The Heintze-Karcher inequality for metric measure spaces
Christian Ketterer

TL;DR
This paper extends the Heintze-Karcher inequality to non-branching metric measure spaces with Ricci curvature bounds, using needle decomposition, and characterizes equality cases in positively curved Riemannian settings.
Contribution
It generalizes the Heintze-Karcher inequality to a broad class of metric measure spaces with curvature bounds and characterizes equality cases in Riemannian curvature-dimension spaces.
Findings
Heintze-Karcher inequality proven for non-branching metric measure spaces
Equality case characterized in positively curved Riemannian spaces
Utilizes needle decomposition technique for the proof
Abstract
In this note we prove the Heintze-Karcher inequality in the context of essentially non-branching metric measure spaces satisfying a lower Ricci curvature bound in the sense of Lott-Sturm-Villani. The proof is based on the the needle decomposition technique for metric measure spaces introduced by Cavalletti-Mondino. Moreover, in the class of spaces satisfying a Riemannian curvature-dimension condition with positive curvature the equality case is characterized.
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The Heintze-Karcher inequality for metric measure spaces
Christian Ketterer
University of Toronto
Abstract.
In this note we prove the Heintze-Karcher inequality in the context of essentially non-branching metric measure spaces satisfying a lower Ricci curvature bound in the sense of Lott-Sturm-Villani. The proof is based on the needle decomposition technique for metric measure spaces introduced by Cavalletti-Mondino. Moreover, in the class of spaces with positive curvature the equality case is characterized.
2010 Mathematics Subject classification. Primary 53C21 30L99, Keywords: curvature-dimension condition, mean curvature, optimal transport, comparison geometry
The author is funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 396662902.
Contents
1. Introduction
The Heintze-Karcher theorem is a classical volume comparison result in Riemannian geometry [HK78] (see also [Mae78]). It states that the one sided tubular neighborhood of a two sided hypersurface in an -dimensional Riemannian manifold is bounded by a surface integral over involving the mean curvature, a lower bound for the Ricci curvature and an upper bound of the dimension . The original proof is based on Jacobi field computations and similar estimates were obtained in [Per16] applying refined Laplace comparison estimates for manifolds with boundary. When is equipped with a smooth measure , , a generalisation was proven by Bayle in [Bay04] (see also [Mor05]) where Ricci curvature is replaced by the Bakry-Emery -Ricci curvature, the mean curvature with generalized mean curvature and the volume of with the weighted volume. The Heintze-Karcher estimate found numerous applications in Riemannian geometry (e.g. [Mil15, Per16, MN14]).
In this note we prove Heintze and Karcher’s theorem in the context of essentially non-branching metric measure spaces with finite measure satisfying a lower Ricci curvature bound in the sense of Lott-Sturm-Villani [Stu06, LV09]. More precisely, we consider an essentially nonbranching space for and with finite measure and a generalized hypersurface that is the boundary of a Borel subset and satisfies . For this setup one can introduce a notion of mean curvature for using the -localisation technique for -Lipschitz functions established by Cavalletti-Mondino [CM17, CM18] (see also previous work by Klartag, Cafarelli, Feldman and McCann [Kla17, CFM02]).
Let us describe our approach. A precise construction is given in Section 5. Associated to we consider the signed distance function that is -Lipschitz for spaces. Then, the localisation technique provides a measurable decomposition of the space into geodesic segments , , and a disintegration of the measure with a quotient space . The measure is supported on and has a semiconcave density w.r.t. for -a.e. . One can define the outer mean curvature in any point satisfying for some and such that exists via
[TABLE]
Similar one defines the inner mean curvature in such a point as . Then, the mean curvature in is defined as
[TABLE]
This notion of generalized mean curvature will be sufficient to prove the Heintze-Karcher estimate. In smooth context, and will coincide with (minus) the classical mean curvature (Remark 5.8). Hence, our sign convention will be that the outer mean curvature of the boundary of a convex body is positive. The decomposition also allows to define a surface measure that is supported on points such that for some and such that exists (Definition 5.2). Again in smooth context this will coincide with the classical notion (Remark 5.4).
The main theorem of this note is the following.
Theorem 1.1**.**
Let be an essentially non-branching metric measure space with satisfying the condition for and . Let be a Borel subset such that and has finite outer curvature (see Definition 5.7). Then
[TABLE]
where and . is the Jacobian function (Definition 4.2).
