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This article deals with the universality of eigenvalue spacings, one of the basic characteristics of random matrices. It first discusses the heuristic meaning of universality before describing the standard universality classes (sine, Airy, Bessel) and their appearance in unitary, orthogonal, and symplectic ensembles. It then examines unitary matrix ensembles in more detail and shows that universality in these ensembles comes down to the convergence of the properly scaled eigenvalue correlation kernels. It also analyses the Riemann–Hilbert method, along with certain non-standard universality classes that arise at singular points in the limiting spectrum. Finally, it considers the limiting kernels for each of the three types of singular points, namely interior singular points, singular edge points, and exterior singular points.
Mathematics - Complex Variables, Probability (math.PR), FOS: Mathematics, FOS: Physical sciences, Mathematical Physics (math-ph), Complex Variables (math.CV), Mathematical Physics, Mathematics - Probability
Mathematics - Complex Variables, Probability (math.PR), FOS: Mathematics, FOS: Physical sciences, Mathematical Physics (math-ph), Complex Variables (math.CV), Mathematical Physics, Mathematics - Probability
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