On Hermitian spaces
So I want to eventually read the proof of the spectral theorem for compact self-adjoint linear operators in a Hilbert space but I keep forgetting the proof of the finite dimensional case I saw in a linear algebra course. I will thus write up this proof to hopefully remember and understand it better. First, I will lay the basic definitions and theorems for Hermitian spaces and then prove the big theorem in my next post. I will follow Artin’s Algebra.
First some definitions:
Definitions:
A Hermitian form on a complex vector space is a map
denoted by
such that it is conjugate linear in the first argument, linear in the second, and Hermitian symmetric. Conjugate linear means that
and Hermitian symmetric means that
A Hermitian form on is said to be positive definite if for all
with equality iff
A Hermitian space is a complex vector space
with a positive definite Hermitian form
We will only work with finite dimensional vector spaces in this post. The standard Hermitian form on
is
Let be a linear operator on a Hermitian space
and let
be the matrix of
with respect to an orthonormal basis
The adjoint operator of
denoted
is the operator whose matrix is the adjoint of
denoted
(with respect to the same basis
). Recall that the adjoint of the matrix
is
the transposed matrix with conjugated entries. Note that this is well defined : if we change
to a new orthonormal basis
with a change of basis matrix
the new matrix of
will be
Therefore its adjoint will be
which is just is the new basis, so the definition of the adjoint of an operator does not depend on the chosen orthonormal basis.
Finally, a normal operator is an operator that commutes with its adjoint, ie or equivalently
for
the matrix of
For example, a Hermitian operator or a self-adjoint operator is an operator such that
while a unitary operator is an operator
such that
These are examples of normal operators. Note also that a real vector space endowed with a symmetric bilinear form is a particular case of a Hermitian space. In this case, the adjoint of a matrix is the transposed matrix and symmetric matrices are Hermitian matrices while orthogonal transformations are unitary operators. As a last remark, note that if
is a unitary matrix (or equivalently a change of basis matrix between two orthonormal basis) and if
is normal, hermitian or unitary, then so is
so that these concepts don’t depend on the choice of basis.
From the projection formula, it is easy to see that for a space there exists an orthogonal basis
such that for each
is equal to
or
By Sylvester’s law (which says that the number of such 1’s, -1’s or 0’s is invariant under a change of basis), it follows that there exists an orthonormal basis for
iff the form is positive definite. In this case, let
be the matrix for
ie
let
be an orthonormal basis for this form and also let
be the change of basis matrix from the canonical basis
to the basis
Then we have
Since if
and
otherwise (because
is orthonormal), we see that
the matrix for the form in the orthonormal basis, must be the identity matrix. We have proven the following proposition:
Proposition: Every positive definite Hermitian form on
is conjugate to the standard Hermitian form. More precisely, if
is the matrix of the form and
is any orthonormal basis for
then
where
is the change of basis matrix from the canonical basis to
Here is a characterisation that motivates the definition of normal, Hermitian and unitary operators:
Proposition: Let
be a linear operator on a (positive definite) Hermitian space
- For all
we have
and
is normal iff for all
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is Hermitian iff for all
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is unitary iff for all
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Proof:
1. Pick an orthonormal basis for
and let
be the matrix of
with respect to
If
and
are the respective representations of
and
in the basis
we have, by the last proposition,
and
hence The other formula can be proven similarly.
2. Substituting for
in the first equation of 1., we get
Substituting for
in the second equation, we get
Therefore, if is normal, ie if
we have
Conversely, if
then
It follows that
Since was arbitrary and because the form is positive definite, we must have
hence
is normal. The proofs of 3. and 4. follow the same lines.
QED
Proposition: Let
be a linear operator on a Hermitian space
and let
be a subspace of
If
is
-invariant, then the orthogonal space
is
-invariant. Since
if
is
-invariant, then
is
-invariant.
Proof: Let and
By the first point of last proposition, we have
So if
is
-invariant, we have
and thus
This gives
which in other words means that
for arbitrary
ie
is
-invariant.
QED
Recall that is an eigenvector for the matrix
iff
for some
iff
is not invertible. Since
is not invertible iff
the fundamental theorem of algebra assures us that every linear operator on a complex vector space has at least one eigenvector.
Theorem: Let
be a normal operator on a Hermitian space
and let
be an eigenvector of
with eigenvalue
Then
is also an eigenvector of
with eigenvalue
Proof:
Case 1: In this case,
Since
is a normal operator, we have
Since the form is positive definite, we must have
as was to be shown.
Case 2: Then, if
is an eigenvector for
with eigenvalue
Moreover, we have
so
In other words, is a normal operator so by case 1,
is an eigenvector for
with eigenvalue
ie
as wanted.
QED
In my next post, I will finish the job and prove the Spectral Theorem for Normal Operators.
Reference: M. Artin, Algebra, 2nd edition.
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