If has finite curvature (Definition 5.7), then
[TABLE]
Remark 1.2*.*
The regularity assumption ”finite outer curvature” in the sense of Definition 5.7 is necessary even in smooth context for the validitiy of the statement above as surfaces with corners show.
Remark*.*
To keep the presentation short we only consider spaces with .
Theorem 1.1 is a generalisation of the Heintze-Karcher theorem and specializes to the classical statement in smooth context. The class of essentially nonbranching spaces includes for instance finite dimensional spaces, weighted Finsler manifolds with lower bounds for their -Ricci tensor and finite dimensional Alexandrov spaces.
We can assume an upper bound for the mean curvature and obtain the following Corollary.
Corollary 1.3**.**
Let be as in Theorem 1.1 with finite curvature. If , it follows
[TABLE]
If and then
Let be the diameter of a simply connected space form of constant curvature , i.e. or . In the case of the generalized Heintze-Karcher estimate also takes the following form.
Corollary 1.4**.**
Let be a metric measure space and let be as in the Theorem 1.1 with finite curvature. Assume . Then
[TABLE]
If , we obtain
[TABLE]
Remark 1.5*.*
The second estimate in the previous corollary also appears in the work of Heintze-Karcher [HK78, 2.2 Theorem].
Recall that the class of spaces can be enforced naturally to the class of spaces by requiring that the space of Sobolev functions is a Hilbert space. For positive and in the context of spaces with the following theorem characterizes the equality case in (2) and Corollary 1.4.
Theorem 1.6**.**
Let be a metric measure space that satisfies the condition for and and let be as in Theorem 1.1 with finite curvature.
Equality in (2) of Theorem 1.1 or in Corollary 1.4 holds if and only if there exists an space such that is a spherical suspension over :
[TABLE]
where and is a constant mean curvature surface in . More precisely, is a sphere centered at one of the poles of . Here, we use the warped product notation for spherical suspensions (compare with the exposition in Subsection 2.2)
The rest of this note is organized as follows. In section 2 we briefly recall some facts about optimal transport and the Wasserstein space of a metric measure space, the curvature-dimension condition for essentially non-branching metric measure spaces, warped products, the Cavalletti-Mondino isoperimetric comparison and a general disintegration theorem for measure spaces.
In section 3 we explain the -localisation technique by Cavalletti-Mondino and how it applies in the context of essentially non-branching metric measure spaces satisfying .
In section 4 we prove a simple comparison result in that follows from Sturm’s comparison theorem.
In section 5 we introduce the signed distance function for a set that arises as boundary of a Borel set in a metric measure space. We describe briefly how the localisation technique applies for this functions. This structure allows us to define the mean curvature of and the generalized surface measure . We also show that these notions coincide with the classical ones in the context of weighted Riemannian manifolds.
In section 6 we prove the main theorems of this note.
1.1. Acknowledgments
The author want to thank Robert McCann, Vitali Kapovitch and Robert Haslhofer for valuable discussions about topics related to this work and Samuel Borza for pointing out the reference [Mae78]. Moreover, the author is grateful to Robert McCann for reading carefully an early version of this article. The author is also very grateful to the anonymous referee for giving useful comments and remarks (especially Remark 5.9) that helped to improve the final version of this note.
2. Preliminaries
2.1. Curvature-dimension condition
In this subsection we recall some facts about optimal transport, the geometry of the Wasserstein space and synthetic Ricci curvature bounds. For more details we refer to [Vil09]. We also assume familarity with calculus on length metric spaces. For details we refer to [BBI01].
Let be a metric space. A rectifiable constant speed curve is a geodesic if where L is the induced length functional. We say is a geodesic metric space if for any pair there exists a geodesic between and . The set of all constant speed geodesics is denoted with and equipped with the topology of uniform convergence. For we write for the evaluation map.
A set is said to be non-branching if and only if for any two geodesics the following holds.
The set of Borel probability measures on such that for some is denoted . For any pair we denote with the -Wasserstein distance. We call the metric space the -Wasserstein space of . The subspace of probability measures with bounded support is denoted with .
Definition 2.1**.**
A metric measure space is a triple where is a complete and separable metric space and is a locally finite Borel measure.
The space of -absolutely continuous probability measures in is denoted by . Similar we define .
Any geodesic in can be lifted to a measure such that . We call such a measure a dynamical optimal plan.
A metric measure space is said to be essentially non-branching if for any two measures any dynamical optimal plan is concentrated on a set of non-branching geodesics.
Example 2.2*.*
Given a Riemannian manifold and a measure for we call the triple a weighted Riemannian manifold.
