Spacings in Orthogonal and Symplectic Random Matrix Ensembles
classification
🧮 math.PR
math-phmath.MP
keywords
distributionensemblesmatrixspacingconvergesempiricalinvariantorthogonal
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We consider the universality of the nearest neighbour eigenvalue spacing distribution in invariant random matrix ensembles. Focussing on orthogonal and symplectic invariant ensembles, we show that the empirical spacing distribution converges in a uniform way. More precisely, the main result states that the expected Kolmogorov distance of the empirical spacing distribution from its universal limit converges to zero as the matrix size tends to infinity.
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