TBan-I: Difference between revisions
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To compute <math>\overline{n(x)}</math>, you must sum over <math>k</math>. | To compute <math>\overline{n(x)}</math>, you must sum over <math>k</math>. | ||
Use the identity | Use the identity | ||
<center><math> \sum_{k=0}^{M-1} k \binom{M-1}{k} (A-B)^k B^{M-1-k} = (A-B)\frac{d}{dA} \sum_{k=0}^{M-1} \binom{M-1}{k} (A-B)^k B^{M-1-k} = (M-1)(A-B)A^{M-2} </math></center> | <center><math> \sum_{k=0}^{M-1} k \binom{M-1}{k} (A-B)^k B^{M-1-k} = (A-B)\frac{d}{dA} \sum_{k=0}^{M-1} \binom{M-1}{k} (A-B)^k B^{M-1-k} = (M-1)(A-B)A^{M-2} </math></center> | ||
to arrive at the form: | to arrive at the form: |
Revision as of 13:58, 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 :
Step 1: Exact manipulations
To compute , you must sum over . Use the identity
to arrive at the form:
Step 2: the Gumbel limit So far, no approximations have been made. To proceed, we use and its asymptotics Gumbel form: