The Cayley-Hamilton theorem shows that the characteristic polynomial of a square matrix is identically equal to zero when it is transformed into a polynomial in the matrix itself. In other words, a square matrix satisfies its own characteristic equation.
In the lecture on matrix
polynomials we have explained that, if
is a field, such as the set of real numbers
or the set of complex numbers
,
and
is an ordinary
polynomial
then
we can use
to define, by extension, an analogous matrix
polynomial
provided
that the entries of the square matrix
belong to the field
.
Remember that the characteristic polynomial of a square matrix
is
where
are the
eigenvalues of
.
As explained above, an ordinary polynomial
can be used to define a matrix polynomial
.
The proposition in the next section, known as Cayley-Hamilton theorem, shows
that the characteristic polynomial of
is identically equal to zero when it is transformed into a polynomial in
.
Here is the Cayley-Hamilton theorem.
Proposition
Let
be a
matrix. Let
be the eigenvalues of
.
Then,
DefineThe
matrix
has a Schur
decomposition
where
is an upper triangular
matrix,
is a unitary matrix and
denotes the conjugate
transpose of
.
Moreover, the diagonal entries of
are the eigenvalues of
.
Since
is unitary,
.
Therefore,
We
are going to show that
and,
as a consequence,
.
Define
We
are going to prove by induction that the first
columns of
are zero (hence all the columns of
are zero and the proposition is true). Let us start from
.
Since
is upper triangular,
is the only non-zero entry of the first column of
.
Therefore, the first column of the matrix
is
zero. Now suppose that the first
columns of
are zero, that
is,
The
columns of
can
be seen as
linear
combinations of the columns of
with coefficients taken from the corresponding columns of
.
In particular, the
-th
column of
is
where:
in step
we have used the fact that
is upper triangular and, as a consequence,
when
;
in step
we have used the fact that the first
columns of
are zero. When
is one of the first
columns of
,
then
.
If
,
then the summation is over an empty set of indices
and
If
,
then the summation is over a single index
and
because
Thus,
we have reached the desired conclusion: the first
columns of
are zero. It follows that all the columns of
are zero and
.
Thus, if
is the characteristic polynomial of
,
then
Let us make an example.
Example
DefineThe
characteristic polynomial of
is
We
can transform it into a polynomial in
as
follows:
Let
us carry out the multiplications so as to check that indeed the
Cayley-Hamilton theorem
holds:
An important consequence of the Cayley-Hamilton theorem is that any polynomial
in a
matrix
can be rewritten as a polynomial whose degree is at most
.
Proposition
Let
be a
matrix. Let
be a matrix polynomial in
.
Then, there exists a polynomial
such
that
and
the degree of
is at most
.
If the degree of
is less than
,
then there is nothing to prove. If the degree of
is greater than or equal to
,
we proceed as follows. By the Cayley-Hamilton theorem, we
have
where
the scalars
are obtained by expanding the product
.
Thus,
can be expressed as a linear combination of powers of
up to the
-th:
If
we pre-multiply both sides of the previous equation by
,
we
obtain
By
substituting (1) into (2), we obtain that also
can be expressed as a linear combination of powers of
up to the
-th.
With this technique (pre-multiply and substitute), we obtain the same
result for any power
,
where
is any positive integer. Thus, given a polynomial
of degree greater than or equal to
,
we can substitute all the powers of
that appear in the polynomials and are greater than or equal to
with lower powers. Hence, we have the stated result.
Below you can find some exercises with explained solutions.
DefineRe-write
the
polynomial
as
a polynomial of degree
in
.
The characteristic polynomial of
is
Therefore,
by the Cayley-Hamilton theorem, we
have
We
pre-multiply both sides of the previous equation so as to
obtain
Then,
we substitute (3) into (4) and
get
Finally,
we can re-write the given
polynomial
Please cite as:
Taboga, Marco (2021). "Cayley-Hamilton theorem", Lectures on matrix algebra. https://www.statlect.com/matrix-algebra/Cayley-Hamilton-theorem.
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