Abstract
Let be non-empty, open and proper. This paper is concerned with , the space of p-integrable Borel measures on equipped with the partial transportation metric introduced by Figalli and Gigli that allows the creation and destruction of mass on . Alternatively, we show that is isometric to a subset of Borel measures with the ordinary Wasserstein distance, on the one point completion of equipped with the shortcut metric
In this article we construct bi-Lipschitz embeddings of the set of unordered m-tuples in into Hilbert space. This generalises Almgren’s bi-Lipschitz embedding theorem to the setting of optimal partial transport.
Introduction
A striking variety of problems in geometry, analysis, combinatorics and a vast number of applications can be neatly formulated in terms of measures and their comparison using transportation metrics. The prototypical transportation metric is the p-Wasserstein distance [2]. This is defined between two Borel measures of the same total mass on a metric space (X, d) by
1 |
where and the infimum is taken over all measures on with coordinate projections and . The resulting metric space of p-integrable probability measures equipped with is denoted by (see Definition 2.1).
A drawback of the Wasserstein distance is the requirement that the compared measures must have the same total mass. Recently emerging theories of optimal partial transport pertain to the transportation of measures without a mass constraint [8, 16, 20]. This article concerns the following formulation due to Figalli and Gigli [11].
Let be an open non-empty proper subset of X. For measures and on , one defines as in (1), but the infimum is taken over measures on with
The resulting metric space of p-integrable measures, equipped with , will be denoted by (see Definition 3.1).
The key property of is that can be used to destroy or create mass, at a cost of transporting it to or from . This allows measures of different total masses to be compared and hence one can construct a metric space consisting of all measures, instead of restricting to probability measures. Understanding the interplay between transportation metrics and is motivated by solving evolution equations with Dirichlet boundary conditions from gradient flows [11, 21]. The metric has found further applications such as obtaining new comparison principles for viscosity solutions [13].
A natural approach to study a metric space is to embed it into a well known space, such as a Euclidean or Banach space, as this allows the metric space to inherit geometric properties of the ambient space. Recall that the distortion of an injective map f between two metric spaces is , where is the Lipschitz constant of f; f is bi-Lipschitz if it has finite distortion. Since bi-Lipschitz embeddings preserve relative distances, they are central to analysis and metric geometry [18] and have applications to algorithm design [14].
Due to the prominence of the Wasserstein spaces in various areas of mathematics, their embeddability has attracted much attention. The non-embeddability (into ) of over various discrete metric spaces [5] such as the planar grid [19] and Hamming cube [15] is known, as is the non-embeddability of for [4]. The interest in bi-Lipschitz embeddings of the Wasserstein spaces dates back to the work of Almgren [1, 9], forming the foundations of his celebrated partial regularity theorem for area minimising currents. Almgren proved that, for any , the set of unordered -tuples of points in ,
equipped with , bi-Lipschitz embeds into some Euclidean space (see Theorem 2.3). Here and throughout, will denote the Dirac mass at x.
In this article we generalise Almgren’s embedding to .
Theorem 1.1
For , let be non-empty, open and proper. The space of unordered tuples of at most points bi-Lipschitz embeds into Hilbert space. The distortion of our embedding is at most , for some constant .
In general, is not a doubling metric space and hence cannot be bi-Lipschitz embedded into any Euclidean space, see Lemma 3.8. Therefore Hilbert space1 becomes the natural target for an embedding. Note that, since we are not constrained to comparing measures of the same total mass, in Theorem 1.1 we consider unordered tuples of at most -points.
To prove Theorem 1.1, we first show, for , that isometrically embeds into the ordinary p-Wasserstein space of measures on , where is the one point completion of equipped with the shortcut metric
for every (see Lemma 3.3). This embedding maps to and so, in order to prove Theorem 1.1, it remains to construct a bi-Lipschitz embedding of into Hilbert space.
We do this, for , by considering a Whitney decomposition of into cubes. This decomposition is chosen such that, inside any cube , the shortcut metric equals the Euclidean metric and consequently
2 |
In particular, Almgren’s theorem gives an embedding of each into some Euclidean space. Despite the fact that any measure can be written as a sum of measures supported on cubes in , the construction of the required bi-Lipschitz embedding of cannot be obtained simply by restricting to cubes. Indeed, may not even be defined between the restriction of two measures to a cube; even when it is, simple examples show that the optimal transport of the restricted measures may be incomparable to the optimal transport of the original measures.
