On Mesoscopic Equilibrium for Linear Statistics in Dyson's Brownian Motion

On Mesoscopic Equilibrium for Linear Statistics in Dyson's Brownian Motion

  • Maurice Duits
  • Kurt Johansson
Publisher:American Mathematical Soc.ISBN 13: 9781470429645ISBN 10: 1470429640

Paperback & Hardcover deals ―

Amazon IndiaGOFlipkart GOSnapdealGOSapnaOnlineGOJain Book AgencyGOBooks Wagon₹5,148Book ChorGOCrosswordGODC BooksGO

e-book & Audiobook deals ―

Amazon India GOGoogle Play Books ₹78Audible GO

* Price may vary from time to time.

* GO = We're not able to fetch the price (please check manually visiting the website).

Know about the book -

On Mesoscopic Equilibrium for Linear Statistics in Dyson's Brownian Motion is written by Maurice Duits and published by American Mathematical Soc.. It's available with International Standard Book Number or ISBN identification 1470429640 (ISBN 10) and 9781470429645 (ISBN 13).

In this paper the authors study mesoscopic fluctuations for Dyson's Brownian motion with β=2 . Dyson showed that the Gaussian Unitary Ensemble (GUE) is the invariant measure for this stochastic evolution and conjectured that, when starting from a generic configuration of initial points, the time that is needed for the GUE statistics to become dominant depends on the scale we look at: The microscopic correlations arrive at the equilibrium regime sooner than the macrosopic correlations. The authors investigate the transition on the intermediate, i.e. mesoscopic, scales. The time scales that they consider are such that the system is already in microscopic equilibrium (sine-universality for the local correlations), but have not yet reached equilibrium at the macrosopic scale. The authors describe the transition to equilibrium on all mesoscopic scales by means of Central Limit Theorems for linear statistics with sufficiently smooth test functions. They consider two situations: deterministic initial points and randomly chosen initial points. In the random situation, they obtain a transition from the classical Central Limit Theorem for independent random variables to the one for the GUE.