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. 2024 Mar 19;390(2):3109–3131. doi: 10.1007/s00208-024-02831-x

Bi-Lipschitz embeddings of the space of unordered m-tuples with a partial transportation metric

David Bate 1,, Ana Lucía Garcia Pulido 2
PMCID: PMC11438830  PMID: 39351581

Abstract

Let ΩRn be non-empty, open and proper. This paper is concerned with Wbp(Ω), the space of p-integrable Borel measures on Ω equipped with the partial transportation metric introduced by Figalli and Gigli that allows the creation and destruction of mass on Ω. Alternatively, we show that Wbp(Ω) is isometric to a subset of Borel measures with the ordinary Wasserstein distance, on the one point completion of Ω equipped with the shortcut metric

δ(x,y)=min{x-y,dist(x,Ω)+dist(y,Ω)}.

In this article we construct bi-Lipschitz embeddings of the set of unordered m-tuples in Wbp(Ω) 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 (Xd) by

Wp(μ,ν)=infγX×Xd(x,y)pdγ(x,y)1p, 1

where p1 and the infimum is taken over all measures γ on X×X with coordinate projections π1γ=μ and π2γ=ν. The resulting metric space of p-integrable probability measures equipped with Wp is denoted by Wp(X) (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 Ω be an open non-empty proper subset of X. For measures μ and ν on Ω, one defines Wbp(μ,ν) as in (1), but the infimum is taken over measures γ on Ω¯×Ω¯ with

π1γ|Ω=μandπ2γ|Ω=ν.

The resulting metric space of p-integrable measures, equipped with Wbp, will be denoted by Wbp(X) (see Definition 3.1).

The key property of Wbp is that Ω can be used to destroy or create mass, at a cost of transporting it to or from Ω. 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 Ω is motivated by solving evolution equations with Dirichlet boundary conditions from gradient flows [11, 21]. The metric Wbp 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 Lip(f)·Lip(f-1), where Lip(f) 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 L1) of W1 over various discrete metric spaces [5] such as the planar grid [19] and Hamming cube [15] is known, as is the non-embeddability of Wp(R3) for p1 [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 mN, the set of unordered m-tuples of points in Rn,

Am(Rn)=i=1m[[xi]]:xiRn1im

equipped with W2, bi-Lipschitz embeds into some Euclidean space (see Theorem 2.3). Here and throughout, [[x]] will denote the Dirac mass at x.

In this article we generalise Almgren’s embedding to Wb2(Ω).

Theorem 1.1

For nN, let ΩRn be non-empty, open and proper. The space (Bm(Ω),Wb2) of unordered tuples of at most m points bi-Lipschitz embeds into Hilbert space. The distortion of our embedding is at most cmn+5/2, for some constant c1.

In general, Wbp(Ω) 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 m-points.

To prove Theorem 1.1, we first show, for ΩX, that Wbp(Ω) isometrically embeds into the ordinary p-Wasserstein space of measures on (Ω,δ), where Ω is the one point completion of Ω equipped with the shortcut metric

δ(x,y)=min{x-y,dist(x,Ω)+dist(y,Ω)}

for every x,yΩ (see Lemma 3.3). This embedding maps Bm(Ω) to Am(Ω) and so, in order to prove Theorem 1.1, it remains to construct a bi-Lipschitz embedding of Am(Ω) into Hilbert space.

We do this, for ΩRn, by considering a Whitney decomposition C of Ω into cubes. This decomposition is chosen such that, inside any cube QC, the shortcut metric equals the Euclidean metric and consequently

Am(Q,δ)=Am(Q,). 2

In particular, Almgren’s theorem gives an embedding of each Am(Q) into some Euclidean space. Despite the fact that any measure can be written as a sum of measures supported on cubes in C, the construction of the required bi-Lipschitz embedding of Am(Ω) cannot be obtained simply by restricting to cubes. Indeed, Wp 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 Am(Ω) into the 2-sum of infinitely many copies of Am(Rn+1), 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 2-sum.

We mention an application of Theorem 1.1 to persistence homology. The space of persistence barcodes can be viewed as mBm(U) for

U={(x,y)R2:y>x},

see [10]. Theorem 1.1 shows that the space of persistence barcodes with at most m-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 Bm(U) 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 Bm(Ω) is equipped with any Wp for p1; due to the equivalence of norms on Rm, these metrics are all bi-Lipschitz equivalent.