Our approach uses (2) as the starting point to determine the optimal transport of measures between different cubes, see Sect. 4. From this analysis we construct a bi-Lipschitz embedding of into the -sum of infinitely many copies of , see Theorem 4.12. The proof of Theorem 1.1 is concluded in Sect. 5 by applying Almgren’s embedding to each term of the -sum.
We mention an application of Theorem 1.1 to persistence homology. The space of persistence barcodes can be viewed as for
see [10]. Theorem 1.1 shows that the space of persistence barcodes with at most -points can be bi-Lipschitz embedded into Hilbert space. This answers questions raised by Carrière and Bauer [6]. Prior to our results, it was known that coarsely embeds into Hilbert space [17]. In fact, Theorem 1.1 applies to the generalised persistence barcodes introduced in [7] whenever the ambient space is Euclidean. Our theorem also holds when is equipped with any for ; due to the equivalence of norms on , these metrics are all bi-Lipschitz equivalent.
Finally, we mention that the distortion of any embedding of into Hilbert space, for , must necessarily converge to as does, see Remark 5.3.
Wasserstein distance and Almgren’s embedding
Let (X, d) be a complete and separable metric space. We write for the set of Borel measures on X and for the set of Borel probability measures on X. The Wasserstein space is defined as follows [2, 3].
Definition 2.1
For and define
where the infimum is taken over all couplings with coordinate projections and . Note that only if as otherwise there does not exist a as in Definition 2.1.
Let be those with
for some (equivalently all) . Then defines a metric on . Analogous statements hold for the case , where the integral is replaced by an essential supremum. We write for the set equipped with .
Definition 2.2
For , define the space of unordered m-tuples
equipped with . Note that, on , equals
where and .
A fundamental step in Almgren’s study of area minimising currents was the following bi-Lipschitz embedding.
Theorem 2.3
(Almgren, Theorem 2.1 [9]) For every there exists an and a bi-Lipschitz embedding . By inspecting the proof one sees that and, for all ,
for a constant .
Optimal partial transport and the shortcut metric
The transportation metric introduced by Figalli and Gigli [11] is defined between two Borel measures. Originally defined for open and bounded , we state the natural generalisation of to complete and separable metric spaces (X, d) (the proof of the triangle inequality is identical).
Definition 3.1
Let be proper and non-empty. For and define
where the infimum is taken over all couplings with and . Then defines a metric on
Analogous statements hold for the case , where the integral is replaced by an essential supremum.
We write for the set equipped with . We also write for the set of with , equipped with .
The first step in our proof of Theorem 1.1 is to show an equivalence between and , for the shortcut metric space, defined as the one point completion of via its complement.
Definition 3.2
For non-empty and proper, let . For define
and . Then defines a metric on .
Profeta and Sturm [21, Remark 1.9] mention that isometrically embeds into , and give an example showing that their embedding is not an isometry for . We show that there exists an isometric embedding of into for any . Here we write for the space of measures with total mass equal to 2.
Lemma 3.3
Let X be a separable metric space and be non-empty and proper. For any , the map
is an isometric embedding.
Proof
Given a coupling for we use it to construct a coupling for and vice versa.
First let and suppose that is a coupling for and in . Let for all and define as
For notational convenience, we let denote the coefficient of in this expression. Then
Similarly, by symmetry, . Thus is a coupling of and in . Moreover,
3 |
Therefore,
Conversely, let be a coupling for and in . Define the closed set
Fix and for each , let with
Since X is separable, c may be chosen to be a Borel function with countable image. Let and and define
4 |
Note that, since is supported on , its restriction to equals 0. Therefore,
Similarly, by symmetry, . Hence is a coupling for and in .
