Eigenvalues of block matrix/Related non-linear eigenvalue problem

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TL;DR
I need to determine whether the eigenvalues of a large [itex]2n[/itex] by [itex]2n[/itex] block matrix are inside the unit circle, and have reduced the problem to an [itex]n[/itex]-dimensional non-linear eigenvalue problem.
I have a matrix [itex]M[/itex] which in block form is defined as follows: [tex] \begin{pmatrix} A (\equiv I + 3\alpha J) & B (\equiv -\alpha J) \\ I & 0 \end{pmatrix}[/tex] where [itex]J[/itex] is an [itex]n[/itex]-by-[itex]n[/itex] complex matrix, [itex]I[/itex] is the identity and [itex]\alpha \in (0,1][/itex] is a parameter. The problem is to determine whether the eigenvalues of [itex]M[/itex] lie in the unit circle.

This comes from the discretization of a PDE, so [itex]n[/itex] is potentially on the order of 5000 and I'm looking for a numerical method. I would prefer not to have to find the eigenvalues of a [itex]2n[/itex] by [itex]2n[/itex] matrix if there's a more efficient way to solve an equivalent [itex]n[/itex]-dimensional problem.

By definition [itex]\lambda[/itex] is an eigenvalue of [itex]M[/itex] if and only if there exist [itex](p_1, p_2) \in (\mathbb{C}^{n})^2 \setminus \{(0,0)\}[/itex] such that [tex] \begin{pmatrix}A & B \\ I & 0 \end{pmatrix} <br /> \begin{pmatrix} p_1 \\ p_2 \end{pmatrix} = \lambda \begin{pmatrix} p_1 \\ p_2 \end{pmatrix}.[/tex] This leads me to the non-linear eigenvalue problem [tex] \lambda(A - \lambda I)p_2 = -B p_2[/tex] with [itex]p_1 = \lambda p_2[/itex], which in terms of [itex]J[/itex] is
[tex] \lambda(3 \alpha J - (\lambda - 1)I)p_2 = \alpha J p_2.[/tex] Is there an efficient algorithm to solve this?

Alternatively, if the eigenvalues of [itex]M[/itex] can be determined directly from those of [itex]J[/itex] then so much the better.
 
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On further reflection, given the relationship between [itex]A[/itex] and [itex]B[/itex], we can obtain eigenvalues of [itex]M[/itex] in terms of those of [itex]B[/itex] as follows:

Since [itex]A = I - 3B[/itex], if [itex]p_2[/itex] is an eigenvector of [itex]B[/itex] with eigenvalue [itex]\mu[/itex] then [itex]p_2[/itex] is also an eigenvector of [itex]A[/itex] with eigenvalue [itex]1 - 3\mu[/itex], since
[tex]Ap_2 = (I - 3B)p_2 = (1 - 3\mu)p_2.[/tex] Thus [tex] (\lambda(1 - 3\mu) + \mu)p_2 = \lambda^2 p_2[/tex] and as [itex]p_2 \neq 0[/itex] we must have [tex] \lambda^2 - (1 - 3\mu)\lambda - \mu = 0.[/tex]

Conversely, if [itex]p_2 \neq 0[/itex] is a solution of the non-linear eigenproblem with eigenvalue [itex]\lambda[/itex] then [tex] \begin{align*}<br /> &\lambda(I - 3B)p_2 + Bp_2 = \lambda^2 p_2 \\<br /> \Leftrightarrow \qquad& B(1 - 3 \lambda)p_2 = (\lambda^2 - \lambda) p_2<br /> \end{align*}[/tex] Now if [itex]\lambda = \frac13[/itex] then the left hand side is zero and the right hand side is [itex]-\frac29 p_2[/itex], which by assumption is not zero. Thus [itex]\lambda \neq \frac13[/itex] and so [tex] Bp_2 = \frac{\lambda^2 - \lambda}{1 - 3\lambda}p_2[/tex] as required.

Problem solved.
 
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