The parabolic Anderson model on Riemann surfaces
Antoine Dahlqvist, Joscha Diehl, Bruce Driver

TL;DR
This paper establishes well-posedness for the parabolic Anderson model on 2D Riemann surfaces by extending regularity structures to curved spaces and constructing the necessary polynomial models.
Contribution
It introduces a novel extension of regularity structures to curved Riemannian manifolds, enabling analysis of the parabolic Anderson model in this setting.
Findings
Proved well-posedness of the model on Riemann surfaces.
Extended regularity structures to curved geometries.
Constructed polynomial models up to any order.
Abstract
We show well-posedness for the parabolic Anderson model on -dimensional closed Riemannian manifolds. To this end we extend the notion of regularity structures to curved space, and explicitly construct the minimal structure required for this equation. A central ingredient is the appropriate re-interpretation of the polynomial model, which we build up to any order.
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Taxonomy
TopicsAdvanced Mathematical Modeling in Engineering · Geometric Analysis and Curvature Flows · Nonlinear Partial Differential Equations
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The parabolic Anderson model on Riemann surfaces
Antoine Dahlqvist University of Cambridge; the author is responsible for the first part of the Appendix
Joscha Diehl Max-Planck Institute Leipzig
Bruce Driver University of California San Diego; the author is responsible for the second part of the Appendix
Abstract
We show well-posedness for the parabolic Anderson model on -dimensional closed Riemannian manifolds. To this end we extend the notion of regularity structures to curved space, and explicitly construct the minimal structure required for this equation. A central ingredient is the appropriate re-interpretation of the polynomial model, which we build up to any order.
1 Introduction
The last few years have seen an explosion of literature on singular stochastic partial differential equations (singular SPDEs). The simplest instance of such an equation is the parabolic Anderson model in two dimensions, formally written as
[TABLE]
Here is looked for, where is some dimensional domain, and is (time-independent) white noise on the domain . This equation is formally ill-posed (or “singular”), since is not expected to be regular enough for the product to be well-defined analytically. The standard tool of stochastic calculus, the Itō integral, is also of no use here, since the white-noise is constant in time.
With the breakthrough results of Hairer [Hai14] and Gubinelli, Imkeller and Perkowski [GIP15] a large class of such equations has become amenable to analysis. Let us sketch the approach of [Hai14], since this is the one we shall use in this work.
- •
assume that “looks like“ the solution to the additive-noise equation
[TABLE]
which is classically well-defined via convolution with the heat semigroup
- •
under this assumption, if we somehow define , then the framework defines automatically
- •
close the fixpoint argument, i.e.
”looks like“ 2. 2.
3. 3.
then ”looks like“
It then only remains to define the missing ingredient ”“. This can be done probabilistically and is actually the only place in this theory that is not deterministic. Using this procedure, it is shown in [Hai14] that (PAM) possesses a unique solution for , the two dimensional torus.
In this work we show that the theory can be adapted to work for , a -dimensional closed Riemannian manifold. The theory of regularity structures is intrinsically a local theory (as opposed to the theory of paracontrolled distributions, which, at least at first sight is global in spirit). It is hence natural to expect that it can be applied to general geometries. It turns out that the implementation of this heuristic is not straightforward.
At least two hurdles need indeed to be bypassed. On the one hand, at the core of Euclidean regularity structures stands the space of polynomials, encoding classical Taylor expansions at any point. The operation of re-expansion from a point to another leads to a morphism from to a space of unipotent matrices. On a manifold, one would need to look for such a space, encoding Taylor expansion and enjoying a similar structure. On the other hand, as usual for fixpoint arguments of (S)PDEs, one needs to estimate the improvement of the heat kernel in adequate spaces, which is a global operation (Schauder estimates).
To solve the first issue, we show that the space of polynomials on the tangent space of the manifolds is a suitable candidate for a canonical regularity structure, that allows to encode Hölder functions. This choice enforces a modified definition of a regularity structure. In particular one has to abandon the idea of one fixed vector space and work with vector bundles instead. For our definition of a model, there is no unipotent structure anymore and re-expansions are only approximately compatible. Within this new framework, when considering the parabolic Anderson model on a surface, we give a weak version of a Schauder estimate with elementary tools and heat kernel estimates.
