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The distribution of overlaps between eigenvectors of Ginibre matrices

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arxiv 1801.01219 v2 pith:3NVTQVHG submitted 2018-01-04 math.PR math-phmath.MP

classification math.PRmath-phmath.MP
keywords eigenvaluesoverlapsconditionnumbersdistributionmatricesmesoscopicoff-diagonal
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We study the overlaps between eigenvectors of nonnormal matrices. They quantify the stability of the spectrum, and characterize the joint eigenvalues increments under Dyson-type dynamics. Well known work by Chalker and Mehlig calculated the expectation of these overlaps for complex Ginibre matrices. For the same model, we extend their results by deriving the distribution of diagonal overlaps (the condition numbers), and their correlations. We prove: (i) convergence of condition numbers for bulk eigenvalues to an inverse Gamma distribution; more generally, we decompose the quenched overlap (i.e. conditioned on eigenvalues) as a product of independent random variables; (ii) asymptotic expectation of off-diagonal overlaps, both for microscopic or mesoscopic separation of the corresponding eigenvalues; (iii) decorrelation of condition numbers associated to eigenvalues at mesoscopic distance, at polynomial speed in the dimension; (iv) second moment asymptotics to identify the fluctuations order for off-diagonal overlaps, when the related eigenvalues are separated by any mesoscopic scale; (v) a new formula for the correlation between overlaps for eigenvalues at microscopic distance, both diagonal and off-diagonal. These results imply estimates on the extreme condition numbers, the volume of the pseudospectrum and the diffusive evolution of eigenvalues under Dyson-type dynamics, at equilibrium.

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  1. On eigenvector statistics in the spherical and truncated unitary ensembles

    math.PR 2019-08 accept novelty 6.0 of 10

    For the spherical and truncated unitary ensembles, diagonal eigenvector overlaps decompose into products of independent variables and converge, conditional on one eigenvalue, to the inverse of a gamma-2 distribution.

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