T-9: Difference between revisions
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\Gamma_a= \sum_{b \in \partial a} t_{ab}^2 \frac{\Gamma_b + \eta}{(E- W\, V_b - R_b)^2+ (\Gamma_b +\eta)^2}, \quad \quad R_a = \sum_{b \in \partial a} t_{ab}^2 \frac{E- W\, V_b - R_b}{(E- W\, V_b - R_b)^2+ (\Gamma_b +\eta)^2} | \Gamma_a= \sum_{b \in \partial a} t_{ab}^2 \frac{\Gamma_b + \eta}{(E- W\, V_b - R_b)^2+ (\Gamma_b +\eta)^2}, \quad \quad R_a = \sum_{b \in \partial a} t_{ab}^2 \frac{E- W\, V_b - R_b}{(E- W\, V_b - R_b)^2+ (\Gamma_b +\eta)^2} | ||
</math> | </math> | ||
These equations admit the solution <math> \Gamma_a=\Gamma_b=0</math> when <math>\eta=0 </math>, which corresponds to localization. We now determine when this solution becomes unstable. | These equations admit the solution <math> \Gamma_a=\Gamma_b=0</math> when <math>\eta=0 </math>, which corresponds to localization. We now determine when this solution becomes unstable. | ||
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<li><em> Imaginary approximation and distributional equation. </em> We consider the equations for <math> \Gamma_a </math> and neglect the terms <math> R_b </math> in the denominators, which couple the equations to those for the real parts of the self energies (“imaginary” approximation). Moreover, we assume to be in the localized phase, where <math> \Gamma_a \sim \eta \ll 1 </math>. Finally, we set <math> t_{ab} \equiv t </math> and <math> E=0 </math> for simplicity. Show that under these assumptions the probability density for the imaginary part, <math> P_\Gamma(\Gamma)</math>, satisfies for <math> \tau=t/W</math> | <li><em> Imaginary approximation and distributional equation. </em> We consider the equations for <math> \Gamma_a </math> and neglect the terms <math> R_b </math> in the denominators, which couple the equations to those for the real parts of the self energies (“imaginary” approximation). Moreover, we assume to be in the localized phase, where <math> \Gamma_a \sim \eta \ll 1 </math>. Finally, we set <math> t_{ab} \equiv t </math> and <math> E=0 </math> for simplicity. Show that under these assumptions the probability density for the imaginary part, <math> P_\Gamma(\Gamma)</math>, satisfies for <math> \tau=t/W</math> | ||
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P_\Gamma(\Gamma)= \int \prod_{b=1}^k dV_b\,p(V_b)\int \prod_{b=1}^k d\Gamma_b \, P_\Gamma(\Gamma_b) \delta \left(\Gamma - \tau^2 \sum_{b \in \partial a} \frac{\Gamma_b + \eta}{ V_b^2} \right) | P_\Gamma(\Gamma)= \int \prod_{b=1}^k dV_b\,p(V_b)\int \prod_{b=1}^k d\Gamma_b \, P_\Gamma(\Gamma_b) \delta \left(\Gamma - \tau^2 \sum_{b \in \partial a} \frac{\Gamma_b + \eta}{ V_b^2} \right) | ||
</math> | </math> | ||
Show that the Laplace transform of this distribution, <math> \Phi(s)=\int_0^\infty d\Gamma e^{-s \Gamma} P_\Gamma(\Gamma) </math>, satisfies | Show that the Laplace transform of this distribution, <math> \Phi(s)=\int_0^\infty d\Gamma e^{-s \Gamma} P_\Gamma(\Gamma) </math>, satisfies | ||
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\Phi(s)= \left[ \int dV\, p(V) e^{-\frac{s \tau^2 \eta}{V^2}} \Phi \left(\frac{s \tau^2 }{ V^2} \right) \right]^k | \Phi(s)= \left[ \int dV\, p(V) e^{-\frac{s \tau^2 \eta}{V^2}} \Phi \left(\frac{s \tau^2 }{ V^2} \right) \right]^k | ||
</math> | </math> | ||
</li><br> | </li><br> | ||
<li><em> The stability analysis. </em> We now assume to be in the localized phase, when for <math> \eta \to 0 </math> the distribution <math> P_\Gamma(\Gamma) \to \delta (\Gamma)</math>. We wish to check the stability of our assumption. This is done by controlling the tails of the distribution <math> P_\Gamma(\Gamma)</math> for finite <math> \eta </math>. | <li><em> The stability analysis. </em> We now assume to be in the localized phase, when for <math> \eta \to 0 </math> the distribution <math> P_\Gamma(\Gamma) \to \delta (\Gamma)</math>. We wish to check the stability of our assumption. This is done by controlling the tails of the distribution <math> P_\Gamma(\Gamma)</math> for finite <math> \eta </math>. | ||
<ul> | <ul> | ||
<li> | <li> | ||
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<li> Assume more generally that <math>P_\Gamma(\Gamma) \sim \Gamma^{-\alpha}</math> for large <math> \Gamma </math> and--> | <li> Assume more generally that <math>P_\Gamma(\Gamma) \sim \Gamma^{-\alpha}</math> for large <math> \Gamma </math> and--> | ||
Show, using a dimensional analysis argument, that this corresponds to a non-analytic behaviour of the Laplace transform, <math> \Phi(s) \sim 1- A |s|^\beta </math> for <math> s </math> small, with <math> \beta= \alpha-1 </math>. </li> | Show, using a dimensional analysis argument, that this corresponds to a non-analytic behaviour of the Laplace transform, <math> \Phi(s) \sim 1- A |s|^\beta </math> for <math> s </math> small, with <math> \beta= \alpha-1 </math>. </li> | ||
<li> Show that the equation for <math> \Phi(s) </math> gives for <math> s </math> small <math>1- A s^\beta =1- A k \int dV \, p(V) \frac{s^\beta \tau^{2 \beta}}{V^{2 \beta}}+ o(s^\beta) </math>, and therefore this is consistent provided that there exists a <math> \beta </math> solving | <li> Show that the equation for <math> \Phi(s) </math> gives for <math> s </math> small <math>1- A s^\beta =1- A k \int dV \, p(V) \frac{s^\beta \tau^{2 \beta}}{V^{2 \beta}}+ o(s^\beta) </math>, and therefore this is consistent provided that there exists a <math> \beta </math> solving | ||