This exposition does not demand any previous knowledge of regularity structures on the Reader. In this sense it is self-contained, apart from a reference to the reconstruction theorem of Hairer in our Theorem 20 and in the construction of the Gaussian model in Section 8. Its proof using wavelet analysis is of no use reproducing here. We believe that the validity of that reconstruction theorem, which we use in coordinates, is easily believed.
We follow a very hands-on approach. Instead of trying to set up a general theory of regularity structures on manifolds, we work with the smallest structure that is necessary to solve PAM. We show the Schauder estimates explicitly. Apart from introducing for the first time regularity structures on manifolds, we believe our work also has a pedagogical value. Since everyting is laid out explicitly and covers the flat case , it can serve as a gentle introduction to the general theory.
In future work we will investigate the algebraic foundation necessary for studying general equations, without having to build the regularity structure “by hand”. For general equations a new proof of the Schauder estimates has also to be found.
During the writing of the present article, a different approached has been put forward in [IB2016a], where the notion of paracontrolled products using semi-groups is developed on general metric spaces. The advantage of the paracontrolled approach is that it requires less machinery. On the downside, the class of equations that can be covered is currently strictly smaller than in the setting of regularity structures. Let us point to [IB2016b] though, which pushes the framework to more general equations.
The outline of this paper is as follows. After presenting notational conventions, we give in Section 2 the notion of distributions on manifold we shall use in this work. Moreover we introduce Hölder spaces on manifolds. In Section 3 we introduce the notion of regularity structure, model and modelled distribution on a manifold. We show how these objects behave nicely under diffeomorphisms and use this fact to show the reconstruction theorem. In Section 4 we give the simplest non-trivial example of a regularity structure on a manifold; the regularity structure for “linear polynomials”. This forms the basis for the regularity structure for PAM, which is constructed in Section 5. As input it takes the product alluded to before. This is constructed in Section 8 via renormalization. Section 6 gives the Schauder estimate for modelled distributions in the setting of PAM and finally Section 7 solves the corresponding fixpoint equation. In Section 9 we show how the construction of Section 4 can be extended to “polynomials” of arbitrary order.
1.1 Notation
In all what follows will be a -dimensional closed Riemannian manifold. When we specialize to the parabolic Anderson model (PAM), the dimension will be . Denote by the radius of injectivity of .
For a function supported in we define for the “scaled test function”
[TABLE]
extended to all of by setting it to zero outside of .
For , a graded normed vector bundle with grading we denote by the size of component in the -th level, .
The differential of a smooth enough function at a point will be denoted . Similar for higher order derivatives (see Section 9) . For the action on vectors we shall write either or .
For denote
[TABLE]
where . Here will be depend the situation, and will always be large enough so that the distributions under consideration can act on .
We shall use for points in and to denote points in . For , we write
[TABLE]
which is consistent with the notation introduced above when considering as Riemannian manifold with the standard metric.
For we denote by the smallest integer strictly larger than .
For a pairing of a distribution with a test function we write .
For two quantities we write if there exists a constant such that . To make explicit the dependence of on a quantity , we sometimes write .
2 Hölder spaces
Definition 1**.**
A distribution on is a bounded, linear functional on (, if is compact).
Given a density on , defines a distribution. Distributions are hence “generalized densities“. Compare [Fri75, Section 2.8] and [Wal12, Section 1.3].
There is another definition of distibutions as “generalized functions”, see [Hor13, Section 1.8]. They are equivalent when there is a canonical way to turn a function into a density and vice versa. This is the case when there is a reference density, like on a Riemannian manifold.
Remark 2**.**
On a Riemannian manifold , denote the standard density by . We can lift a function to a density . Then, for , defined as
[TABLE]
is a distribution.
