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Characteristic polynomials of sample covariance matrices: The non-square case

Holger Kösters — 2010

Open Mathematics

We consider the sample covariance matrices of large data matrices which have i.i.d. complex matrix entries and which are non-square in the sense that the difference between the number of rows and the number of columns tends to infinity. We show that the second-order correlation function of the characteristic polynomial of the sample covariance matrix is asymptotically given by the sine kernel in the bulk of the spectrum and by the Airy kernel at the edge of the spectrum. Similar results are given...

The quenched invariance principle for random walks in random environments admitting a bounded cycle representation

Jean-Dominique Deuschel;  Holger Kösters — 2008

Annales de l'I.H.P. Probabilités et statistiques

We derive a quenched invariance principle for random walks in random environments whose transition probabilities are defined in terms of weighted cycles of bounded length. To this end, we adapt the proof for random walks among random conductances by Sidoravicius and Sznitman ( (2004) 219–244) to the non-reversible setting.

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