Wigner semicircle distribution

Template:Short description Template:Probability distribution{\pi R^2} + \frac{\arcsin\!\left(\frac{x}{R}\right)}{\pi}\!</math>
for <math>-R\leq x \leq R</math>|

  mean       =<math>0\,</math>|
  median     =<math>0\,</math>|
  mode       =<math>0\,</math>|
  variance   =<math>\frac{R^2}{4}\!</math>|
  skewness   =<math>0\,</math>|
  kurtosis   =<math>-1\,</math>|
  entropy    =<math>\ln (\pi R) - \frac12 \,</math>|
  mgf        =<math>2\,\frac{I_1(R\,t)}{R\,t}</math>|
  char       =<math>2\,\frac{J_1(R\,t)}{R\,t}</math>|

}} The Wigner semicircle distribution, named after the physicist Eugene Wigner, is the probability distribution defined on the domain [−R, R] whose probability density function f is a scaled semicircle, i.e. a semi-ellipse, centered at (0, 0):

<math>f(x)={2 \over \pi R^2}\sqrt{R^2-x^2\,}\, </math>

for −R ≤ x ≤ R, and f(x) = 0 if |x| > R. The parameter R is commonly referred to as the "radius" parameter of the distribution.

The distribution arises as the limiting distribution of the eigenvalues of many random symmetric matrices, that is, as the dimensions of the random matrix approach infinity. The distribution of the spacing or gaps between eigenvalues is addressed by the similarly named Wigner surmise.

General properties

Because of symmetry, all of the odd-order moments of the Wigner distribution are zero. For positive integers Template:Mvar, the Template:Math-th moment of this distribution is

<math>\frac{1}{n+1}\left({R \over 2}\right)^{2n} {2n\choose n}\, </math>

In the typical special case that Template:Math, this sequence coincides with the Catalan numbers 1, 2, 5, 14, etc. In particular, the second moment is Template:Math and the fourth moment is Template:Math, which shows that the excess kurtosis is Template:Math.Template:Sfnm As can be calculated using the residue theorem, the Stieltjes transform of the Wigner distribution is given by

<math>s(z)=-\frac{2}{R^2}(z-\sqrt{z^2-R^2})</math>

for complex numbers Template:Mvar with positive imaginary part, where the complex square root is taken to have positive imaginary part.Template:Sfnm

The Wigner distribution coincides with a scaled and shifted beta distribution: if Template:Mvar is a beta-distributed random variable with parameters Template:Math, then the random variable Template:Math exhibits a Wigner semicircle distribution with radius Template:Mvar. By this transformation it is straightforward to directly compute some statistical quantities for the Wigner distribution in terms of those for the beta distributions, which are better known.Template:Sfnm

The Chebyshev polynomials of the second kind are orthogonal polynomials with respect to the Wigner semicircle distribution of radius Template:Math.<ref>See Table 18.3.1 of Template:Harvtxt.</ref>

Characteristic function and Moment generating function

The characteristic function of the Wigner distribution can be determined from that of the beta-variate Template:Mvar:

<math>\varphi(t)=e^{-iRt}\varphi_Y(2Rt)=e^{-iRt}{}_1F_1\left(\frac{3}{2}; 3; 2iRt\right)=\frac{2J_1(Rt)}{Rt},</math>

where Template:Math is the confluent hypergeometric function and Template:Math is the Bessel function of the first kind.

Likewise the moment generating function can be calculated as

<math>M(t)=e^{-Rt}M_Y(2Rt)=e^{-Rt}{}_1F_1\left(\frac{3}{2}; 3; 2Rt\right)=\frac{2I_1(Rt)}{Rt}</math>

where Template:Math is the modified Bessel function of the first kind. The final equalities in both of the above lines are well-known identities relating the confluent hypergeometric function with the Bessel functions.<ref>See identities 10.16.5 and 10.39.5 of Template:Harvtxt.</ref>

Relation to free probability

In free probability theory, the role of Wigner's semicircle distribution is analogous to that of the normal distribution in classical probability theory. Namely, in free probability theory, the role of cumulants is occupied by "free cumulants", whose relation to ordinary cumulants is simply that the role of the set of all partitions of a finite set in the theory of ordinary cumulants is replaced by the set of all noncrossing partitions of a finite set. Just as the cumulants of degree more than 2 of a probability distribution are all zero if and only if the distribution is normal, so also, the free cumulants of degree more than 2 of a probability distribution are all zero if and only if the distribution is Wigner's semicircle distribution.

See also

• Wigner surmise
• The Wigner semicircle distribution is the limit of the Kesten–McKay distributions, as the parameter d tends to infinity.
• In number-theoretic literature, the Wigner distribution is sometimes called the Sato–Tate distribution. See Sato–Tate conjecture.
• Marchenko–Pastur distribution or Free Poisson distribution

Literature

• Template:Cite book
• Template:Cite book
• Template:Cite book
• Template:Cite encyclopedia
• Template:Cite journal

External links

• Eric W. Weisstein et al., Wigner's semicircle