Definition 3** (Push-forward).**
Let be a coordinate chart on . If and is a distribution on we can define the push-forward via
[TABLE]
Remark 4**.**
This push-forward is compatible with the pull-back of densities. Indeed, for we get the distribution , by Remark 2. This density pulls back under as (compare [Lee03, Proposition 16.38])
[TABLE]
where are standard coordinates on , and is the Riemannian metric in the coordinates . Hence
[TABLE]
where the last line is the pairing of a distribution with a test function on and is the canonical identification of a locally integrable density on with a distribution.
Recall the following definition of Hölder spaces in Euclidean space.
Definition 5**.**
For denote by the space of distributions with
[TABLE]
here , is defined in (4) and the set of test functions is defined in (3).
For we keep the classical definition, i.e.
[TABLE]
where , , .
Remark 6**.**
For the norm is independent of the arbitrary upper bound for the supremum over as well as the support of . For every
[TABLE]
where .
Remark 7**.**
Every time that a condition like
[TABLE]
appears, uniformly over with one can equivalently demand
[TABLE]
uniformly over , with , for .
We need a reformulation similar to this remark, but for Schwartz test functions.
Lemma 8**.**
Let and . Then (and not just ). Define for ,
[TABLE]
Then, for ,
[TABLE]
Remark 9**.**
Note that if , then satisfies for , , ,
[TABLE]
Proof.
Let , , be a partition of unity of such that and .
Define
[TABLE]
Then . Write for short . We have and
[TABLE]
Then
[TABLE]
as desired. We used the fact that is upper bounded by , which is finite, since and independent of . ∎
Definition 10**.**
Let be a closed Riemannian manifold. Let a finite partition of unity be given on , subordinate to a finite atlas . For define
[TABLE]
and
[TABLE]
For an equivalent characterization of will be shown in Theorem 90. We now give one in the case .
Lemma 11**.**
For , a closed Riemannian manifold, an equivalent norm on is given by
[TABLE]
where we recall that is defined in (2).
Proof.
Fix an atlas with subordinate partition of unity . Denote
[TABLE]
(): Let , . Then
[TABLE]
Here is such that and . Now
[TABLE]
Indeed, this follows from
[TABLE]
for some constant , for all , and . Moreover
[TABLE]
for all . Hence
[TABLE]
The result then follows from Remark 7.
(): We have to show
[TABLE]
for all , . Now for
[TABLE]
where the last equality holds if , with .
Claim: there exists such that for all , , either or . Indeed, since is finite and for all , is compactly supported in there exists such that if and if then . Away from the boundary, the differential of is bounded, and then for one has . This proves the claim.
Now one checks that falls under Remark 7, and applies Remark 6. ∎
As immediate consequence we get the following statement.
Corollary 12**.**
Let be another finite atlas with subordinate partition of unity . Then for
[TABLE]
with equivalent norms.
3 Regularity structures on manifolds
Let be a -dimensional Riemannian manifold without boundary. The two cases we are most interested in are
- •
is compact without boundary (i.e. closed)
- •
is an open bounded subset of with induced Euclidean metric
We now give our definition of a regularity structure and a model on a manifold . For concrete incarnations of these abstract definitions we refer the reader to Section 4 for the implementation of a first order “polynomial” structure; to Section 9 for a structure implementing “polynomials” of any order and right before Lemma 33 for the structure used for the parabolic Anderson model.
Definition 13** (Regularity structure).**
A regularity structure is a graded vector bundle on , with a finite grading . For , denotes the vector bundle of homogeneity . It is assumed to be finite dimensional. We denote the fiber at by and the fiber of homogeneity at by . For , we write for the projection of onto .
Definition 14** (Model).**
Let a collection of open sets , , with , and maps
[TABLE]
be given. We assume there is for every compactum a constant such that is defined for and for , is a diffeomorphism and .
Given , we say that is a model with transport precision if the following entity is finite for every compactum
[TABLE]
where we recall that the set of test functions was defined in (3).
Remark 15**.**
Note that the conditions on a model do not pin down the global regularity of . Without loss of generality we will assume that for all and .
Our definition of a regularity structure and a corresponding model are slightly more general than the original formulation by Hairer [Hai14]. This extension is necessary to accomodate the “polynomial regularity structure”, which will be constructed up to first order in Section 4 and up to any order in Section 9. Let us point out the key differences.
