '''Show''' that: |
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| <center><math> | | <center><math> |
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| </math></center> | | </math></center> |
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| # '''Show''' that:
| | * '''Show''' that: |
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| <center><math> | | <center><math> |
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| </math></center> | | </math></center> |
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| # '''Hence''' write:
| | * '''Hence''' write: |
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| <center><math> | | <center><math> |
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| Estimate <math>C(t)</math> for <math>t \gg L^2</math>. | | Estimate <math>C(t)</math> for <math>t \gg L^2</math>. |
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| # Estimate <math>C(t)</math> for <math>t \ll L^2</math> and large <math>L</math>.
| | * Estimate <math>C(t)</math> for <math>t \ll L^2</math> and large <math>L</math>. |
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| *Hint:* Write the series as an integral using the continuum variable <math>z = 2 \pi n / L</math>. It is helpful to know:
| | '''Hint:''' Write the series as an integral using the continuum variable <math>z = 2 \pi n / L</math>. It is helpful to know: |
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| <center><math> | | <center><math> |
Latest revision as of 13:36, 16 September 2025
Exercise 2: Edwards-Wilkinson Interface with Stationary Initial Condition
Consider an Edwards-Wilkinson interface in 1+1 dimensions, at temperature
, and of length
with periodic boundary conditions:
where
is a Gaussian white noise with zero mean and variance:
The solution can be written in Fourier space as:
with Fourier decomposition:
where
.
In class, we computed the width of the interface starting from a flat interface at
, i.e.,
. The mean square displacement of a point
is similar but includes also the contribution of the zero mode. The result is:
The first term describes the diffusion of the center of mass, while the second comes from the non-zero Fourier modes.
Now consider the case where the initial interface
is drawn from the equilibrium distribution at temperature
:
For simplicity, set the initial center of mass to zero:
.
We consider the mean square displacement of the point
.
The average is performed over both the thermal noise
and the initial condition
:
Questions:
- Compute the ensemble average of the Gaussian initial condition:
Hint: Write the integral in terms of Fourier modes and use
.
where the term
depends only on the initial condition. Show that:
Estimate
for
.
- Estimate
for
and large
.
Hint: Write the series as an integral using the continuum variable
. It is helpful to know:
Provide the two asymptotic behaviors of
.