Now, for any ,
Therefore,
5 |
Since is arbitrary, this shows that
Remark 3.4
After the first version of this article appeared, we were made aware that the statement of Lemma 3.3, for the case as defined in our introduction, appears in the work of Divol and Lacombe [10, Proposition 3.15]. Note that our proof does not rely on the existence of unique closest points in , whilst the one in [10] does. However, a flaw in their argument makes the proof incorrect even for the case of .
Central to their proof is the definition of a measure and the claim that it is a coupling of and in (using the variables of [10, Lemma 3.17]). Using this they derive [10, Equation (3.8)] from which the proof is concluded. However, examples such as [21, Remark 1.9] show this equation to be false. Moreover, this equation would imply that in . These contradictions originate in the fact that is not a coupling of and , which can be verified by comparing the total measure of to that of or .
Since the map
has distortion , we obtain the following corollary.
Corollary 3.5
Let X be a separable metric space and be non-empty and proper. Then bi-Lipschitz embeds into with distortion 2.
The same proof as the one for Lemma 3.3 shows that the full space isometrically embeds into .
Lemma 3.6
Let X be a separable metric space and non-empty and proper. For any ,
is an isometric embedding.
Remark 3.7
For any ,
Therefore, the triangle inequality for implies that is indeed a metric on the image of .
Proof
(Proof of Lemma 3.6) If then
defines a coupling of and . The calculation in (3) shows that
Conversely, if , then as defined in (4) is a coupling for and (5) shows that
The shortcut metric space is not doubling
A metric space X is doubling if there exists such that each ball is covered by N balls of half the radius of B.
Lemma 3.8
For , let be non-empty and open such that is a proper subset of . Then for any and any sufficiently small , there exist with for each . In particular, is not doubling.
Proof
Let and . For , let lie on the circle centred on x of radius (such points exist since is open). For each , let be the line segment connecting to x and let be the connected component of containing . Since , there exists such that
Now, is continuous on each and converges to 0 as one travels along towards . Therefore, for each sufficiently small and each , there exists with . In particular, if , then for each .
Finally, we see that for each , but we require at least N balls of radius to cover . Since is arbitrary, cannot be doubling.
Remark 3.9
Lemma 3.8 is sharp in the following sense. If , then is bi-Lipschitz equivalent to a Euclidean circle. For any , if , then is isometric to . In both of these cases, the conclusion of Lemma 3.8 fails.
Note that each Euclidean space is doubling and that the doubling property is preserved under taking subsets and bi-Lipschitz images. Therefore, if a metric space is bi-Lipschitz embeddable into some Euclidean space, it must necessarily be doubling.
Corollary 3.10
For let be non-empty and open such that is a proper subset of . Then is not bi-Lipschitz embeddable into any Euclidean space.
The space of unordered tuples of at most points
Definition 3.11
Let X be a metric space, non-empty and proper and . Define the space of unordered tuples of at most m points as
with the metric inherited from .
This space is naturally identified with a subset of .
Corollary 3.12
Let . For any separable metric space X and non-empty and proper , isometrically embeds into via the map
Proof
Embed into by , apply Lemma 3.3, and then embed into by .
A bi-Lipschitz description of in terms of
To construct the bi-Lipschitz embedding from Theorem 1.1, it would be natural to adapt the techniques from the proof of Theorem 2.3 to our setting. However, the proof of Theorem 2.3 strictly depends on both, the linear structure of (in particular the existence of projections), and the compactness of the unit ball. Although as a set, bears no relationship to the linear structure of and this fact prohibits the direct use of Almgren’s techniques. On the other hand, whilst it is possible to find a bi-Lipschitz embedding of into to gain a linear structure, this comes at the expense of compactness of the unit ball. Thus it is not possible to modify Almgren’s proof to our setting.
In order to prove Theorem 1.1 we will use a Whitney decomposition of into cubes
(see Proposition 4.2) such that, within each , is given by . Consequently, . Theorem 2.3 then gives a bi-Lipschitz embedding of each into and it would be favourable to use these embeddings as “coordinate projections" to construct a global embedding into Hilbert space. Of course, the union of the does not cover and therefore we cannot simply define coordinate projections by taking restrictions to each . Nevertheless, the fact that enables us to construct a map which, roughly speaking, acts as a smooth projection to .
The main result of this section shows that the can be combined to define a bi-Lipschitz embedding of into the following metric space.
