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From Random Matrices to Stochastic Operators
Authors:Alan Edelman  Brian D Sutton
Institution:(1) Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA;(2) Department of Mathematics, Randolph-Macon College, Ashland, VA 23005, USA
Abstract:We propose that classical random matrix models are properly viewed as finite difference schemes for stochastic differential operators. Three particular stochastic operators commonly arise, each associated with a familiar class of local eigenvalue behavior. The stochastic Airy operator displays soft edge behavior, associated with the Airy kernel. The stochastic Bessel operator displays hard edge behavior, associated with the Bessel kernel. The article concludes with suggestions for a stochastic sine operator, which would display bulk behavior, associated with the sine kernel.
Keywords:random matrices  random eigenvalues  stochastic differential operators
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