Rank 1 real Wishart spiked model

In this paper, we consider N‐dimensional real Wishart matrices Y in the class \input amssym $W_{\Bbb R} (\Sigma ,M)$ in which all but one eigenvalue of Σ is 1. Let the nontrivial eigenvalue of Σ be 1+τ; then as N, M → ∞, with M/N → γ2 finite and nonzero, the eigenvalue distribution of Y will converg...

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Bibliographic Details
Published in:Communications on pure and applied mathematics 2012-11, Vol.65 (11), p.1528-1638
Main Author: Mo, M. Y.
Format: Article
Language:English
Subjects:
Eigenvalues
Integrals
Mathematical analysis
Matrix
Polynomials
Probability distribution
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Summary:In this paper, we consider N‐dimensional real Wishart matrices Y in the class \input amssym $W_{\Bbb R} (\Sigma ,M)$ in which all but one eigenvalue of Σ is 1. Let the nontrivial eigenvalue of Σ be 1+τ; then as N, M → ∞, with M/N → γ2 finite and nonzero, the eigenvalue distribution of Y will converge into the Marchenko‐Pastur distribution inside a bulk region. When τ increases from 0, one starts to see a stray eigenvalue of Y outside of the support of the Marchenko‐Pastur density. As this stray eigenvalue leaves the bulk region, a phase transition will occur in the largest eigenvalue distribution of the Wishart matrix. In this paper we will compute the asymptotics of the largest eigenvalue distribution when the phase transition occurs. We will first establish the results that are valid for all N and M and will use them to carry out the asymptotic analysis. In particular, we have derived a contour integral formula for the Harish‐Chandra Itzykson‐Zuber integral $\int_{O(N)} {e^{{\rm tr}(XgYg^{\rm T} )} } g^{\rm T} dg$ when X and Y are real symmetric and Y is a rank 1 matrix. This allows us to write down a Fredholm determinant formula for the largest eigenvalue distribution and analyze it using orthogonal polynomial techniques. As a result, we obtain an integral formula for the largest eigenvalue distribution in the large‐ N limit characterized by Painlevé transcendents. The approach used in this paper is very different from a recent paper by Bloemenal and Virág, in which the largest eigenvalue distribution was obtained using a stochastic operator method. In particular, the Painlevé formula for the largest eigenvalue distribution obtained in this paper is new. © 2012 Wiley Periodicals, Inc.
ISSN:0010-3640
1097-0312
DOI:10.1002/cpa.21415