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Problem H.1: freezing as a localization/condensation transition
In this problem, we show how the freezing transition can be understood in terms of extreme valued statistics (discussed in the lecture) and localization. We consider the energies of the configurations and define , so that
We show that is a sum of random variables that become heavy tailed for , implying that the central limit theorem is violated and this sum is dominated by few terms, the largest ones. This can be interpreted as the occurrence of localization (or condensation).
- Heavy tails and concentration. Compute the distribution of the variables Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \delta E_\alpha }
and show that for this is an exponential. Using this, compute the distribution of the Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle z_\alpha }
and show that it is a power law,
When , one has : the distribution of becomes heavy tailed. What does this imply for the sum ? Is this consistent with the behaviour of the partition function and of the entropy discussed in Problem 2? Why can one talk about a localization or condensation transition?
- Inverse participation ratio. The low temperature behaviour of the partition function an be characterized in terms of a standard measure of localization (or condensation), the Inverse Participation Ratio (IPR) defined as:
When is power law distributed with exponent , one can show (HOMEWORK!) that
Discuss how this quantity changes across the transition at , and how this fits with what you expect in general in a localized phase.