In this section, we will look at some special classes of square
matrices which are diagonalisable. We will also be dealing with
matrices having complex entries and hence for a matrix
recall the following definitions.
Note that a symmetric matrix is always Hermitian, a skew-symmetric matrix
is always skew-Hermitian and an orthogonal matrix is always
unitary. Each of these matrices are normal. If
is a unitary
matrix then
EXAMPLE 6.3.2
- Let
Then
is skew-Hermitian.
- Let
and
Then
is a unitary matrix and
is a normal
matrix. Note that
is also a normal matrix.
EXERCISE 6.3.4
- Let
be a square matrix such that
is a diagonal matrix for some unitary matrix
.
Prove that
is a normal matrix.
- Let
be any matrix. Then
where
is the Hermitian part of
and
is the skew-Hermitian part of
- Every matrix can be uniquely expressed as
where both
and
are Hermitian matrices.
- Show that
is always skew-Hermitian.
- Does there exist a unitary matrix
such that
where
and
Proof.
Let
be an eigenpair. Then
and
implies
Hence
But
is an eigenvector and hence
and so the real number
is non-zero as well. Thus
That is,
is a real number.
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Proof.
We will prove the result by induction on the size of
the matrix. The result is clearly true if
Let the result
be true for
we will prove the result in case
So, let
be a
matrix and let
be
an eigenpair of
with
We now extend the linearly
independent set
to form an orthonormal basis
(using
Gram-Schmidt
Orthogonalisation) of
.
As
is an orthonormal set,
Therefore, observe that for all
Hence, we also have
for
Now, define
(with
as columns of
). Then the matrix
is a unitary matrix
and
where
is a
matrix. As
,we get
. This condition,
together with the fact that
is a real number (use Proposition
6.3.5), implies that
. That is,
is also
a Hermitian matrix. Therefore, by induction hypothesis there
exists a
unitary matrix
such that
Recall that , the entries
for
are the eigenvalues of the matrix
We also know that
two similar matrices have the same set of eigenvalues. Hence, the
eigenvalues of
are
Define
Then
is a unitary matrix
and
Thus,
is a diagonal matrix with diagonal entries
the eigenvalues of
Hence, the result follows.
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COROLLARY 6.3.7
Let
be an
real symmetric matrix. Then
- the eigenvalues of
are all real,
- the corresponding eigenvectors can be chosen to have real entries, and
- the eigenvectors also form an orthonormal basis of
Proof.
As
is symmetric,
is also an Hermitian matrix. Hence, by Proposition
6.3.5, the eigenvalues of
are all real.
Let
be an eigenpair of
Suppose
Then there exist
such that
So,
Comparing the real and imaginary parts, we get
and
Thus, we can choose the eigenvectors to have real entries.
To prove the orthonormality of the eigenvectors, we proceed on the lines
of the proof of Theorem 6.3.6, Hence, the readers are advised
to complete the proof.
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Remark 6.3.9
In the previous exercise, we saw that the matrices
and
are similar but not unitarily equivalent, whereas
unitary equivalence implies similarity equivalence as
But in numerical calculations, unitary transformations are preferred
as compared to similarity transformations. The main reasons being:
- Exercise 6.3.8.2 implies
that an orthonormal
change of basis leaves unchanged the sum of squares of the
absolute values of the entries which need not be true under a
non-orthonormal change of basis.
- As
for a unitary matrix
unitary equivalence is
computationally simpler.
- Also in doing ``conjugate transpose", the loss of accuracy due to round-off
errors doesn't occur.
We next prove the Schur's Lemma and use it to show that normal matrices
are unitarily diagonalisable.
LEMMA 6.3.10 (Schur's Lemma)
Every
complex matrix is unitarily similar to an upper
triangular matrix.
Proof.
We will prove the result by induction on the size of
the matrix. The result is clearly true if
Let the result
be true for
we will prove the result in case
So, let
be a
matrix and let
be
an eigenpair for
with
Then the linearly
independent set
can be extended, using the
Gram-Schmidt
Orthogonalisation process, to get an orthonormal basis
of
. Then
(with
as the columns of the matrix
)
is a unitary matrix and
where
is a
matrix. By induction
hypothesis there exists a
unitary matrix
such that
is an upper triangular matrix
with diagonal entries
the eigen
values of the matrix
Observe that since the eigenvalues of
are
the
eigenvalues of
are
Define
Then check that
is a unitary matrix and
is an upper triangular matrix with diagonal entries
the eigenvalues of the
matrix
Hence, the result follows.
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We end this chapter with an application of the theory of diagonalisation
to the study of conic sections in analytic geometry and the study of
maxima and minima in analysis.
A K Lal
2007-09-12