Finally, we mention that the distortion of any embedding of Bm(Ω) into Hilbert space, for ΩRn, must necessarily converge to as m does, see Remark 5.3.

Wasserstein distance and Almgren’s embedding

Let (Xd) be a complete and separable metric space. We write M(X) for the set of Borel measures on X and P(X) for the set of Borel probability measures on X. The Wasserstein space is defined as follows [2, 3].

Definition 2.1

For μ,νM(X) and p[1,) define

Wp(μ,ν)=infγX×Xd(x,y)pdγ(x,y)1p,

where the infimum is taken over all couplings γM(X×X) with coordinate projections π1γ=μ and π2γ=ν. Note that Wp(μ,ν)< only if μ(X)=ν(X) as otherwise there does not exist a γ as in Definition 2.1.

Let Pp(X) be those μP(X) with

Xd(x,x0)pdμ(x)<

for some (equivalently all) x0X. Then Wp defines a metric on Pp(X). Analogous statements hold for the case p=, where the Lp integral is replaced by an essential supremum. We write Wp(X) for the set Pp(X) equipped with Wp.

Definition 2.2

For mN, define the space of unordered m-tuples

Am(X)=i=1m[[xi]]:xiX1im,

equipped with W2. Note that, on Am(X), W2 equals

W2(p,q)=minσΣmi=1md(pi,qσ(i))2,

where p=i=1m[[pi]] and q=i=1m[[qi]].

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 mN there exists an NN and a bi-Lipschitz embedding ξ:Am(Rn)RN. By inspecting the proof one sees that ξ(0)=0 and, for all p,qAm(Rn),

W2(p,q)cmn+1ξ(p)-ξ(q)W2(p,q)

for a constant c1.

Optimal partial transport and the shortcut metric

The transportation metric Wb introduced by Figalli and Gigli [11] is defined between two Borel measures. Originally defined for open and bounded ΩRn, we state the natural generalisation of Wb to complete and separable metric spaces (Xd) (the proof of the triangle inequality is identical).

Definition 3.1

Let ΩX be proper and non-empty. For μ,νM(Ω) and p[1,) define

Wbp(μ,ν)=infγX×Xd(x,y)pdγ(x,y)1p,

where the infimum is taken over all couplings γM(X×X) with π1γ|Ω=μ and π2γ|Ω=ν. Then Wbp defines a metric on

Mbp(Ω):={μM(Ω):Wbp(μ,0)<}.

Analogous statements hold for the case p=, where the Lp integral is replaced by an essential supremum.

We write Wbp(Ω) for the set Mbp(Ω) equipped with Wbp. We also write Wbp1(Ω) for the set of μMbp(Ω) with μ(Ω)1, equipped with Wbp.

The first step in our proof of Theorem 1.1 is to show an equivalence between Wbp1(Ω) and Wp(Ω), for Ω the shortcut metric space, defined as the one point completion of Ω via its complement.

Definition 3.2

For ΩX non-empty and proper, let Ω=Ω{}. For x,yΩ define

δ(x,y)=min{x-y,dist(x,X\Ω)+dist(y,X\Ω)}

and δ(x,)=dist(x,X\Ω). Then δ defines a metric on Ω.

Profeta and Sturm [21, Remark 1.9] mention that Wb11(Ω) isometrically embeds into W1(Ω), and give an example showing that their embedding is not an isometry for p>1. We show that there exists an isometric embedding of Wbp1(Ω) into 2Wp(Ω) for any p1. Here we write 2Wp(Ω) for the space of measures with total mass equal to 2.

Lemma 3.3

Let X be a separable metric space and ΩX be non-empty and proper. For any p1, the map

Wbp1(Ω)2Wp(Ω)ι(μ)=μ+(2-μ(Ω))[[]],

is an isometric embedding.

Proof

Given a coupling for μ,ν we use it to construct a coupling for ι(μ),ι(ν) and vice versa.