- •
Derivatives of functions on a general manifold can only be stored in a fibered space. Hence the regularity structure has to be a vector bundle and not a fixed vector space.
- •
For this reason there cannot be a fixed structure group in which the transport maps take value.
- •
The transport maps can also act “upwards”, see Remark 81.
- •
The distributions as well as the transports only make sense locally.
It turns out that the theory can handle these slight extensions. In particular the reconstruction theorem still holds, Theorem 22. Finally, we remark that our regularity structure does not include time and that the parabolic Anderson model will be treated by considering functions in time, valued in modelled distributions (Definition 17) on a manifold.
As in Lemma 8 we know how acts on a more general class of functions:
Lemma 16**.**
For a regularity structure let be given a model of transport precision with . Let , a compactum in . Let satisfy the assumptions of Lemma 8 with the additional condition . Assume moreover that (which can always be achieved by making smaller.) Then for
[TABLE]
where is defined in Lemma 8.
Proof.
Let , , be a partition of unity of such that and . Let . Define
[TABLE]
so that
[TABLE]
Then . Hence for . Moreover
[TABLE]
Then
[TABLE]
Note that in the sum . Hence, by assumption . Hence by definition of a model, for . Then for those
[TABLE]
Moreover
[TABLE]
Combining,
[TABLE]
∎
Definition 17**.**
Let be a regularity structure and a model of precision . Define for the space of modelled distributions
[TABLE]
with
[TABLE]
Here is the distance of points in for which makes sense, see Definition 14. Note that the precision of transport plays no role here.
Remark 18**.**
As usual for Hölder norms, for every compactum an equivalent norm is obtained by replacing in the supremum, for any , the condition with the condition .
Lemma 19** (Push-forward).**
Let be Riemannian manifolds. Let a diffeomorphism.
Let be a regularity structure on with model with transport precision . Define
[TABLE]
Then, is a regularity structure on with grading and is a model with transport precision . Moreover
[TABLE] 2. 2.
Let and define . Then and
[TABLE]
Proof.
Since has derivatives bounded below and above for every compactum, one can choose for every compactum a constant as in the definition of a model, such that is well-defined for and as well as . Here denotes the exponential map on .
Let and and
[TABLE]
since falls under Remark 7. For with and , we have
[TABLE]
again by Remark 7. Finally for with and , we have
[TABLE]
- Let then
[TABLE]
and similarily for the distance of two modelled distributions. ∎
Lemma 20** (Reconstruction for ).**
Let be a regularity struture on , an open connected subset of . Let be a model with precision . Let and assume . Denote . Assume either that or that and that the lowest homogeneity in is given by the constant distribution (of the polynomial regularity structure of Section 4).
For every there exists a unique such that for every compactum
[TABLE]
Here , , (so that the action of is well-defined) and .
Remark 21**.**
Uniqueness actually holds in the class of operators that satisfy (5) with replaced by any .
Proof.
**Existence
**We will apply [Hai14, Proposition 3.25].111Compare also [Hai15, Theorem 2.10] for a concise presentation of the (wavelet) techniques involved in its proof. This Proposition is formulated for , but the statement is local and also holds for . So we have to verify for
[TABLE]
uniformly over , , and . In [Hai14, Proposition 3.25] the upper bound is chosen on , but any upper bound works, so we chose , since we need to be well-defined.
Here
[TABLE]
and is a scaling function for a wavelet basis of regularity . We have chosen also such that for and , the expression is well-defined. First, (7) follows from the fact that is the lowest homogeneity in (note that is scaled to preserve the -norm, whereas the scaling in the definition of a model preserves the -norm).
Now
[TABLE]
We bound the first term as
[TABLE]
since . The second term is bounded as
[TABLE]
This proves (6) and an application of [Hai14, Proposition 3.25] gives the existence of satisfying the bound (5).
The preceding argument is valid for . For , one can run the argument for some and get unique existence of with the claimed properties. In Corollary 23 below it is shown that actually .
