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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), you have:
''' 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>



Revision as of 12:26, 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 n(x):Given a realization of the random energies E1,E2,…,EM, define

n(x)=#{i∣Emin<Ei<Emin+x}

that is, the number of random variables lying above the minimum

Emin

but less than

Emin+x

. This is itself a random variable. We are interested in its mean value:

n(x)‾=∑k=0M−1kProb[n(x)=k]

The Final goal is to show that, for large M (when the extremes are described by the Gumbel distribution), you have:

n(x)‾=ex/bM−1

Step 1: Exact manipulations: You start from the exact expression for the probability of k states in the interval:

Prob[n(x)=k]=M(M−1k)∫−∞∞dEp(E)[P(E+x)−P(E)]k[1−P(E+x)]M−k−1

To compute n(x)‾, you must sum over k. Use the identity

∑k=0M−1k(M−1k)(A−B)kBM−1−k=(A−B)ddA∑k=0M−1(M−1k)(A−B)kBM−1−k=(M−1)(A−B)AM−2

to arrive at the form:

n(x)‾=M(M−1)∫−∞∞dEp(E)[P(E+x)−P(E)](1−P(E))M−2=M∫−∞∞dE[P(E+x)−P(E)]dQM−1(E)dE

where QM−1(E)=[1−P(E)]M−1.

Step 2: the Gumbel limit So far, no approximations have been made. To proceed, we use QM−1(E)≈QM(E) and its asymptotics Gumbel form:

dQM−1(E)dEdE∼exp⁡(E−aMbM)exp⁡[−exp⁡(E−aMbM)]dEbM=eze−ezdz

where z=(E−aM)/bM.

Compute the integral and verify that you obtain:

n(x)‾=(ex/bM−1)∫−∞∞dze2z−ez=ex/bM−1