Weinstein–Aronszajn identity
In mathematics, the Weinstein–Aronszajn identity states that if [math]\displaystyle{ A }[/math] and [math]\displaystyle{ B }[/math] are matrices of size m × n and n × m respectively (either or both of which may be infinite) then, provided [math]\displaystyle{ AB }[/math] (and hence, also [math]\displaystyle{ BA }[/math]) is of trace class,
- [math]\displaystyle{ \det(I_m + AB) = \det(I_n + BA), }[/math]
where [math]\displaystyle{ I_k }[/math] is the k × k identity matrix.
It is closely related to the matrix determinant lemma and its generalization. It is the determinant analogue of the Woodbury matrix identity for matrix inverses.
Proof
The identity may be proved as follows.[1] Let [math]\displaystyle{ M }[/math] be a matrix consisting of the four blocks [math]\displaystyle{ I_m }[/math], [math]\displaystyle{ A }[/math], [math]\displaystyle{ B }[/math] and [math]\displaystyle{ I_n }[/math]:
- [math]\displaystyle{ M = \begin{pmatrix} I_m & A \\ B & I_n \end{pmatrix}. }[/math]
Because Im is invertible, the formula for the determinant of a block matrix gives
- [math]\displaystyle{ \det\begin{pmatrix} I_m & A \\ B & I_n \end{pmatrix} = \det(I_m) \det\left(I_n - B I_m^{-1} A\right) = \det(I_n - BA). }[/math]
Because In is invertible, the formula for the determinant of a block matrix gives
- [math]\displaystyle{ \det\begin{pmatrix} I_m & A\\ B & I_n \end{pmatrix} = \det(I_n) \det\left(I_m - A I_n^{-1} B\right) = \det(I_m - AB). }[/math]
Thus
- [math]\displaystyle{ \det(I_n - B A) = \det(I_m - A B). }[/math]
Substituting [math]\displaystyle{ -A }[/math] for [math]\displaystyle{ A }[/math] then gives the Weinstein–Aronszajn identity.
Applications
Let [math]\displaystyle{ \lambda \in \mathbb{R} \setminus \{0\} }[/math]. The identity can be used to show the somewhat more general statement that
- [math]\displaystyle{ \det(AB - \lambda I_m) = (-\lambda)^{m - n} \det(BA - \lambda I_n). }[/math]
It follows that the non-zero eigenvalues of [math]\displaystyle{ AB }[/math] and [math]\displaystyle{ BA }[/math] are the same.
This identity is useful in developing a Bayes estimator for multivariate Gaussian distributions.
The identity also finds applications in random matrix theory by relating determinants of large matrices to determinants of smaller ones.[2]
References
- ↑ Pozrikidis, C. (2014), An Introduction to Grids, Graphs, and Networks, Oxford University Press, p. 271, ISBN 9780199996735, https://books.google.com/books?id=Ws_RAgAAQBAJ&pg=PA271
- ↑ "The mesoscopic structure of GUE eigenvalues | What's new". http://terrytao.wordpress.com/2010/12/17/the-mesoscopic-structure-of-gue-eigenvalues/. Retrieved 2016-01-16.
Original source: https://en.wikipedia.org/wiki/Weinstein–Aronszajn identity.
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