scholarly journals Spectral distributions of periodic random matrix ensembles

2019 ◽  
Vol 10 (01) ◽  
pp. 2150011
Author(s):  
Roger Van Peski

Koloğlu, Kopp and Miller compute the limiting spectral distribution of a certain class of real random matrix ensembles, known as [Formula: see text]-block circulant ensembles, and discover that it is exactly equal to the eigenvalue distribution of an [Formula: see text] Gaussian unitary ensemble. We give a simpler proof that under very general conditions which subsume the cases studied by Koloğlu–Kopp–Miller, real-symmetric ensembles with periodic diagonals always have limiting spectral distribution equal to the eigenvalue distribution of a finite Hermitian ensemble with Gaussian entries which is a ‘complex version’ of a [Formula: see text] submatrix of the ensemble. We also prove an essentially algebraic relation between certain periodic finite Hermitian ensembles with Gaussian entries, and the previous result may be seen as an asymptotic version of this for real-symmetric ensembles. The proofs show that this general correspondence between periodic random matrix ensembles and finite complex Hermitian ensembles is elementary and combinatorial in nature.

2015 ◽  
Vol 04 (01) ◽  
pp. 1550002 ◽  
Author(s):  
Sheehan Olver ◽  
Raj Rao Nadakuditi ◽  
Thomas Trogdon

We develop a computationally efficient algorithm for sampling from a broad class of unitary random matrix ensembles that includes but goes well beyond the straightforward to sample Gaussian unitary ensemble (GUE). The algorithm exploits the fact that the eigenvalues of unitary ensembles (UEs) can be represented as a determinantal point process whose kernel is given in terms of orthogonal polynomials. Consequently, our algorithm can be used to sample from UEs for which the associated orthogonal polynomials can be numerically computed efficiently. By facilitating high accuracy sampling of non-classical UEs, the algorithm can aid in the experimentation-based formulation or refutation of universality conjectures involving eigenvalue statistics that might presently be unamenable to theoretical analysis. Examples of such experiments are included.


1993 ◽  
Vol 62 (7) ◽  
pp. 2248-2259 ◽  
Author(s):  
Masahiro Shiroishi ◽  
Taro Nagao ◽  
Miki Wadati

Nonlinearity ◽  
2016 ◽  
Vol 29 (11) ◽  
pp. 3385-3416 ◽  
Author(s):  
Tom Claeys ◽  
Antoine Doeraene

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