On random symmetric matrices with a constraint: the spectral density of random impedance networks
classification
❄️ cond-mat.dis-nn
keywords
randomdensityimpedancematricesnetworksconstraintresultsymmetric
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We derive the mean eigenvalue density for symmetric Gaussian random N x N matrices in the limit of large N, with a constraint implying that the row sum of matrix elements should vanish. The result is shown to be equivalent to a result found recently for the average density of resonances in random impedance networks [Y.V. Fyodorov, J. Phys. A: Math. Gen. 32, 7429 (1999)]. In the case of banded matrices, the analytical results are compared with those extracted from the numerical solution of Kirchhoff equations for quasi one-dimensional random impedance networks.
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