First let μ,νWbp1(Ω) and suppose that γM(X×X) is a coupling for μ and ν in Wbp(Ω). Let π(x)= for all xX and define γM(Ω×Ω) as

γ=γ|Ω×Ω+(π×id)#γ|X\Ω×Ω+(id×π)#γ|Ω×X\Ω+(2-[γ(Ω×Ω)+γ(X\Ω×Ω)+γ(Ω×X\Ω)])[[(,)]].

For notational convenience, we let κ denote the coefficient of [[(,)]] in this expression. Then

π1γ=π1(γ|Ω×Ω)+γ(X\Ω×Ω)[[]]+π1(γ|Ω×X\Ω)+κ[[]]=π1(γ|Ω×Ω)+π1(γ|Ω×X\Ω)+(2-[γ(Ω×Ω)+γ(Ω×X\Ω)])[[]]=π1(γ|Ω×X)+(2-γ(Ω×X))[[]]=μ+(2-μ(X))[[]]=ι(μ).

Similarly, by symmetry, π2γ=ι(ν). Thus γ is a coupling of ι(μ) and ι(ν) in Wp(Ω). Moreover,

δ(x,y)pdγ(x,y)=Ω×Ωδ(x,y)pdγ(x,y)+X\Ω×Ωδ(,y)pdγ(x,y)+Ω×X\Ωδ(x,)pdγ(x,y)+κδ(,)pΩ×Ωd(x,y)pdγ(x,y)+X\Ω×Ωd(x,y)pdγ(x,y)+Ω×X\Ωd(x,y)pdγ(x,y)=d(x,y)pdγ(x,y). 3

Therefore,

Wp(ι(μ),ι(ν))Wbp(μ,ν).

Conversely, let γ be a coupling for ι(μ) and ι(ν) in Wp(Ω). Define the closed set

E={(x,y)Ω×Ω:δ(x,y)=d(x,y)}.

Fix ϵ>0 and for each xΩ, let c(x)X\Ω with

d(x,c(x))(1+ϵ)dist(x,X\Ω).

Since X is separable, c may be chosen to be a Borel function with countable image. Let c1=(id×c)π1 and c2=(c×id)π2 and define

γ=γ|E+(c1)#γ|(Ω×Ω)\E+(c2)#γ|(Ω×Ω)\EM(X×X). 4

Note that, since π1((c1)#γ) is supported on X\Ω, its restriction to Ω equals 0. Therefore,

(π1γ)|Ω=(π1γ|E)|Ω+(π1γ|(Ω×Ω)\E)|Ω+0=(π1γ)|Ω=μ.

Similarly, by symmetry, (π2γ)|Ω=ν. Hence γ is a coupling for μ and ν in Wbp(Ω).

Now, for any (x,y)(Ω×Ω)\E,

d(x,c(x))p+d(c(y),y)p(1+ϵ)p(δ(x,)p+δ(,y)p)(1+ϵ)pδ(x,y)p.

Therefore,

X×Xd(x,y)pdγ(x,y)=Ed(x,y)pdγ(x,y)+(Ω×Ω)\Ed(x,c(x))pdγ(x,y)+(Ω×Ω)\Ed(c(y),y)pdγ(x,y)Ed(x,y)pdγ(x,y)+(Ω×Ω)\E(1+ϵ)pδ(x,y)pdγ(x,y)(1+ϵ)pΩ×Ωδ(x,y)pdγ(x,y). 5

Since ϵ>0 is arbitrary, this shows that

Wp(ι(μ),ι(ν))Wbp(μ,ν).

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 Ω=U 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 Ω, whilst the one in [10] does. However, a flaw in their argument makes the proof incorrect even for the case of Ω=U.

Central to their proof is the definition of a measure π~ and the claim that it is a coupling of μ~ and ν~ in Wp(Ω) (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 δ=d in Ω. These contradictions originate in the fact that π~ is not a coupling of μ~ and ν~, which can be verified by comparing the total measure of π~ to that of μ~,ν~ or π~.

Since the map

2Wp(Ω)Wp(Ω)μμ/2

has distortion 21/p, we obtain the following corollary.

Corollary 3.5

Let X be a separable metric space and ΩX be non-empty and proper. Then Wbp1(Ω) bi-Lipschitz embeds into Wp(Ω) with distortion 2.

The same proof as the one for Lemma 3.3 shows that the full space Wbp(Ω) isometrically embeds into M(Ω).