Definition 2.3**.**
For we define as the solution of
[TABLE]
is defined as solution of the same ODE with initial value . For , and we define the distortion coefficient as
[TABLE]
Note that . Moreover, using the convention for , and the modified distortion coefficient is defined as
[TABLE]
Definition 2.4** ([Stu06, LV09]).**
An essentially non-branching metric measure space satisfies the curvature-dimension condition for and if for every there exists a dynamical optimal coupling between and such that for all
[TABLE]
and for all where .
Example 2.5*.*
The metric measure space associated to a weighted Riemannian manifold for satisfies the condition , , , if and only if is geodesically convex and the Bakry-Emery -Ricci tensor is bounded from below by on .
Definition 2.6** ([AGS14, Gig15, EKS15, CM16, AMS19]).**
The Riemannian curvature-dimension condition for and is defined as the condition together with the property that the associated Sobolev space is a Hilbert space.
For a brief overview of the historical development of the previous definition we also refer to the preliminaries of [KK17].
2.2. Warped products
For and the -dimensional model space is
[TABLE]
where is equipped with the restriction of the standard metric on . The metric measure space satisfies [Stu06, Example 1.8].
Let be a weighted Riemannian manifold with and . The warped product between and w.r.t. is defined as the metric completion of the weighted Riemannian manifold where and . In [Ket13] it was proved that if the warping function satisfies
[TABLE]
and satisfies then satisfies . This applies in particular when and . Then the corresponding warped product is a spherical suspension. For instance, we can choose . If we can choose and we get that
More generally, one can define warped products in the context of metric measure spaces. In [Ket15] it was proved that satisfies the condition if and only if satisfies the condition .
2.3. Isoperimetric profile
Let be a metric measure space such that is finite, and let . Denote the -tubular neigborhood of . We also set . The (outer) Minkowski content of is defined by
[TABLE]
The isoperimetric profile function of is defined as follows. Let be the probability measure proportional to . Then, we set
[TABLE]
Let . The model isoperimetric profile for spaces with Ricci curvature bigger or equal than and dimension bounded above by is given by where is again the -dimensional model space that was introduced in the previous section.
The following theorem is one of the main results in [CM17] and generalizes the Levy-Gromov isoperimetric inequality for Riemannina manifolds.
Theorem 2.7** (Cavalletti-Mondino).**
Let be an essentially non-branching space for and . Then for every Borel set it holds that
[TABLE]
If satisfies the condition and there exists with equality in (3) then
[TABLE]
*for some space . Moreover, is a closed geodesic ball of volume centered at one of the origins of . *
2.4. Disintegration of measures
For further details about the content of this section we refer to [Fre06, Section 452].
Let be a measurable space, and let be a map for a set . One can equip with the -algebra that is induced by where if . Given a probability measure on , one can define a probability measure on via the pushforward .
Definition 2.8**.**
A disintegration of that is consistent with is a map such that the following holds
- •
is a probability measure on for every ,
- •
is -measurable for every ,
and for all and the consistency condition
[TABLE]
holds. We use the notation for such a disintegration. We call the measures conditional probability measures.
A disintegration is called strongly consistent with respect if for -a.e. we have .
Theorem 2.9**.**
Assume that is a countably generated probabilty space and is a partition of . Let be the quotient map associated to this partition, that is if and only if and assume the corresponding quotient space is a Polish space.
Then, there exists a strongly consistent disintegration of w.r.t. that is unique in the following sense: if is another consistent disintegration of w.r.t. then for -a.e. .
3. -localisation of generalized Ricci curvature bounds.
In this section we will briefly recall the localisation technique introduced by Cavalletti and Mondino. The presentation follows Section 3 and 4 in [CM17]. We assume familarity with basic concepts in optimal transport (for instance [Vil09]).
Let be a locally compact metric measure space that is essentially nonbranching. We assume that and .
Let be a -Lipschitz function. Then
[TABLE]
is a -cyclically monotone set, and one defines . The union defines a relation on , and induces the transport set with endpoints
[TABLE]
where . For one defines and similar and . Since is -Lipschitz, and are closed as well as and .
The forward and backward branching points are defined respectively as
[TABLE]
Then one considers the (nonbranched) transport set and the (nonbrached) transport relation that is the restriction of to .
As showed in [CM17] , and are -compact, and is a Borel set. In [Cav14] Cavalletti shows that the restriction of to is an equivalence relation. Hence, from one obtains a partition of into a disjoint family of equivalence classes . There exists a measurable section , that is , and can be identified with the image of under . Every is isometric to an interval via an isometry where is parametrized such that , , for the section before. The map extends to a geodesic also denoted and defined on the closure of . We set .
