A Gaussian fluctuation formula is proved for linear statistics of complex random matrices in the case where the statistic is rotationally invariant. For a general linear statistic without this symmetry, Coulomb gas theory is used to predict that the distribution will again be a Gaussian, with a specific mean and variance. The variance splits naturally into a bulk and surface contibution, the latter resulting from the long-range correlations at the boundary of the support of the eigenvalue density.
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Peter J. Forrester (1999) studied this question.
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