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In the last third of the course we will apply what we have
learned about distributions, and a little more, to understand
properties of differential operators with constant coefficients.
Before I start talking about these, I want to prove another
density result.
So far we have not defined a topology on
- I will leave this as an optional
exercise.18 However we shall consider a
notion of convergence. Suppose
is a
sequence in
. It is said to converge
weakly to
if
 |
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There is no `uniformity' assumed here, it is rather like
pointwise convergence (except the linearity of the functions
makes it seem stronger).
Proof.
We can use Schwartz representation theorem to write, for some

depending on

,
We know that

is dense in

,
in the sense of metric spaces so we can find

,

in

. The density result then follows from the basic
properties of weak convergence.
Proof.
This follows by writing everyting in terms of pairings, for
example if
This weak density shows that our definition of
, and
are unique if we require Proposition 10.2 to hold.
We have discussed differentiation as an operator (meaning just a
linear map between spaces of function-like objects)
Any polynomial on
defines a differential operator19
 |
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Before discussing any general theorems let me consider some
examples.
Functions, or distributions, satisfying
are
said to be holomorphic, those satisfying
are
said to be harmonic.
This is quite hard to prove and not as interetsing as it might
seem. We will however give lots of examples, starting with
. Consider the function
 |
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Proof.
Since

is smooth and bounded away from the origin
the local integrability follows from the estimate, using polar
coordinates,
 |
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Differentiating directly in the region where it is smooth,
so indeed,

in

.
20
The derivative is really defined by
Here I have cut the space

out of the
integral and used the local integrability in taking the limit as

. Integrating by parts in

we find
There is a corrsponding formula for integration by parts in
so, recalling that
away from
,
assuming that both limits exist. Now, we can write
Replacing

by either

or

in
(
10.13) both limits are zero. For example
Thus we get the same result in (
10.13) by replacing

by

. Then

,
Let me remind you that we have already discussed the convolution
of functions
This makes sense provided
is of slow growth and
. In fact we can rewrite the definition in terms of pairing
 |
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where the
indicates the variable in the pairing.
Proof.
If

then for any fixed

,
Indeed the seminorm estimates required are
Since

and
we conclude that
The continuity of

means that for some
so it follows that
 |
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The argument above shows that
is a
continuous function of
with values in
, so
is continuous and satisfies (10.15). It is
therefore an element of
.
Differentiability follows in the same way since for each
,
with
the
th unit vector
is continuous in

,

. Thus,

has continuous partial derivatives and
The same argument then shows that

.
That

follows from the
definition of derivative of distributions
Finally consider the support property. Here we are assuming that
is compact; we also know that
is a
closed set. We have to show that
 |
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implies

for

near

. Now
(
10.16) just means that
 |
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Since

, so both statements mean that there
is
no

with

. This can also be written
and as we showed when discussing supports implies
From (
10.17) this is an
open condition on

, so
the support property follows.
Now suppose
and
.
Then
 |
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This is really Hörmander's Lemma 4.1.3 and Theorem 4.1.2; I
ask you to prove it as Problem 35.
We have shown that
is
if
and
, i.e., the regularity of
follows from the regularity of one of the factors. This
makes it reasonable to expect that
can be defined when
,
and one of them has compact
support. If
and
then
where
. In fact using
Problem 35,
 |
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Here,
are both smooth, but notice
Proof.
Since

has compact support there exists

such that

. Then
Thus, for some

,
where

is one of our norms on

.
Since

is supported in some large ball,
Thus

is
bounded for each

. The same argument applies to the
derivative using Theorem
10.6, so
In fact we get a little more, since we see that for each
there exists
and
(depending on
and
) such that
This means that
is a continuous linear map.
Now (10.19) allows us to define
when
and
has compact support by
Using the continuity above, I ask you to check that
in Problem 36. For the moment let me assume that this
convolution has the same properties as before - I ask you to
check the main parts of this in Problem 37.
Recall that
is a fundamental situation for
, a constant coefficient differential operator, if
. We also use a weaker notion.
Since the same
must work for nearby points in
(10.22), the set
is closed.
Furthermore
 |
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As Problem 37 I ask you to show that if
and
the
with
in a neighbourhood of
such that
. In particular
 |
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Proof.
One half of this is true for
any differential operator:
Proof.
We must show that

. Now, if

we can find

,

near

, such that

. Then
The first term is

and

, so

.
It remains to show the converse of (10.26) where
is
assumed to be hypoelliptic. Take
, a parametrix for
with
and assume, or
rather arrange, that
have compact support. In fact if
we can arrange that
Now
with
so
Since
it suffices to show that
Take
with
,
but
Then
,
so
where
and
. It follows that
.
Recall from last time that a differential operator
is said
to be hypoelliptic if there exists
with
 |
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The second condition here means that if
and
in
for some
then
. Since
we conclude that
and we may well suppose that
, replaced now by
,
has compact support. Last time I showed that
I will remind you of the proof later.
First however I want to discuss the important notion of
ellipticity. Remember that
is `really' just a
polynomial, called the characteristic polynomial
It has the property
This shows (if it isn't already obvious) that we can remove
from
thought of as an operator on
.
We can think of inverting
by dividing by
. This works well provided
, for all
. An example of this is
However even the Laplacian,
, does
not satisfy this rather stringent condition.
It is reasonable to expect the top order derivatives to be the
most important. We therefore consider
the leading part, or principal symbol, of
.
So what I want to show today is
We want to find a parametrix for
; we already know
that we might as well suppose that
has compact support.
Taking the Fourier transform of (10.27) we see that
should satisfy
 |
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Here we use the fact that
,
so
too.
First suppose that
is actually homogeneous
of degree
. Thus
The assumption at ellipticity means that
 |
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Since
is compact and
is continuous
 |
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for some constant
. Using homogeneity
 |
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Now, to get
from (10.28) we want to divide by
or multiply by
. The only problem
with defining
is at
. We shall simply
avoid this unfortunate point by choosing
as
before, with
in
.
Proof.
Clearly