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1=k \int dV \, p(V) \left(\frac{\tau}{|V|}\right)^{2 \beta} \equiv k I(\beta). | 1=k \int dV \, p(V) \left(\frac{\tau}{|V|}\right)^{2 \beta} \equiv k I(\beta). | ||
</math> | </math> | ||
</li> | |||
</ul> | </ul> | ||
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<li><em> The critical disorder. </em> Consider now local fields <math> V_x </math> taken from a uniform distribution in <math> [-1/2, 1/2] </math>. Compute <math> I(\beta) </math> and show that it is non monotonic, with a local minimum <math> \beta^* </math> in the interval <math> [0, 1/2]</math>. Show that <math> I(\beta^*) </math> increases as the disorder is made weaker and weaker, and thus the transition to delocalisation occurs at the critical value of disorder when <math> I(\beta^*)=k^{-1} </math>. Show that this gives the following estimate for the critical disorder <math>(W/t)_c=1/\tau_c </math> at which the transition to delocalisation occurs: | <li><em> The critical disorder. </em> Consider now local fields <math> V_x </math> taken from a uniform distribution in <math> [-1/2, 1/2] </math>. Compute <math> I(\beta) </math> and show that it is non monotonic, with a local minimum <math> \beta^* </math> in the interval <math> [0, 1/2]</math>. Show that <math> I(\beta^*) </math> increases as the disorder is made weaker and weaker, and thus the transition to delocalisation occurs at the critical value of disorder when <math> I(\beta^*)=k^{-1} </math>. Show that this gives the following estimate for the critical disorder <math>(W/t)_c=1/\tau_c </math> at which the transition to delocalisation occurs: | ||
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\frac{1}{\tau_c} = \, 2 k e \log \left( \frac{1}{2 \tau_c}\right) \sim \, 2 e \, k \log \left(k\right) | \frac{1}{\tau_c} = \, 2 k e \log \left( \frac{1}{2 \tau_c}\right) \sim \, 2 e \, k \log \left(k\right) | ||
</math> | </math> | ||
Why the critical disorder increases with <math> k </math>? | Why the critical disorder increases with <math> k </math>? | ||
</li> | </li> | ||
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Linearization and stability analysis, critical disorder, mobility edge. | Linearization and stability analysis, critical disorder, mobility edge. | ||
== | == To know more == | ||
Latest revision as of 11:38, 11 March 2026
Goal: the goal of this problem is to determine when the solution of the distributional equations corresponding to localization is unstable, providing an estimate of thee mobility edge on the Bethe lattice.
Techniques: stability analysis, Laplace transforms.
Problems
In this Problem we determine for which values of parameters localization is stable, estimating the critical value of disorder where the transition to a delocalised phase occurs. Recall the results of Problem 8: the real and imaginary parts of the local self energy satisfy the self-consistent equations:
These equations admit the solution when , which corresponds to localization. We now determine when this solution becomes unstable.
Problem 9: an estimate of the mobility edge
- Imaginary approximation and distributional equation. We consider the equations for and neglect the terms in the denominators, which couple the equations to those for the real parts of the self energies (“imaginary” approximation). Moreover, we assume to be in the localized phase, where . Finally, we set and for simplicity. Show that under these assumptions the probability density for the imaginary part, , satisfies for Show that the Laplace transform of this distribution, , satisfies
- The stability analysis. We now assume to be in the localized phase, when for the distribution . We wish to check the stability of our assumption. This is done by controlling the tails of the distribution for finite .
- For finite , we expect that typically , and thus should have a peak at this scale; however, we also expect [*] some power law decay for large . Show, using a dimensional analysis argument, that this corresponds to a non-analytic behaviour of the Laplace transform, for small, with .
- Show that the equation for gives for small , and therefore this is consistent provided that there exists a solving

Behaviour of the integral in the case of uniformily distributed disorder, for . - The critical disorder. Consider now local fields taken from a uniform distribution in . Compute and show that it is non monotonic, with a local minimum in the interval . Show that increases as the disorder is made weaker and weaker, and thus the transition to delocalisation occurs at the critical value of disorder when . Show that this gives the following estimate for the critical disorder at which the transition to delocalisation occurs: Why the critical disorder increases with ?
- [*] - Why do we expect power law tails? Recall that in first approximation . If is uniformly distributed, then .
Check out: key concepts
Linearization and stability analysis, critical disorder, mobility edge.