The index set can also be written as
[TABLE]
and for , and is equipped with the induced measurable structure [CM17, Lemma 3.9]. Then, the quotient map is measurable, and we set .
Theorem 3.1**.**
Let be a compact geodesic metric measure space with and finite. Let be a -Lipschitz function, let be the induced partition of via , and let be the induced quotient map as above. Then, there exists a unique strongly consistent disintegration of w.r.t. .
Now, we assume that is an essentially non-branching space for and . The following lemma is Theorem 3.4 in [CM17].
Lemma 3.2**.**
Let be an essentially non-branching space for and with and . Then, for any -Lipschitz function , it holds .
The initial and final points are defined as follows
[TABLE]
In [CM16, Theorem 7.10] it was proved that under the assumption of the previous lemma there exists with such that for one has . In particular, for we have
[TABLE]
where denotes the relative interior of the closed set .
Theorem 3.3**.**
Let be an essentially non-branching space with , , and .
Then, for any -Lipschitz function there exists a disintegration of that is strongly consistent with .
Moreover, there exists such that and , is a Radon measure with and verifies the condition .
More precisely, for all it holds that
[TABLE]
for every geodesic .
Remark 3.4*.*
The property (5) yields that is locally Lipschitz continuous on [CM17, Section 4], and that satifies
[TABLE]
Remark 3.5*.*
The Bishop-Gromov volume monotonicity implies that can always be extended to continuous function on [CM18, Remark 2.14]. Then (5) holds for every geodesic . We set and consider as function that is defined everywhere on . We also consider defined via .
Remark 3.6*.*
In the following we set . Then, and for every the inequality (5) and (4) hold. We also set and .
4. -dimensional comparison results
Let such that
[TABLE]
for any constant speed geodesic . Then is semi-concave and therefore locally Lipschitz on . satisfies in distributional sense [EKS15, Lemma 2.8]. The limits
[TABLE]
exist for every and are in for . If then is continuous in [math]. Moreover, is continuous from the right/left on , and
[TABLE]
with equality if and only if is differentiable in . In particular is locally semi-concave, and is twice differentiable -almost everywhere.
Lemma 4.1**.**
Let be as above. Let . Then
[TABLE]
In particular, the right hand side is positive on .
Proof.
Consider with and . We set
[TABLE]
for . We choose small enough such that . Then
[TABLE]
Hence, by classical Sturm comparison [dC92] we obtain
[TABLE]
Now, one can check that on if and , and also
[TABLE]
Hence, we obtain that
[TABLE]
Finally, since we can choose arbitrarily small, we obtain the result. ∎
Definition 4.2**.**
Let , , . The Jacobian function is defined as
[TABLE]
is pointwise monotone non-decreasing in and , and monotone non-increasing in .
Corollary 4.3**.**
Let such that and for any constant speed geodesic it holds
[TABLE]
Then where
Proof.
Applyng Lemma 4.1 to yields
[TABLE]
Now, we note that , we devide by and apply to both sides. ∎
5. Mean curvature in the context of spaces.
Let be a metric measure space as in Theorem 3.3. Let be a closed subset, and let such that . The function is given by
[TABLE]
Let us also define . The signed distance function for is given by
[TABLE]
It follows that if and only if , if and if . It is clear that and . Setting we can also write
[TABLE]
is -Lipschitz. denote the topological interior of .
Let be the transport set of with endpoints. We have . In particular, we have by Lemma 3.2.
Therefore, the -Lipschitz function induces a partition of up to a set of measure zero for a measurable quotient space , and a disintegration that is strongly consistent with the partition. The subset , , is the image of a geodesic .
We consider as in Remark 3.6. One has the representation
[TABLE]
For any transport ray , , it holds that and
Remark 5.1*.*
It is easy to see that is a measurable subset. The set is defined such that we have for a unique . Then, the map is a measurable section on , one can identify the measurable set with and one can parametrize such that . Moreover, we define
[TABLE]
The sets and are measurable, and also
[TABLE]
as well as and are measurable. The map is measurable (see [CM16, Proposition 10.4]).
Definition 5.2**.**
We define a surface measure via
[TABLE]
for any continuous function . That is is the pushforward of under the map .
Remark 5.3*.*
We note that the measure is by definition concentrated on .