Lemma 3.6

Let X be a separable metric space and ΩX non-empty and proper. For any p1,

Wbp(Ω)(M(Ω),Wp)ι(μ)=μ+·[[]]

is an isometric embedding.

Remark 3.7

For any μMbp(Ω),

Wp(ι(μ),·[[]])=Wbp(μ,0)<.

Therefore, the triangle inequality for Wp implies that Wp is indeed a metric on the image of ι.

Proof

(Proof of Lemma 3.6) If μ,νMbp(Ω) then

γ=γ|Ω×Ω+(π×id)#γ|X\Ω×Ω+(id×π)#γ|Ω×X\Ω+·[[(,)]]

defines a coupling of ι(μ) and ι(ν). The calculation in (3) shows that

Wp(ι(μ),ι(ν))Wbp(μ,ν).

Conversely, if μ,νMbp(Ω), then γ as defined in (4) is a coupling for μ,ν and (5) shows that

Wp(ι(μ),ι(ν))Wbp(μ,ν).

The shortcut metric space is not doubling

A metric space X is doubling if there exists NN such that each ball BX is covered by N balls of half the radius of B.

Lemma 3.8

For n2, let ΩRn be non-empty and open such that Ω¯ is a proper subset of Rn. Then for any NN and any sufficiently small ϵ>0, there exist y1,,yNΩ with δ(yi,yj)=ϵ for each ij. In particular, Ω is not doubling.

Proof

Let xΩ¯ and yΩ. For NN, let y1,,yNΩ lie on the circle centred on x of radius x-y (such points exist since Ω is open). For each 1iN, let li be the line segment connecting yi to x and let li be the connected component of liΩ containing yi. Since xΩ¯, there exists η>0 such that

inf{z-z:zli,zlj,ij}>η.

Now, dist(·,Ω) is continuous on each li and converges to 0 as one travels along li towards Ω. Therefore, for each sufficiently small ϵ>0 and each 1iN, there exists zili with dist(zi,Ω)=ϵ/2. In particular, if ϵ<η, then δ(zi,zj)=ϵ for each 1ijN.

Finally, we see that yiB(y1,ϵ) for each 1jN, but we require at least N balls of radius ϵ/4 to cover B(y1,ϵ). Since NN is arbitrary, Ω cannot be doubling.

Remark 3.9

Lemma 3.8 is sharp in the following sense. If Ω=(-1,1)R, then Ω is bi-Lipschitz equivalent to a Euclidean circle. For any nN, if Ω=Rn\{0}, then Ω is isometric to Rn. 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 n2 let ΩRn be non-empty and open such that Ω¯ is a proper subset of Rn. Then Ω is not bi-Lipschitz embeddable into any Euclidean space.

The space of unordered tuples of at most m points

Definition 3.11

Let X be a metric space, ΩX non-empty and proper and mN. Define the space of unordered tuples of at most m points as

Bm(Ω)=k=1mAk(Ω),

with the metric inherited from Wb2(Ω).

This space is naturally identified with a subset of Am(Ω).

Corollary 3.12

Let mN. For any separable metric space X and non-empty and proper ΩX, Bm(Ω) isometrically embeds into Am(Ω) via the map

i=1k[[xi]]i=1k[[xi]]+(2m-k)[[]].

Proof

Embed Bm(X) into Wbp1(X) by μμ/m, apply Lemma 3.3, and then embed into Am(Ω) by μmμ.

A bi-Lipschitz description of Am(Ω) in terms of Am(Rn+1)

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 Rn (in particular the existence of projections), and the compactness of the unit ball. Although ΩRn as a set, δ bears no relationship to the linear structure of Rn 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 Ω into 2 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 C of Ω into cubes

Ω=QCQ

(see Proposition 4.2) such that, within each Q, δ is given by ·. Consequently, Am(Q,δ)=Am(Q,·). Theorem 2.3 then gives a bi-Lipschitz embedding of each Am(Q,δ) into RN 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 Am(Q) does not cover Am(Ω) and therefore we cannot simply define coordinate projections by taking restrictions to each Q. Nevertheless, the fact that Am(Q,δ)=Am(Q,·) enables us to construct a map ϕQ:Am(Ω)Am(Rn+1) which, roughly speaking, acts as a smooth projection to Am(Q).

