Mock-Gaussian behaviour is when a smooth counting function (or linear statistic) has its first few moments equal to the moments of a Gaussian distribution, even though it is not a normal distribution. In this lecture we will see that this behaviour holds eigenvalues of random matrices, and analogously for the zeros of the Riemann zeta function and other L-functions. The research presented in this lecture is joint with Zeev Rudnick.
- http://uk.arxiv.org/abs/math.PR/0206289 - Mock-Gaussian Behaviour for Linear Statistics of Classical Compact Groups
- http://uk.arxiv.org/abs/math.NT/0208220 - Linear statistics for zeros of Riemann's zeta function
- http://uk.arxiv.org/abs/math.NT/0208230 - Linear statistics of low-lying zeros of L--functions