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arxiv: 1203.5838 · v1 · pith:ZCJ4VZIGnew · submitted 2012-03-26 · 🧮 math.PR · math-ph· math.MP

The averaged characteristic polynomial for the Gaussian and chiral Gaussian ensembles with a source

classification 🧮 math.PR math-phmath.MP
keywords gaussianbetarandomaveragedcasecharacteristicchiralmatrix
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In classical random matrix theory the Gaussian and chiral Gaussian random matrix models with a source are realized as shifted mean Gaussian, and chiral Gaussian, random matrices with real $(\beta = 1)$, complex ($\beta = 2)$ and real quaternion $(\beta = 4$) elements. We use the Dyson Brownian motion model to give a meaning for general $\beta > 0$. In the Gaussian case a further construction valid for $\beta > 0$ is given, as the eigenvalue PDF of a recursively defined random matrix ensemble. In the case of real or complex elements, a combinatorial argument is used to compute the averaged characteristic polynomial. The resulting functional forms are shown to be a special cases of duality formulas due to Desrosiers. New derivations of the general case of Desrosiers' dualities are given. A soft edge scaling limit of the averaged characteristic polynomial is identified, and an explicit evaluation in terms of so-called incomplete Airy functions is obtained.

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