**Uniqueness
**Uniqueness follows exactly as in [Hai14, Section 3].
∎
Lemma 22** (Reconstruction for a closed Riemannian manifold).**
Let be a closed Riemannian manifold with regularity structure and a model with transport precision . Let , and and assume .
Denote . Assume either that or that and that the lowest homogeneity in is given by the constant distribution (of the polynomial regularity structure).
Then, there exists a unique distribution such that
[TABLE]
for , .
Proof.
By a cutting up procedure, it is enough to show (8) for , with to be chosen.
Let an atlas with subordinate partition of unity , with finite. On each chart, we push-forward the regularity structure, model and to with corresponding reconstruction operation , model and modelled distribution . For each fix a compactum such that is strictly contained in . By Lemma 19,
[TABLE]
Now reconstruct in each coordinate chart as using Theorem 20. Define . Then
[TABLE]
If we want the summand to vanish. So let . Then for , we have implies . Hence, if we have , so the summand vanishes.
Otherwise, with
[TABLE]
since falls under Remark 7 around . Summing over gives (8).
∎
Corollary 23**.**
In setting of the previous theorem, assume that the lowest homogeneity in is [math] and that it is given by the constant (as in the polynomial regularity structure of Section 4). Then is given by projection onto that homogeneity, i.e.
[TABLE]
Proof.
Define , then
[TABLE]
Recall that the projection is defined in Definition 13. The last term is of bounded by a constant times , where is the smallest homogeneity strictly larger than [math].
For the second to last term we first write
[TABLE]
Now, since ,
[TABLE]
By the properties of a model
[TABLE]
Hence and then
[TABLE]
Hence, by Remark 21, . ∎
We want to apply the Lemma 22 to the terms in the heat kernel asymptotics (Theorem 40). The problem is that their support will be of order (and not of order as for ). Hence we need the following refinement which is similar to Lemma 8.
Lemma 24**.**
*In the setting of Lemma 22, let satisfy the assumptions of Lemma 8 with the additional condition . Then *
[TABLE]
where is defined in Lemma 8.
Proof.
Let be given as in the proof of Lemma 16 with . Recall that . Hence for . Then with
[TABLE]
Note that in the sum . Hence is well-defined. Now the first summand can be written as
[TABLE]
Applying Remark 7 to and (8), this is bounded by a constant times .
The second summand is bounded as
[TABLE]
Hence
[TABLE]
for . ∎
4 Linear “polynomials” on a Riemannian manifold
The regularity structure for linear “polynomials” on the Riemannian manifold will be built on the vector bundle . For readability introduce the symbol and decree that it forms a basis for . Define the graded vector bundle
[TABLE]
with grading . For let be the fiber at . A generic element of will be written as
[TABLE]
with . Let , where is the radius of injectivity of . Define the linear map as
[TABLE]
Note that since is a trivial fiber bundle, it is enough to specify it on the basis element . This is not possible on . Note also that is chosen to have value [math] and differential at .
Finally define the re-expansion maps as
[TABLE]
which is well-defined for ; the radius of injectivity of . and together form the polynomial model, where we take in Definition 14.
The transport of is chosen such that and have, at , the same value and the same first derivative. Our re-expansion is not exact, i.e. we do not have , but we have the following.
Lemma 25**.**
For , uniformly for bounded,
[TABLE]
Proof.
Let
[TABLE]
By construction and hence the statement follows from Taylor’s theorem. ∎
Remark 26**.**
In the setting of the previous Lemma, not only but also . Indeed, for two points at distance smaller than the cut locus and ,
[TABLE]
where the tangent map satisfies indeed By definition,
[TABLE]
does a priori disagree with but at . Let us set and The path is the unique path from to with length and speed staying within the cut-locus from , that is in other words, for any
[TABLE]
Hence,
[TABLE]
and
[TABLE]
The next lemma follows from Lemma 25 and is shown in more generality in Theorem 89.
Lemma 27**.**
The above is a model of transport precision .
As a sanity check for our construction, we mention the following lemma, which is almost immediate in the flat case (see [Hai14, Lemma 2.12]). We will prove it in Section 9 in a more general setting.