Remark 5.4*.*
Let us adress briefly the smooth case. Let be compact weighted Riemannian manifold. Let (with for ). Assume that is an -dimensional compact -submanifold. Then, the signed distance function is smooth on a neighborhood of and is the smooth unit normal vectorfield along . More precisely, and for all . We denote the induced volume for .
Recall that for every there exist and such that is a minimal geodesic on , and we define
[TABLE]
and the map via . It is well-known that is a diffeomorphism on , that and that integrals can be computed effectively by the following formula:
[TABLE]
On the other hand, we can define a map via where is the projection map. Then , , are precisely the non-branched transport geodesics w.r.t. , and . Moreover, we see that
[TABLE]
Hence, in this case we can identify with , and the quotient measure on with . The integration formula (8) becomes
[TABLE]
By the uniqueness statement in the disintegration theorem and by (9) we therefore have that and .
It follows that for a measurable set that
[TABLE]
Hence, the measure coincides with in this case.
Let us recall another result of Cavalletti-Mondino.
Theorem 5.5** ([CM18]).**
Let be an space, and and as above. Then , and one element of that we denote with is the Radon functional on given by the representation formula
[TABLE]
We note that the Radon functional can be represented as the difference of two measures and such that
[TABLE]
where denotes the -absolutely continuous part in the Lebesgue decomposition of . In particular, coincides with a measurable function -a.e. .
Remark 5.6*.*
In the light of the previous section and since is semiconcave on , coincides -a.e. with the function that is defined via
[TABLE]
Hence, are measurable functions on and everywhere defined on .
Definition 5.7**.**
Set and let be the induced disintegration.
We say that has finite outer curvature if , has finite inner curvature if , and has finite curvature if .
Provided has finite outer curvature we define the outer mean curvature of as
[TABLE]
If we switch the roles of and and has finite inner curvature, then we call the corresponding outer mean curvature the inner mean curvature and we write .
For with finite curvature the mean curvature is defined as .
Remark 5.8*.*
Let us again go back to the smooth situation of Remark 5.4. In this case , , is smooth on the maximal open interval where is a geodesic. Moreover, is a smooth map. Hence
[TABLE]
for where denotes the mean curvature vector along . We conclude that in this case our notion of mean curvature coincides with the classical one.
Remark 5.9*.*
As was pointed out to the author by the referee the property of having finite outer/inner curvature in the sense of the previous definition corresponds to an interior/exterior ball condition for what is a condition on the full second fundamental form of the boundary in smooth context.
Remark 5.10*.*
The definition of mean curvature as given in Definition 5.7 is sufficient for the Heintze-Karcher theorem. But considering Theorem 5.5 one might define the mean curvature of as the measure given by
[TABLE]
6. Proof of the main theorems
Proof of Theorem 1.1. Let be closed subset, and as before. Consider
[TABLE]
where . One has via . One can check that
[TABLE]
We assume finite outer curvature, that is . Moreover, and therefore . Let . Theorem 3.3 (-localisation) and Corollary 4.3 yield
[TABLE]
This is the first claim in Theorem 1.1.
Now, we assume finite curvature. By switching the roles of and we obtain similarly
[TABLE]
Note that by the symmetries of and we have that . In the last inequality we use . Hence
[TABLE]
This proves Theorem 1.1. ∎
Proof of Corollary 1.3. Let us prove the second claim of the corollary. The first one follows from Theorem 1.1. Assume , has finite curvature and . Then on and from the proof of the main theorem we get that
[TABLE]
When we let , the claim follows.
Proof of Corollary 1.4. Let . Consider where is the connected component of that contains . solves on and a straighforward computation yields
[TABLE]
We set . We can see that up to translation must coincide with . Hence
[TABLE]
We can plug this back into the Heintze-Karcher inequality (2) and obtain Corollary 1.4. ∎
Proof of Theorem 1.6. Assume and equality in the Heintze-Karcher estimate (2), or equivalently assume equality in Corollary 1.4.
Then, all the inequalities in the proof before become equalities. In particular, from Corollary 4.3 we obtain that
[TABLE]
Recall that is a probability measure for by construction of the disintegration. Plugging that back into the Heintze-Karcher inequality yields
[TABLE]
We consider . The corresponding Minkowski content computes as
[TABLE]
where is a probability measure and . We also observe that
[TABLE]
We set . exists and is monotone nondecreasing where . One can check that . Moreover, we compute
[TABLE]
We see that is monotone nonincreasing, hence is concave. Jensen’s inequality yields that
[TABLE]
Hence by Theorem 2.7 there is equality and Theorem 2.7 yields the result. ∎
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