Definition 4.1
Let be a countable set and define
to be the -sum of copies of . That is, consists of sequences
of elements of for which
where , equipped with the metric
Once we have an embedding into , we will show that it is possible to find an embedding into . Indeed, in Sect. 5, we apply Theorem 2.3 to each term in the definition of to obtain a bi-Lipschitz embedding of into .
A Whitney decomposition of
To construct the embedding into , we will use a Whitney decomposition of . For a cube , let denote the side length of .
Proposition 4.2
(Appendix J [12]) Let be non-empty, open and proper. There exists a family of closed cubes such that
and the elements of have disjoint interiors.
for all .
- If and then
We say that are neighbours. Each has at most neighbours.
A Whitney decomposition of estimates which quantity attains the minimum in the definition of .
Lemma 4.3
Let be a Whitney decomposition of , and and . Then
6 |
If are neighbours then
7 |
If are not neighbours then
8 |
Proof
The first inequality in (6) is implied by . The second follows from the triangle inequality:
Now suppose are neighbours and let . Then by (6),
giving (7). On the other hand, suppose that are not neighbours and . Then for a neighbour of . In particular
giving the first inequality in (8). The second inequality follows from (6).
For the remainder of the paper we fix , non-empty, open and proper and a Whitney decomposition of as in Proposition 4.2. We also fix as in Definition 4.1.
Constructing a coordinate system
To construct a bi-Lipschitz embedding of into , we define projections
that serve as a coordinate system for . The embedding into will then be defined as the -sum of the (see Definition 4.6).
We begin with the construction of a function that approximates the identity within a given , is supported on the neighbours of , and maintains bi-Lipschitz bounds with . For and , we write for the closed r-neighbourhood of .
Lemma 4.4
For each there exists a map
such that
is -Lipschitz;
for all . In particular, is supported on the neighbours of ;
;
- For all ,
The extension of to , defined by , is -Lipschitz with respect to ;
- If and , then
Proof
Fix and let c be the centre of . For each , let
That is, is an -Lipschitz function with that equals 1 on and 0 on . We also set
a 1-Lipschitz function satisfying for all x in the support of .
Define . Since is a product of Lipschitz functions, the Lipschitz constant of is bounded above by
This demonstrates item 1. Items 2 to 4 are immediate.
To see item 5, first let be such that . Then by item 2, for a neighbour of , so that . Therefore, by item 3,
using Eq. (6) for the final inequality. Thus
holds for any (including ). Therefore, by the triangle inequality, for any ,
Combining this inequality with item 1 shows that is -Lipschitz with respect to on .
Finally, to see item 6, first suppose that . Then by item 2,
so that item 6 holds in this case.
In the case we will show that
9 |
completing the proof of item 6. To this end, note that
Therefore, by considering the first component of , we see that
Thus, if
10 |
then (9) holds. On the other hand, if (10) does not hold, then by considering the final component of , we have
giving (9).
The pushforwards under each define our coordinate projections on .
Definition 4.5
For every , define to be the pushforward under . That is,
Recall the construction of from Definition 4.1.
Definition 4.6
Define the embedding by
This is well defined since each is supported on the neighbours of , so that each is contained in the support of at most of the .
is bi-Lipschitz
In this section we show that is a bi-Lipschitz embedding, beginning by showing that it is Lipschitz.
For and , let
From now on we use the notation to denote the element of arising from the natural action of the symmetric group on : for each .
Lemma 4.7
For any ,
where depends only upon n.
Proof
Fix and let and . Set
so that, by Lemma 4.4 item 2,
Applying Lemma 4.4 item 5 gives
Therefore
Further,
since is contained within the union of the neighbours of . The result follows for .
To prove the lower Lipschitz bound, we fix the following notation until the end of the section.
Notation 4.8
Fix and, for every , let be such that
11 |
Let . For integer , the annuli
are disjoint and so there exists such that
12 |
Set
Note that is contained within the union of the neighbours of .
Let and define to be the set of for which
13 |
Set
To obtain a lower bound of
14 |
in terms of , we will construct a for which is comparable to (14). A first attempt to do this may be, for each and each , to define . Of course, a defined in this way need not be injective, for example if there exist and such that . Nonetheless, we will show that it is possible to construct a permutation for the cubes in . Indeed, we now show that conditions (12) and (13) ensure that, for each , if and only if : (12) provides a moat surrounding and (13) ensures that the distance between and is less than the width of the moat.
Lemma 4.9
For any ,
15 |
and
16 |
Moreover, if with ,
17 |
Proof
For any , (13) and Lemma 4.4 item 6 imply
In particular,
18 |
Therefore (12) implies that . By symmetry, if then and so (15) holds. Since , Lemma 4.4 item 4 implies (16).
Now let with and . Then (18) for R implies
and so (12) implies . The similar argument with p and exchanged gives (17).
By carefully partitioning E using the , we use Lemma 4.9 to construct the desired permutation on .
Proposition 4.10
There exists a bijection such that
Proof
Let
Note that, by (15), can equivalently be defined as the set of with . Since is finite, we enumerate it as
in such a way that
Then, for , applying Lemma 4.9 with and gives
19 |
Let and for each define
Then (19) implies that is a permutation between and for each . Therefore, we define a bijection
by setting to equal on for each . Then
using (16) for the third equality. Finally (11) completes the proof.
Next we consider the points outside E for which we use the distance to to estimate .
Lemma 4.11
For any bijection
we have
for that depends only upon n.
Proof
For a moment fix and let contain . Then necessarily . Therefore (13) and (6) imply
Since each contains at most m such points ,
The same estimate for gives the desired inequality for .
We combine our previous results to show that is a bi-Lipschitz embedding.
Theorem 4.12
For any ,
where depends only upon n.
Proof
The right hand inequality is given by Lemma 4.7.
For the left hand inequality, let be the bijection obtained from Proposition 4.10 and arbitrarily extend it to a bijection of . Then
using Proposition 4.10 and Lemma 4.11 for the first inequality.
The embedding into Hilbert space
In this section we conclude the proof of Theorem 1.1. Let be the embedding given by Theorem 2.3. We write
as a direct -sum over . Recall the construction of from Definition 4.1.
Lemma 5.1
The function defined by
is well defined. Moreover, for any ,
for depending only upon n.
Proof
Let , so that
Since is 1-Lipschitz this implies that
Hence, is well defined. Moreover, using that is 1-Lipschitz again, we have, for any ,
so that is also 1-Lipschitz. Finally, Theorem 2.3 gives
Theorem 5.2
There exists a bi-Lipschitz embedding with distortion at most , for depending only upon n. That is, for any ,
Proof
First isometrically embed into via Corollary 3.12. One then applies Theorem 4.12 to bi-Lipschitz embed into . Finally, Lemma 5.1 bi-Lipschitz embeds into , as required.
Remark 5.3
For , the distortion of any embedding of into converges to as increases. In particular, does not bi-Lipschitz embed into .
Indeed, by Eq. (7) we see that contains an isometric copy of for some cube Q. Thus, the distortion of any embedding into is at least that of . For , Andoni, Naor and Nieman [4, Theorem 7] prove that does not coarsely, in particular bi-Lipschitz, embed into any Banach space of non-trivial type, namely Hilbert space. Since the set of discrete measures is dense in , a scaling argument shows that the distortion of any bi-Lipschitz embedding of must converge to as does.
The same conclusion can be made for using an unpublished result of Austin and Naor announced in [4, Remark 8], which states that does not bi-Lipschitz embed into and, hence, does not bi-Lipschitz embed into .
Acknowledgements
D.B. was supported by the European Union’s Horizon 2020 research and innovation programme grant number 948021. A.L.G.P. was supported by the Engineering and Physical Sciences Research Council grant number EP/R018472/1. We would like to thank Andrea Marchese for useful discussions regarding Almgren’s -valued functions. We would also like to thank the referee for carefully reading this article and providing valuable suggestions that improved the exposition of this work.
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Conflict of interest
On behalf of all authors, the corresponding author states that there are no conflicts of interest.
Footnotes
We adopt the standard convention that Hilbert space is the unique complete and separable infinite dimensional inner product space, up to isometric isomorphism.
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