Lemma 28**.**
For , a function is in if and only if there exists a function with and .
In that case: .
5 The regularity structure for PAM on a manifold
In the next four sections is a -dimensional closed manifold.
The regularity structure for PAM will be built on two copies of the vector bundle, We denote these two copies by and . In order to distinguish the different elements of these bundles we introduce the symbols and decree that they form a basis for We then write
[TABLE]
where is simply another copy of Formally we have, . As usual we will let and denote the fibers of these bundles over
The vector bundles and are graded, with gradings
[TABLE]
for some corresponding to the regularity of the driving white noise .
For (or recall (Definition 13) that ( is the projection taking an element to its – component. To be concrete, generic elements are of the form
[TABLE]
with . And then for example
[TABLE]
All the graded fibers have a canonical norm, where on the cotangent space we use the norm induced by the Riemannian metric. For , (or ) we write, in a slight abuse of notation, .
The model we shall use for the parabolic Anderson model will be time dependent, so we need slight extensions of our definitions.
Definition 29**.**
For , assume we are given a family of models on parametrized by . Define
[TABLE]
where is defined in Definition 14. Note that for fixed , the model comes with a reconstruction operator (Theorem 22), which we shall denote .
Definition 30** (Time-dependent modelled distributions).**
For , given a family of models parametrized by , denote by the corresponding spaces of modelled distributions. That is, as defined in Definition 17,
[TABLE]
For , define the modified norm
[TABLE]
Here if and if .
Define to be the space of functions with and
[TABLE]
where if and if . For , define the modified norm
[TABLE]
Remark 31**.**
The modified norms with scaling parameter are necessary for the fixpoint argument, see Remark 36.
As usual with Hölder-type spaces on compact domains, these spaces are complete Banach spaces.
We now build the model for the structures . As input we need realization of and .
Definition 32**.**
Assume for we are given and a family of distributions , , satisfying
[TABLE]
where the action of the heat kernel on is well-defined by Theorem 34. Define
[TABLE]
where and is the radius of injectivity of .
In our application to white-noise forcing, will be the white noise on and will be constructed via Gaussian renormalization in Section 8.
Now define the models for and as
[TABLE]
with transports
[TABLE]
Lemma 33**.**
These are in fact models with the radius of injectivity of and the distances/norms of the model only depend on . Indeed for ,
[TABLE]
with for and for .
Proof.
By Lemma 11
[TABLE]
By definition
[TABLE]
Moreover
[TABLE]
since , with .
Regarding transport, both the transport of and are exact by definition and
[TABLE]
where we used Lemma 25 for the last step.
Finally
[TABLE]
by the Schauder estimate Theorem 34, and
[TABLE]
by Lemma 27. Hence
[TABLE]
when .
Analogously, one gets the bounds for with . ∎
6 Schauder estimates
Let be the heat kernel on . We start with a Schauder estimate for distributions. Since its proof follows the same idea as the upcoming Schauder estimate for modelled distributions, we omit the proof of the next theorem.
Theorem 34**.**
Let , and , for . Then for
[TABLE]
We now prove an extension of this classical result to the space of modelled distributions. For
[TABLE]
an element of 222Recall from the beginning of this section that are real-valued and is a section of ., define
[TABLE]
with
[TABLE]
The well-definedness of these terms is part of the following theorem.
Theorem 35** (Schauder estimate).**
For with , set and . Let and . Then, for all
[TABLE]
Moreover, , with , and
[TABLE]
Remark 36**.**
Here we can see why we introduced the modified norm . Without it, i.e. with , the factor on the right hand side cannot be made small, which is necessary for the fixpoint argument.
Remark 37**.**
Contrary to classical Schauder estimates, we only get an “improvement of derivatives”. In order to get an “improvement of derivatives” one has to include quadratic polynomials in the regularity structure. This is also the reason why we have to choose in such a specific way. Note that an improvement by will be enough to set up the fix-point argument.