The main result of this section shows that the ϕQ can be combined to define a bi-Lipschitz embedding of Am(Ω) into the following metric space.

Definition 4.1

Let C be a countable set and define

T:=QCAm(Rn+1)

to be the 2-sum of copies of Am(Rn+1). That is, T consists of sequences

QCaQ

of elements of Am(Rn+1) for which

QCW22(aQ,0)<,

where 0=i=1m[[0]], equipped with the metric

QCW22(aQ,aQ).

Once we have an embedding into T, we will show that it is possible to find an embedding into 2. Indeed, in Sect. 5, we apply Theorem 2.3 to each term in the definition of T to obtain a bi-Lipschitz embedding of T into 2.

A Whitney decomposition of Ω

To construct the embedding into T, we will use a Whitney decomposition of Ω. For a cube QRn, let l(Q) denote the side length of Q.

Proposition 4.2

(Appendix J [12]) Let ΩRn be non-empty, open and proper. There exists a family of closed cubes C such that

  1. C=Ω and the elements of C have disjoint interiors.

  2. nl(Q)dist(Q,Ω)4nl(Q) for all QC.

  3. If Q,QC and QQ then
    14l(Q)l(Q)4.
    We say that Q,Q are neighbours.
  4. Each QC has at most 12n neighbours.

A Whitney decomposition of Ω estimates which quantity attains the minimum in the definition of δ.

Lemma 4.3

Let C be a Whitney decomposition of ΩRn, Q,QC and xQ and yQ. Then

nl(Q)dist(x,Ω)5nl(Q). 6

If Q,Q are neighbours then

δ(x,y)=x-y. 7

If Q,Q are not neighbours then

l(Q)+l(Q)8δ(x,y)5n(l(Q)+l(Q)). 8

Proof

The first inequality in (6) is implied by nl(Q)dist(Q,Ω). The second follows from the triangle inequality:

dist(x,Ω)dist(Q,Ω)+diam(Q)4nl(Q)+nl(Q).

Now suppose Q,Q are neighbours and let zQQ. Then by (6),

dist(x,Ω)+dist(y,Ω)n(l(Q)+l(Q))x-z+z-yx-y,

giving (7). On the other hand, suppose that Q,Q are not neighbours and l(Q)l(Q). Then x-yl(Q) for Q a neighbour of Q. In particular

x-yl(Q)l(Q)4l(Q)+l(Q)8,

giving the first inequality in (8). The second inequality follows from (6).

For the remainder of the paper we fix mN, ΩRn non-empty, open and proper and C a Whitney decomposition of Ω as in Proposition 4.2. We also fix T as in Definition 4.1.

Constructing a coordinate system

To construct a bi-Lipschitz embedding of Am(Ω) into T, we define projections

ϕQ:Am(Ω)Am(Rn+1)

that serve as a coordinate system for Am(Ω). The embedding into T will then be defined as the 2-sum of the ϕQ (see Definition 4.6).

We begin with the construction of a function ϕQ that approximates the identity within a given QC, is supported on the neighbours of Q, and maintains bi-Lipschitz bounds with δ. For QC and r>0, we write B(Q,r) for the closed r-neighbourhood of Q.

Lemma 4.4

For each QC there exists a map

ϕQ:ΩRn+1

such that

  1. ϕQ is 9n+1-Lipschitz;

  2. ϕQ(x)=0 for all xB(Q,l(Q)/4). In particular, ϕQ is supported on the neighbours of Q;

  3. ϕQn+1l(Q);

  4. For all x,yB(Q,l(Q)/8),
    ϕQ(x)-ϕQ(y)=x-y;
  5. The extension of ϕQ to Ω, defined by ϕQ()=0, is 9n+1-Lipschitz with respect to δ;

  6. If xB(Q,l(Q)/8) and yΩ, then
    ϕQ(x)-ϕQ(y)minx-y2n,l(Q).

Proof

Fix QC and let c be the centre of Q. For each xΩ, let

η(x)=max1-distx,BQ,l(Q)88l(Q),0.

