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Nei seguente esercizio useremo le notazioni della statistica dei valori estremi usate nel corso. | Nei seguente esercizio useremo le notazioni della statistica dei valori estremi usate nel corso. | ||
= | = Exercise 1: The Gumbel Distribution = | ||
In the spirit of the central limit theorem, you look for a scaling form: | |||
<center><math> E_{\min} = a_M + b_M z </math></center> | |||
Revision as of 14:41, 31 August 2025
Nei seguente esercizio useremo le notazioni della statistica dei valori estremi usate nel corso.
Exercise 1: The Gumbel Distribution
In the spirit of the central limit theorem, you look for a scaling form:
Therefore, the variable is distributed according to an M-independent distribution.
It is possible to generalize this result and classify the scaling forms into the Gumbel universality class:
- Characteristics:
- Applies when the tails of decay faster than any power law.
- Examples: the Gaussian case discussed here or exponential distributions .
- Scaling Form:
esercizio 2: The weakest link
Exercise 3: number of states above the minimum
Definition of :Given a realization of the random energies , define
that is, the number of random variables lying above the minimum
but less than
. This is itself a random variable. We are interested in its mean value:
The Final goal is to show that, for large M (when the extremes are described by the Gumbel distribution), you have:
Step 1: Exact manipulations: You start from the exact expression for the probability of states in the interval:
To compute , you must sum over . Use the identity
to arrive at the form:
where .
Step 2: the Gumbel limit So far, no approximations have been made. To proceed, we use and its asymptotics Gumbel form:
where .
The main contribution to the integral comes from the region near , where .
Compute the integral and verify that you obtain: