In my current position as Director of Undergraduate Studies for the Georgia Tech School of Mathematics, I’ve been heavily involved with revamping our linear algebra curriculum. So I’ve spent a lot of time lately reading through various linear algebra books. The goal of this post is to give a self-contained proof of the existence and uniqueness of the Jordan Canonical Form which is somewhat different from the ‘usual’ proofs one finds in textbooks. I’m not claiming any novelty — I’m sure this approach has been discovered before — but I don’t know a good reference so I thought I’d record the details here.
The proof I give here does not use properties of polynomials (e.g. the Chinese Remainder Theorem), nor does it rely on the classification of finitely generated modules over a PID, so it might be of some pedagogical interest. The proof I give for the Generalized Eigenvector Decomposition is based on an auxiliary result — the Fitting Decomposition — which in my opinion ought to be better known. The proof I give of the structure theorem for nilpotent operators comes from these lecture notes of Curt McMullen (Theorem 5.19). It is particularly concise compared to some other arguments I’ve seen.
Jordan Canonical Form
Recall that an elementary Jordan block is an
matrix of the following form (illustrated with
):
A matrix is in Jordan Canonical Form if it is a block sum of elementary Jordan blocks, for example:
The theorem we wish to prove is that, over an algebraically closed field , every
matrix is similar to a matrix in Jordan Canonical Form, and the latter is unique up to rearranging the elementary Jordan blocks. Thus two
matrices are similar over
if and only if they have the same Jordan Canonical Forms (up to rearranging the blocks). More canonically, we want to show that if
is a finite-dimensional vector space over
and
is a linear operator, then
is direct sum of
-invariant subspaces
such that the matrix of
restricted to
(with respect to some ordered basis
) is an elementary Jordan block. The latter condition means that there is
and a vector
with
such that
is a basis for
.
Fitting Decomposition
Let be a finite dimensional vector space over a field
, and let
be a linear endomorphism.
Theorem 1 (Fitting Decomposition): There is a unique direct sum decomposition
with the following properties:
1. (1) Bothand
are
-invariant.
2. (2)is nilpotent on
.
3. (3)is invertible on
.
Proof: The chain must stabilize to a
-invariant subspace
and the chain
must stabilize to a
-invariant subspace
.
We claim that is nilpotent on
and
is invertible on
. Indeed, it is easy to see that
, which implies that
is invertible on
by the Rank-Nullity Theorem, and
for some
and thus
is nilpotent on
.
Next, we claim that . It is clear from what we have already shown that
. So it suffices to show that every
can be written as
with
and
. Without loss of generality (replacing
by a larger integer if necessary), we may assume that
and
for the same
. Since
, we have
for some
. Then
so
. Setting
gives the desired decomposition of
.
Finally, we show that the decomposition is unique. Suppose
with
nilpotent on
and invertible on
. Then
for some positive integer
, and
for every positive integer
. Thus
and
. By dimension considerations, we must have
and
.
Generalized Eigenvector Decomposition
Let be an eigenvalue of
. A generalized eigenvector for
with eigenvalue
is a vector
such that
for some positive integer
. The generalized eigenspace
is the subspace of
consisting of all generalized eigenvectors for
with eigenvalue
. Note that
can also be characterized as the nilpotent part of the Fitting Decomposition of
.
Lemma: If
is nilpotent on
and
is non-zero, then
is invertible on
.
Proof: Suppose . Then
, so
for all positive integers
. Choosing
large enough so that
, we have
which implies that
.
Theorem 2 (Generalized Eigenvector Decomposition): Assume that every eigenvalue of
(over some extension of
) is defined over
, and let
be the distinct eigenvalues of
. Then
Proof: Let be an eigenvalue of
, and let
be the Fitting Decomposition of
relative to
. Since
, it follows by induction that
is a direct sum of generalized eigenspaces for
. We claim that the generalized eigenspaces of
are precisely the
for
. Given this claim, the Theorem follows immediately. To prove the claim, we make the following observations:
(1) Every eigenvalue of restricted to
is equal to
for some
.
This follows from the easily verified facts that every eigenvalue of is also an eigenvalue of
, and
is not an eigenvalue of
.
(2) For , the generalized eigenspace of
with respect to
equals the generalized eigenspace of
with respect to
.
Any generalized eigenvector for is automatically a generalized eigenvector for
. Conversely, if
for some
, then the restriction of
to
is nilpotent, so by the Lemma the restriction of
to
is invertible. It follows that
for all positive integers
, so
by the proof of Theorem 1.
Nilpotent Operators and Cyclic Vectors
A subspace of
is called cyclic with respect to
if there is a vector
and a positive integer
such that
is a basis for
.
Theorem 3 (Cyclic Decomposition for Nilpotent Operators): If
is nilpotent on
, then
is a direct sum of cyclic subspaces for
.
Proof: Suppose that is nilpotent of exponent
, i.e.,
on
but
. Choose
with
and let
be the
-invariant subspace of
spanned by
. We claim that
has a
-invariant complement, i.e., there exists a
-invariant subspace
of
with
. Assuming the claim, it follows by induction that
is a direct sum of cyclic subspaces for
and the Theorem is proved.
To prove the claim, let and let
. Note that the restriction of
to
has exponent
, so by induction there is a
-invariant decomposition
. Let
. We make the following two observations:
(1)
To see this, note that if we have
and
for some
. As
, we have
.
(2)
Indeed, implies that
.
By (1) and (2), there exists a subspace with
such that
. (Augment a basis for
to a basis of
using vectors in
.) Since
, we can take
to be the desired
-invariant complement.
Dénouement
Combining Theorems 2 and 3, we deduce:
Theorem 4 (Jordan Canonical Form): There is an ordered basis
for
such that the matrix of
with respect to
is a block sum of elementary
Jordan matrices
. The number of Jordan blocks with a given size and given eigenvalue is independent of the choice of
.
Proof: By Theorem 2, is a direct sum of generalized eigenspaces
for
, and by Theorem 3 each
is a direct sum of cyclic subspaces for
. Amalgamating the various ordered bases coming from these cyclic subspsaces gives an ordered basis
for
with the required property. The uniqueness part follows from the easily verified observation that the number of Jordan blocks of size at least
and eigenvalue
is equal to
.
Corollary: Assume that
is algebraically closed. Then two
matrices
and
are similar over
if and only if they have the same eigenvalues (say
) and for all
and
we have
.
Very nice. At the risk of being pointlessly abstract, to get a decomposition independent of any choices, one can use the Jacobson-Morosov structure theorem for nilpotent operators. This is just the classical name for the Lefschetz-type filtration used for monodromy.
The argument in Theorem 3 is very nice. I remember finding this surprisingly hard to find a good elementary proof for when I did it last year; I think I’ll steal your approach next time. It is worth pointing out that the reason you know
is because, otherwise,
would have exponent larger than
.
Thanks, David — I’ve incorporated your suggestion to explain in more detail why
.
Nice article. Just a small remark: it’s clear that V_i and V_n are im T^p and ker T^p, respectively, with the same index p. So, by the rank-nullity theorem, they must have complementary dimension. Consequently, once you’ve (easily) shown that V_n ∩ V_i is trivial, you have V = V_n ⊕ V_i for free.
Good point, thanks!