That is, η is an 8/l(Q)-Lipschitz function with η=1 that equals 1 on B(Q,l(Q)/8) and 0 on Ω\B(Q,l(Q)/4). We also set

φ(x)=(x-c,l(Q))Rn+1,

a 1-Lipschitz function satisfying φ(x)n+1l(Q) for all x in the support of η.

Define ϕQ=ηφ. Since ϕQ is a product of Lipschitz functions, the Lipschitz constant of ϕQ is bounded above by

Lipφη+sup{φ(x):xsptη}Lipη1+n+1l(Q)8l(Q)9n+1.

This demonstrates item 1. Items 2 to 4 are immediate.

To see item 5, first let xΩ be such that ϕQ(x)0. Then by item 2, xQ for Q a neighbour of Q, so that l(Q)l(Q)/4. Therefore, by item 3,

ϕQ(x)n+1l(Q)4n+1l(Q)8dist(x,Ω),

using Eq. (6) for the final inequality. Thus

ϕQ(x)8dist(x,Ω)

holds for any xΩ (including x=). Therefore, by the triangle inequality, for any x,yΩ,

ϕQ(x)-ϕQ(y)8dist(x,Ω)+dist(y,Ω).

Combining this inequality with item 1 shows that ϕQ is 9n+1-Lipschitz with respect to δ on Ω.

Finally, to see item 6, first suppose that yB(Q,l(Q)/4). Then by item 2,

ϕQ(x)-ϕQ(y)=φ(x)l(Q),

so that item 6 holds in this case.

In the case yB(Q,l(Q)/4) we will show that

ϕQ(x)-ϕQ(y)x-y2n, 9

completing the proof of item 6. To this end, note that

y-cnl(Q)2+l(Q)4nl(Q).

Therefore, by considering the first component of ϕQ, we see that

ϕQ(x)-ϕQ(y)(x-c)-η(y)(y-c)x-y-(1-η(y))y-cx-y-n(1-η(y))l(Q).

Thus, if

n(1-η(y))l(Q)x-y2, 10

then (9) holds. On the other hand, if (10) does not hold, then by considering the final component of ϕ, we have

ϕQ(x)-ϕQ(y)(1-η(y))l(Q)x-y2n,

giving (9).

The pushforwards under each ϕQ define our coordinate projections on Am(Ω).

Definition 4.5

For every QC, define ϕQ to be the pushforward under ϕQ. That is,

ϕQ:Am(Ω)Am(Rn+1)i=1m[[pi]]i=1m[[ϕQ(pi)]].

Recall the construction of T from Definition 4.1.

Definition 4.6

Define the embedding ϕ by

Am(Ω)Tϕ=QCϕQ

This is well defined since each ϕQ is supported on the neighbours of Q, so that each xΩ is contained in the support of at most 12n of the ϕQ.

ϕ is bi-Lipschitz

In this section we show that ϕ is a bi-Lipschitz embedding, beginning by showing that it is Lipschitz.

For p(Ω)m and SΩ, let

p-1(S)={1km:pkS}.

From now on we use the notation σq to denote the element of (Rn)m arising from the natural action of the symmetric group Σm on (Rn)m: (σq)i=qσ(i) for each 1im.

Lemma 4.7

For any p,qAm(Ω),

QCW2(ϕQ(p),ϕQ(q))2c0W22(p,q),

where c01 depends only upon n.

Proof

Fix p,q(Ω)m and let QC and σΣm. Set

JQσ=p-1(B(Q,l(Q)/4))(σq)-1(B(Q,l(Q)/4)),

so that, by Lemma 4.4 item 2,

k=1mϕQ(pk)-ϕQ(qσ(k))2=kJQσϕQ(pk)-ϕQ(qσ(k))2.

Applying Lemma 4.4 item 5 gives

k=1mϕQ(pk)-ϕQ(qσ(k))292(n+1)kJQσδ(pk,qσ(k))2.

Therefore

QCminσΣmk=1mϕQ(pk)-ϕQ(qσ(k))292(n+1)QCminσΣmkJQσδ(pk,qσ(k))2.

Further,

QCminσΣmkJQσδ(pk,qσ(k))2minσΣmQCkJQσδ(pk,qσ(k))2minσΣm2·12nk=1mδ(pk,qσ(k))2,

since B(Q,l(Q)/4) is contained within the union of the neighbours of Q. The result follows for c0=2·92·12n(n+1).

