TBan-I: Difference between revisions

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<center><math> n(x) = \#\{ i \mid E_{\min} < E_i < E_{\min}+x \} </math></center> that is, the number of random variables lying above the minimum <math>E_{\min}</math> but less than <math>E_{\min}+x</math>. This is itself a random variable. We are interested in its mean value: <center><math> \overline{n(x)} = \sum_{k=0}^{M-1} k \, \text{Prob}[n(x)=k] </math></center>
<center><math> n(x) = \#\{ i \mid E_{\min} < E_i < E_{\min}+x \} </math></center> that is, the number of random variables lying above the minimum <math>E_{\min}</math> but less than <math>E_{\min}+x</math>. This is itself a random variable. We are interested in its mean value: <center><math> \overline{n(x)} = \sum_{k=0}^{M-1} k \, \text{Prob}[n(x)=k] </math></center>


''' The Final goal''' is to show that for large 'M', when the extremes are described by the Gumbel distribution :
''' The Final goal''' is to show that, for large 'M' (when the extremes are described by the Gumbel distribution), you have:
<center><math> \overline{n(x)}  = e^{x/b_M}-1 </math></center>
<center><math> \overline{n(x)}  = e^{x/b_M}-1 </math></center>


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where <math>Q_{M-1}(E) = [1-P(E)]^{M-1}</math>.
where <math>Q_{M-1}(E) = [1-P(E)]^{M-1}</math>.
'''Step 2: the Gumbel limit ''' So far, no approximations have been made. To proceed, we use <math> Q_{M-1}(E)\approx Q_M(E)</math> and its  asymptotics Gumbel form:
'''Step 2: the Gumbel limit ''' So far, no approximations have been made. To proceed, we use <math> Q_{M-1}(E)\approx Q_M(E)</math> and its  asymptotics Gumbel form:

Revision as of 14:12, 31 August 2025

Nei seguente esercizio useremo le notazioni della statistica dei valori estremi usate nel corso.

exercise 1: La distribuzione di Gumbel

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: