In this lecture we define Riemannian structures and corresponding Laplace–Beltrami operators. We first study Riemannian structures on Rn to avoid technicalities in the presentation of the main ideas and then, in a later lecture, will extend our results to the manifold case.
We start with the following basic definition:
Definition: A Riemannian structure on is a smooth map
from
to the set of symmetric positive matrices.
In other words, a Riemannian structure induces at each point an inner product
, and the dependence
is asked to be smooth.
A natural way to define Riemannian structures, is to start from a family of smooth vector fields such that for every
,
is a basis of
. It is then easily seen that there is a unique Riemannian structure on
that makes for
,
an orthonormal basis.
Conversely, given a Riemannian structure on , it is possible to find smooth vector fields
on
such that for
,
an orthonormal basis for this Riemannian structure.
In this course, we shall mainly deal with such a point of view on Riemannian structures and use as much as possible the language of vector fields. This point of view is not restrictive and will allow more easy extensions to the sub-Riemannian case in a later part of the course.
Let us consider a family of smooth vector fields such that for every
,
is a basis of
. Without loss of generality we may assume that
Our goal is to associate to this Riemannian structure a canonical diffusion operator.
As a first step, we associate with the vector fields a natural Borel measure
which is the measure with density
with respect to the Lebesgue measure. This is the so-called Riemannian measure. The diffusion operator we want to consider shall be symmetric with respect to this measure.
Remark: Let be another system of smooth vector fields on
such that for every
,
is an orthonormal basis with respect to the inner product
. The systems of vector fields
and
are related one to each other through an orthogonal mapping. This implies that
In other words, the Riemannian measure
only depends on the Riemannian structure
.
Due to the fact that for every ,
is a basis of
, we may find smooth functions
‘s on $\mathbb{R}^n$ such that
Those functions are called the structure constants of the Riemannian structure. Every relevant geometric quantities may be expressed in terms of these functions. Of course, these functions depend on the choice of the vector fields $V_i$’s and thus are not Riemannian invariants, but several combinations of them, like curvature quantities, are Riemannian invariants.
The following proposition expresses the formal adjoint with respect to the Lebesgue measure of the vector field which is seen as an operator acting on the spave of smooth and compactly supported functions.
Proposition: If are smooth and compactly supported functions, then we have
where
Proof: Let us denote and
We have
We now compute
. We then observe that
Thus, we obtain
.
With this integration by parts formula in hands we are led to the following natural definition
Definition: The diffusion operator is called the Laplace-Beltrami operator associated with the Riemannian structure
.
The following straightforward properties of are let as an exercise to the reader:
is an elliptic operator;
- The Riemannian measure
is invariant for
;
- The operator
is symmetric with respect to
.
Exercise: Let be another system of smooth vector fields on
such that for every
,
is an orthonormal basis with respect to the inner product
. Show that
In other words, the Laplace-Beltrami operator is a Riemannian invariant: It only depends on the Riemannian structure
.
In order to apply the diffusion semigroup theory developed in the first lectures and construct without ambiguity the semigroup associated to the Laplace-Beltrami operator L, we need to know if L is essentially self-adjoint. Interestingly, this property of essential self-adjointness is clodely related to a metric property of the underlying Riemannian structure: The completeness of the associated distance.
Given an absolutely continuous curve , we define its Riemannian length by
If
, let us denote by
the set of absolutely continuous curves
such that
The Riemannian distance between
and
is defined by
By using reparametrization, we may define the Riemannian distance in a equivalent way by using the notion of sub-unit curve. Let
be an absolutely continuous curve. Since the vector fields
‘s form a basis of
at each point, we may find continuous functions
such that
The curve
is then said to be sub-unit if for almost every
,
. By using reparametrization, it is easily seen that for
,
.
Exercise: Let . Show that for every
,
An important fact is that hence defined is indeed a distance that induces the usual topology of
.
Definition: The function defined above is a distance that induces the usual topology of
.
Proof: Since any curve can be parametrized backwards and forwards, we have . The triangle inequality is easily proved by using juxtaposition of curves. Plainly
, so it remains to prove that if
then
. Let
such that
. Let us denote
. The closed Euclidean ball
is compact, therefore there exist two constants
such that for every
and
,
Let now
be an absolutely continuous curve such that
. Let
We have
As a consequence, we deduce that Therefore
is indeed a distance. Moreover, it is shown as above that for every
, there are constants
such that for every
,
This implies that
induces the usual topology of
As shown in the following proposition, the distance is intrinsically associated to the Laplace-Beltrami operator.
Proposition: For , we have
Proof: Let . We denote
Let
be a sub-unit curve such that
We can find
such that
and
. Let now
. From the change of variable formula we have,
Therefore, from Cauchy-Schwarz inequality,
As a consequence
We now prove the converse inequality which is trickier. The idea is to use the function that satisfies
and
. However, giving a precise meaning to
is not so easy, because it turns out that
is not differentiable at
. It suggests to use an approximation of the identity to regularize
and avoid the discussion of this differentiability issue. More precisely, fix
, and for
, consider the function
where
,
,
,
and
,
, has the property that
and
for
. Since for any
,
,
it is easy to see that
, for some constant
. Hence
The following theorem is known as the Hopf–Rinow theorem, it provides a necessary and sufficient condition for the completeness of the metric space .
Proposition: The metric space is complete (i.e. Cauchy sequences are convergent) if and only the compact sets are the closed and bounded sets.
Proof: It is clear that if closed and bounded sets are compact then the metric space is complete; It comes from the fact that Cauchy sequence are convergent if and only if they have at least one cluster value. So, we need to prove that closed and bounded sets for the distance
are compact provided that
is complete. To check this, it is enough to prove that closed balls are compact. Let
. Observe that if the closed ball
is compact for some
, then
is closed for any
. Define
Since
induces the usual topology of
,
. Let us assume that
and let us show that it leads to a contradiction. We first show that
is compact. Since
is assumed to be complete, it suffices to prove that
is totally bounded: That is, for every
there is a finite set
such that every point of
belongs to a
-neighborhood of
.
So, let small enough. By definition of
, the ball
is compact; It is therefore totally bounded. We can find a finite set
such that every point of
lies in a
-neighborhood of
. Let now
. We claim that there exists
such that
. If
, there is nothing to prove, we may therefore assume that
. Consider then a sub-unit curve
such that
,
. Let
We have
. On the other hand,
As a consequence,
In every case, there exists therefore
such that
. We may then pick
in
such that
. From the triangle inequality, we have
. So, at the end, it turns out that every point of
lies in a
-neighborhood of
. This shows that
is totally bounded and therefore compact because
is assumed to be complete. Actually, the previous argument shows more, it shows that if every point of
lies in a
-neighborhood of a finite
, then every point of
will lie
-neighborhood of
, so that the ball
is also compact. This contradicts the fact the definition of
. Therefore every closed ball is a compact set, due to the arbitrariness of
Checking that the metric space is complete is not always easy in concrete situations. From the Hopf-Rinow theorem, it suffices to prove that the closed balls are compact. The following proposition is therefore useful.
Proposition: Suppose that the vector fields ‘s have globally Lipschitz coefficients . Then the closed ball
is compact for every
and
. As a consequence the metric space
is complete.
Proof: By the hypothesis on the ‘s there exists a constant
such
that for any
. Fix
and let
, be a sub-unit curve such that
Letting
we obtain
We infer that
, for some
depending only on
. Integrating the latter inequality one has
. for some constant
. The previous estimate shows in particular, that
We conclude that
is Euclidean compact. Since the metric and the Euclidean topology coincide, it is also
-compact
Completeness of the metric space is related to the essential self-adjointness of the Laplace-Beltrami operator.
Theorem: If the metric space is complete, then the Laplace-Beltrami operator
is essentially self-adjoint.
Proof: We know that if there exists an increasing sequence such that
on
, and
, as
, then the operator
is essentially self-adjoint. We are therefore reduced to prove the existence of such a sequence. Let us fix a base point
. We can find an exhaustion function
such that
By the completeness of
and the Hopf-Rinow theorem, the level sets
are relatively compact and, furthermore,
as
. We now pick an increasing sequence of functions
such that
on
,
outside
, and
. If we set
, then we have
,
on
as
, and