To prove the lower Lipschitz bound, we fix the following notation until the end of the section.

Notation 4.8

Fix p,q(Ω)m and, for every QC, let σQΣm be such that

k=1mϕQ(pk)-ϕQ(qσQ(k))2=W2(ϕQ(p),ϕQ(q))2. 11

Let QC. For integer 0r2m, the annuli

Qr=BQ,r+13ml(Q)8\BQ,r3ml(Q)8

are disjoint and so there exists 0r2m such that

p-1(Qr)(σQq)-1(Qr)=. 12

Set

Q^=BQ,r3ml(Q)8.

Note that Q^ is contained within the union of the neighbours of Q.

Let c1=(48n)-1 and define C to be the set of QC for which

W2(ϕQ(p),ϕQ(q))<c1l(Q)m. 13

Set

E=QCQ^.

To obtain a lower bound of

QCW2(ϕQ(p),ϕQ(q))2 14

in terms of W22(p,q), we will construct a τΣm for which i=1mδ(pi,qτ(i))2 is comparable to (14). A first attempt to do this may be, for each QC and each ip-1(Q), to define τ(i)=σQ(i). Of course, a τ defined in this way need not be injective, for example if there exist QQC and ij such that qσQ(i)=qσQ(j). Nonetheless, we will show that it is possible to construct a permutation for the cubes in C. Indeed, we now show that conditions (12) and (13) ensure that, for each QC, piQ^ if and only if qσQ(i)Q^: (12) provides a moat surrounding Q^ and (13) ensures that the distance between pi and qσQ(i) is less than the width of the moat.

Lemma 4.9

For any QC,

p-1(Q^)=(σQq)-1(Q^) 15

and

pk-qσQ(k)=ϕQ(pk)-ϕQ(qσQ(k))kp-1(Q^). 16

Moreover, if RC with l(R)l(Q),

p-1(Q^R^)=(σRq)-1(Q^R^) 17

Proof

For any kp-1(Q^), (13) and Lemma 4.4 item 6 imply

minpk-qσQ(k)2n,l(Q)<c1l(Q)m.

In particular,

pk-qσQ(k)<l(Q)24m. 18

Therefore (12) implies that qσQ(k)Q^. By symmetry, if k(σQq)-1(Q^) then kp-1(Q^) and so (15) holds. Since Q^B(Q,l(Q)/8), Lemma 4.4 item 4 implies (16).

Now let RC with l(R)l(Q) and kp-1(Q^R^). Then (18) for R implies

pk-qσR(k)<l(R)24ml(Q)24m

and so (12) implies qσR(k)Q^. The similar argument with p and σRq exchanged gives (17).

By carefully partitioning E using the Q^, we use Lemma 4.9 to construct the desired permutation on p-1(E).

Proposition 4.10

There exists a bijection τ:p-1(E)q-1(E) such that

kp-1(E)pk-qτ(k)2QCW2(ϕQ(p),ϕQ(q))2.

Proof

Let

C={QC:p-1(Q^)}.

Note that, by (15), C can equivalently be defined as the set of QC with q-1(Q^). Since C is finite, we enumerate it as

C={Q1,Q2,,Qj}

in such a way that

l(Q1)l(Q2)l(Qj).

Then, for 1ikj, applying Lemma 4.9 with Q=Qk and R=Qi gives

p-1Q^iQ^k=(σQkq)-1Q^iQ^k1ikj. 19

Let B1=Q^1 and for each 2kj define

Bk:=Q^k\i=1k-1Q^i=Q^k\i=1k-1Q^iQ^k.

Then (19) implies that σQk is a permutation between p-1(Bk) and σQkq-1(Bk) for each 1kj. Therefore, we define a bijection

τ:p-1(E)q-1(E)

by setting τ to equal σQk on Dk:=p-1(Bk) for each 1kj. Then

kp-1(E)pk-qτ(k)2=i=1jkDipk-qτ(k)2=i=1jkDipk-qσQi(k)2=i=1jkDiϕQi(pk)-ϕQi(qσQi(k))2QCk=1mϕQ(pk)-ϕQ(qσQ(k))2,

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 Ω to estimate δ.

