Abstract
The singular values squared of the random matrix product , where each is a rectangular standard complex Gaussian matrix while is non-random, are shown to be a determinantal point process with correlation kernel given by a double contour integral. When all but finitely many eigenvalues of are equal to , the kernel is shown to admit a well-defined hard edge scaling, in which case a critical value is established and a phase transition phenomenon is observed. More specifically, the limiting kernel in the subcritical regime of is independent of , and is in fact the same as that known for the case due to Kuijlaars and Zhang. The critical regime of allows for a double scaling limit by choosing , and for this the critical kernel and outlier phenomenon are established. In the simplest case , which is closely related to non-intersecting squared Bessel paths, a distribution corresponding to the finite shifted mean LUE is proven to be the scaling limit in the supercritical regime of with two distinct scaling rates. Similar results also hold true for the random matrix product , with each being a truncated unitary matrix.
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