
arXiv: 1402.3660
AbstractAn exchangeable random matrix is a random matrix with distribution invariant under any permutation of the entries. For such random matrices, we show, as the dimension tends to infinity, that the empirical spectral distribution tends to the uniform law on the unit disc. This is an instance of the universality phenomenon known as the circular law, for a model of random matrices with dependent entries, rows, and columns. It is also a non‐Hermitian counterpart of a result of Chatterjee on the semi‐circular law for random Hermitian matrices with exchangeable entries. The proof relies in particular on a reduction to a simpler model given by a random shuffle of a rigid deterministic matrix, on hermitization, and also on combinatorial concentration of measure and combinatorial Central Limit Theorem. A crucial step is a polynomial bound on the smallest singular value of exchangeable random matrices, which may be of independent interest. © 2015 Wiley Periodicals, Inc. Random Struct. Alg., 48, 454–479, 2016
Random matrices (algebraic aspects), Random permutations, smallest singular value, Probability (math.PR), random matrices, concentration of measure, spectral analysis, Probabilités et mathématiques appliquées, 510, 519, random permutations, Random matrices (probabilistic aspects), exchangeable distributions, FOS: Mathematics, Combinatorial Central Limit Theorem, combinatorial central limit theorem, Random matrices, Mathematics - Probability
Random matrices (algebraic aspects), Random permutations, smallest singular value, Probability (math.PR), random matrices, concentration of measure, spectral analysis, Probabilités et mathématiques appliquées, 510, 519, random permutations, Random matrices (probabilistic aspects), exchangeable distributions, FOS: Mathematics, Combinatorial Central Limit Theorem, combinatorial central limit theorem, Random matrices, Mathematics - Probability
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