Lemma 4.11

For any bijection

σ:p-1(Ω\E)q-1(Ω\E)

we have

kp-1(Ω\E)(dist(pk,Ω)+dist(qσ(k),Ω))2m3c2QC\CW2(ϕQ(p),ϕQ(q))2,

for c21 that depends only upon n.

Proof

For a moment fix kp-1(Ω\E) and let QC contain pk. Then necessarily QC. Therefore (13) and (6) imply

W2(ϕQ(p),ϕQ(q))c1ml(Q)c15nmdist(pk,Ω).

Since each QC contains at most m such points pk,

kp-1(Ω\E)dist(pk,Ω)225m2nc12mQC\CW2(ϕQ(p),ϕQ(q))2.

The same estimate for σq gives the desired inequality for c2=4·25n/c12.

We combine our previous results to show that ϕQ is a bi-Lipschitz embedding.

Theorem 4.12

For any p,qAm(Ω),

W2(p,q)2c3m3QCW2(ϕQ(p),ϕQ(q))2c3W2(p,q)2,

where c31 depends only upon n.

Proof

The right hand inequality is given by Lemma 4.7.

For the left hand inequality, let τ be the bijection obtained from Proposition 4.10 and arbitrarily extend it to a bijection of {1,,m}. Then

QCW2(ϕQ(p),ϕQ(q))2=QCk=1mϕQ(pk)-ϕQ(qσQ(k))2+QCk=1mϕQ(pk)-ϕQ(qσQ(k))2kp-1(E)pk-qτ(k)2+1c2m3kp-1(Ω\E)(dist(pk,Ω)+dist(qτ(k),Ω))21c2m3k=1mδ(pk,qτ(k))21c2m3W2(p,q)2,

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 ξ:Am(Rn+1)RN be the embedding given by Theorem 2.3. We write

2=QCRN

as a direct l2-sum over C. Recall the construction of T from Definition 4.1.

Lemma 5.1

The function ξ:T2 defined by

QCAm(Rn+1)QCRNξ=QCξ

is well defined. Moreover, for any a,bT,

1cm2n+2QCW2(aQ,bQ)2ξ(a)-ξ(b)2QCW2(aQ,bQ)2,

for c1 depending only upon n.

Proof

Let aT, so that

QCW2(pQ,0)2<.

Since ξ is 1-Lipschitz this implies that

QCξ(pQ)2=QCξ(pQ)-ξ(0)2QCW2(pQ,0)2<.

Hence, ξ is well defined. Moreover, using that ξ is 1-Lipschitz again, we have, for any bT,

QCξ(aQ)-ξ(bQ)2QCW2(aQ,bQ)2,

so that ξ is also 1-Lipschitz. Finally, Theorem 2.3 gives

QCξ(aQ)-ξ(bQ)21cm2n+2QCW2(aQ,bQ)2.

Theorem 5.2

There exists a bi-Lipschitz embedding ζ:Bm(Ω)2 with distortion at most cmn+5/2, for c1 depending only upon n. That is, for any p,qBm(Ω),

W2(p,q)cmn+5/2ζ(p)-ζ(q)cW2(p,q).

Proof

First isometrically embed Bm(Ω) into Am(Ω) via Corollary 3.12. One then applies Theorem 4.12 to bi-Lipschitz embed Am(Ω) into T. Finally, Lemma 5.1 bi-Lipschitz embeds T into 2, as required.

Remark 5.3

For n3, the distortion of any embedding of Am(Ω) into 2 converges to as m increases. In particular, Wb2(Ω) does not bi-Lipschitz embed into 2.

Indeed, by Eq. (7) we see that Am(Ω) contains an isometric copy of Am(Q) for some cube Q. Thus, the distortion of any embedding into 2 is at least that of Am(Q). For n3, Andoni, Naor and Nieman [4, Theorem 7] prove that W2(Rn) 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 W2(Rn), a scaling argument shows that the distortion of any bi-Lipschitz embedding of Am(Q) must converge to as m does.

The same conclusion can be made for n=2 using an unpublished result of Austin and Naor announced in [4, Remark 8], which states that W2(R2) does not bi-Lipschitz embed into L1 and, hence, does not bi-Lipschitz embed into 2.

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 m-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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Declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there are no conflicts of interest.

Footnotes

1

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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