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On Mesoscopic Equilibrium for Linear Statistics in Dyson’s Brownian Motion
 
Maurice Duits Royal Institute of Technology, Stockholm, Sweden
Kurt Johansson Royal Institute of Technology, Stockholm, Sweden
On Mesoscopic Equilibrium for Linear Statistics in Dyson's Brownian Motion
eBook ISBN:  978-1-4704-4821-9
Product Code:  MEMO/255/1222.E
List Price: $78.00
MAA Member Price: $70.20
AMS Member Price: $46.80
On Mesoscopic Equilibrium for Linear Statistics in Dyson's Brownian Motion
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On Mesoscopic Equilibrium for Linear Statistics in Dyson’s Brownian Motion
Maurice Duits Royal Institute of Technology, Stockholm, Sweden
Kurt Johansson Royal Institute of Technology, Stockholm, Sweden
eBook ISBN:  978-1-4704-4821-9
Product Code:  MEMO/255/1222.E
List Price: $78.00
MAA Member Price: $70.20
AMS Member Price: $46.80
  • Book Details
     
     
    Memoirs of the American Mathematical Society
    Volume: 2552018; 118 pp

    In this paper the authors study mesoscopic fluctuations for Dyson's Brownian motion with \(\beta =2\). 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.

  • Table of Contents
     
     
    • Chapters
    • 1. Introduction
    • 2. Statement of results
    • 3. Proof of Theorem
    • 4. Proof of Theorem
    • 5. Asymptotic analysis of $K_n$ and $R_n$
    • 6. Proof of Proposition
    • 7. Proof of Lemma
    • 8. Random initial points
    • 9. Proof of Theorem : the general case
    • Appendix
  • Additional Material
     
     
  • Requests
     
     
    Review Copy – for publishers of book reviews
    Permission – for use of book, eBook, or Journal content
    Accessibility – to request an alternate format of an AMS title
Volume: 2552018; 118 pp

In this paper the authors study mesoscopic fluctuations for Dyson's Brownian motion with \(\beta =2\). 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.

  • Chapters
  • 1. Introduction
  • 2. Statement of results
  • 3. Proof of Theorem
  • 4. Proof of Theorem
  • 5. Asymptotic analysis of $K_n$ and $R_n$
  • 6. Proof of Proposition
  • 7. Proof of Lemma
  • 8. Random initial points
  • 9. Proof of Theorem : the general case
  • Appendix
Review Copy – for publishers of book reviews
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
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