LMS Research School: Methods for Random Matrix Theory and Applications28 Feb 2020, by Sponsored events in
11 May 2020 – 15 May 2020
University of Reading
Though the random matrices have been long studied for their applications to multivariable statistics since the work of Wishart and in physics for its application to the level-spacing of highly excited energy levels of nuclei since the work of Wigner, Dyson and others, there has in recent years been a renewed significant interest in this subject. Some of the main reasons for this are: (a) The discovery that a large class of random matrix models are related to completely integrable systems of differential equations of both the Painlevé type and those of the Kadomtsev-Petviashvili (KP); (b) The relation of the theory of random matrices to the theory of Hankel and Toeplitz determinants; (c) The development of the novel technique – the Riemann-Hilbert method, which yields the solution of a number of the long-standing problems in the field; (d) The discovery of the remarkable fact that the random matrices and the nonlinear Hamiltonian PDEs demonstrate the same universal features at the relevant critical and transition regimes. These topics as well as some other important aspects of random matrix theory will be covered in the three lecture courses (five hours each) and in the invited lectures (one hour each).
Igor Krasovsky, University of Reading
Jani A. Virtanen, University of Reading
For more information, please visit the website here.