Upper-Triangular Matrices and Orthonormal Bases
I just noticed in my drafts this post which I’d written last Friday never went up.
Let’s say we have a real or complex vector space of finite dimension
with an inner product, and let
be a linear map from
to itself. Further, let
be a basis with respect to which the matrix of
is upper-triangular. It turns out that we can also find an orthonormal basis which also gives us an upper-triangular matrix. And of course, we’ll use Gram-Schmidt to do it.
What it rests on is that an upper-triangular matrix means we have a nested sequence of invariant subspaces. If we define to be the span of
then clearly we have a chain
Further, the fact that the matrix of is upper-triangular means that
. And so the whole subspace is invariant:
.
Now let’s apply Gram-Schmidt to the basis and get an orthonormal basis
. As a bonus, the span of
is the same as the span of
, which is
. So we have exactly the same chain of invariant subspaces, and the matrix of
with respect to the new orthonormal basis is still upper-triangular.
In particular, since every complex linear transformation has an upper-triangular matrix with respect to some basis, there must exist an orthonormal basis giving an upper-triangular matrix. For real transformations, of course, it’s possible that there isn’t any upper-triangular matrix at all. It’s also worth pointing out here that there’s no guarantee that we can push forward and get an orthonormal Jordan basis.

[...] and see what happens as we try to diagonalize it. First, since we’re working over here, we can pick an orthonormal basis that gives us an upper-triangular matrix and call the basis . Now, I assert that this matrix already is diagonal when is [...]
Pingback by The Complex Spectral Theorem « The Unapologetic Mathematician | August 10, 2009 |