is a continuous function and

, so

. It therefore
is the Fourier transform of some

.
Furthermore
Since

,

. Thus
is a parametrix for

. We still need to show the `hard part' that
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We can show (10.33) by considering the distributions
. The idea is that for
large,
vanishes rather rapidly at the origin and this
should `weaken' the singularity of
there. In fact we shall
show that
 |
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If you recall, these Sobolev spaces are defined in terms of the
Fourier transform, namely we must show that
Now
, so what we need to cinsider is the
behaviour of the derivatives of
, which is just
in (10.32).
Proof.
The estimate in (
10.36) for

is just
(
10.35). To prove the higher estimates that for each

there is a polynomial of degree at most

such that
 |
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Once we know (
10.37) we get (
10.36) straight away
since
We can prove (10.37) by induction, since it is certainly
true for
. Suppose it is true for
. To get the same identity for each
with
it is enough to differentiate one
of the identities with
once. Thus
Since

is a polynomial of
degree at most

this proves the lemma.
Going backwards, observe that
is
smooth in
, so (10.36) implies that
which certainly holds if
,
giving (10.34). Now, by Sobolev's embedding theorem
In particular this means that if we choose
with
then for every
,
is smooth and
Thus
and this is what we wanted to show,
.
So now we have actually proved that
is hypoelliptic if
it is elliptic. Rather than go through the proof again to make
sure, let me go on to the general case and in doing so review it.
Proof.
Proof of theorem.
We need to show that if

is elliptic then

has a
parametrix

as in (
10.27). From the discussion above
the ellipticity of

implies (and is equivalent to)
On the other hand
is a polynomial of degree at most

, so
This means that id

is large enough then in

,

, so
This means that

itself satisfies the conditions of
Lemma
10.14. Thus if

is equal
to

in a large enough ball then

in

and satisfies (
10.36) which can be
written
The discussion above now shows that defining

by

gives a solution to (
10.27).
The last step in the proof is to show that if
has compact support, and satisfies (10.27), then
Let me refine this result a little bit.
Proof.
We need to show that

then

. Once we can fix

,
we might as well suppose that

has compact support too.
Indeed, choose a large ball

so that
This is possible by the assumed boundedness of

.
Then choose

with

on

; it follows from Theorem L16.2, or rather its extension
to distributions, that

, so
we can replace

by

, noting that

. Now if

has compact
support we can choose compact neighbourhoods

,

of

and

such that

. Furthermore we an decompose

,

so that

,

and

. It follows that
Now,

, by the support property of
convolution and the three other terms are

, since at least
one of the factors is

. Thus

.
The most important example of a differential operator which is
hypoelliptic, but not elliptic, is the heat operator
 |
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In fact the distribution
is a fundamental solution. First we need to check that
is a distribution. Certainly
is
in
.
Moreover as
in
it vanishes with all
derivatives, so it is
except at
,
. Since it
is clearly measurable we will check that it is locally integrable
near the origin, i.e.,
 |
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since
. We can change variables, setting
, so
and the integral becomes
Since
is actually bounded near infinity, it follows that
,
As before we want to compute
First we check that
in
, where
it is a
function. This is a straightforward computation:
Now we can integrate by parts in (10.42) to get
Making the same change of variables as before,
,
As
the integral here is bounded by the integrable
function
, for some
, so by
Lebesgue's theorem of dominated convergence, conveys to the
integral of the limit. This is
Thus
so
is indeed a fundamental solution. Since it vanishes in
it is canned a forward fundamrntal solution.
Let's see what we can use it for.
Proof.
Naturally we try

. That it satisfies
(
10.43)follows from the properties of convolution.
Similarly if

is such that

then
So we need to show uniqueness. If
in two solutions of (10.43) then their difference
satisfies the `homogeneous' equation
. Furthermore,
in
for some
. Given any
choose
with
in
,
in
and consider
where

for some

,

near 0. Thus

has comapct support
and in fact

. I ask you to check this last
statement as Problem L18.P1.
Anyway,
Now,
Since
![$ \operatorname{supp} (\psi_{\overline{t}}) \subset \left\{ t \geq
\overline{t} \right. ]$](img1425.png)
, the second tier here is supported in

. Thus

in

,
but

is arbitrary, so

.
Notice that the assumption that
is not
redundant in the statement of the Proposition, if we allow ``large''
solutions they become non-unique. Problem L18.P2 asks you to
apply the fundamental solution to solve the initial value problem
for the heat operator.
Next we make similar use of the fundamental solution for
Laplace's operator. If
the
 |
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is a fundamental solution. You should check that
in
directly, I will show later that
, for the appropriate choice of
, but you can do it
directly, as in the case
.
Proof.
Since convolution

is
defined we certainly get a solution to

this way.
We need to check that

. First we know that

is hypoelliptic so we can decompose
and then

. In fact we can see from
(
10.44) that