To be specific, in order to get an “improvement of derivatives” the complete list of symbols necessary is, ordered by homogeneity,
[TABLE]
where stand for the space-directions.333Assuming that one builds a regularity structure including space and time. These symbols would be the building blocks for the regularity structure on flat space. On a manifold the polynomials would represent the respective symmetric covariant tensor bundles, as laid out in Section 4. The Schauder estimate has to be shown on the level of each of theses symbols, and hence a treatment “by hand” as we do here would be cumbersome.
Remark 38**.**
The following proof based on the heat kernel (almost) being a scaled test function goes back, in the flat case, to [CM2016]. A proof splitting up the heat kernel into a sum of smooth, compactly supported kernels (following the strategy of [Hai14]) is also possible, but more cumbersome.
Proof of Theorem 35.
The first statement follows from the definition of and the fact that reconstruction of modelled distributions taking values only in positive homogeneities is given by the projection onto homogeneity [math], see Lemma 23.
Recall that , the radius of injectivity. By Remark 18 we can, and will only consider . Introduce the short notation
[TABLE]
Note that .
We shall need the following facts. Since
[TABLE]
we have
[TABLE]
where we used the classical Schauder estimate Theorem 34.
Moreover for a function satisfying the assumptions of Lemma 16 and Lemma 24 (recall that is the reconstruction operator of Theorem 22 associated to the model )
[TABLE]
and similarily
[TABLE]
We now estimate each term in the definition of the norm .
**Space regularity
Homogeneity [math]**
[TABLE]
where using heat asymptotics, Theorem 40.
Regarding the easier term involving we write
[TABLE]
where acts on the dummy variable and convolution acts on and is the geodesic connection to . Since
[TABLE]
this expression is well-defined for large enough and of order
[TABLE]
We now treat the term involving . Denoting by the integrand of the above integral, for ,
[TABLE]
The first term we bound as
[TABLE]
where we used (10) together with Lemma 41 (i), as well as to Hölder continuity of in space (9) and in time.
The second we bound as
[TABLE]
where we used (10) together with Lemma 41 (i) as well as the Hölder continuity of in time.
The last one we bound as
[TABLE]
where we used (10) together with Lemma 41 (ii) as well as to Hölder continuity of in space (9) and in time.
Hence
[TABLE]
and then by Lemma 39
[TABLE]
if
[TABLE]
Then the following are upper bounds to
[TABLE]
Both are satisfied under our assumptions.
Now consider . By [DS15, Theorem 6.1] we have
[TABLE]
where for any and is acting on the first variable of . Now
[TABLE]
The first term we bound as
[TABLE]
where we used (10) together with Lemma 41. 444 In coordinates,
where are the Christoffel symbols. This gives the quadratic factor in . The blowup in follows from an application of Lemma 41 (i), (ii) to the components here.
The second term we bound as
[TABLE]
where we used Lemma 41 and the Hölder continuity of in time.
Hence by Lemma 39
[TABLE]
if
[TABLE]
Then the following are upper bounds to
[TABLE]
Both are satisfied under our assumptions.
Hence
[TABLE]
Homogeneity
[TABLE]
so we need
[TABLE]
which is satisfied under our assumptions.
**Homogeneity
**As on homogeneity we write . We only treat the term involving .
[TABLE]
It is enough to bound this expression acting on . Write
[TABLE]
For we bound ( denotes the dummy variable on which is acting, denotes the dummy variable in the distribution-pairing)
[TABLE]
where we used (10) together with Lemma 41 (ii), as well as the Hölder continuity of in time.
Now
[TABLE]
where we used (10) together with Lemma 41 (ii) with Y_{p}:=d|_{p}\exp^{-1}_{q}(z)\Bigl{(}X\Bigr{)}, as well as the Hölder continuity of in time.
Hence by Lemma 39
[TABLE]
if
[TABLE]
Then the following are upper bounds to
[TABLE]
Both are satisfied under our assumptions.
Consider now . Again it is enough to bound the term acting on some . For notational simplicity let and . We then write the term to bound as
[TABLE]
Now with ,
[TABLE]
where we used (10) together with Lemma 41 (iii).
Similarily
[TABLE]
where we used Lemma 41 (iii) and the Hölder continuity of in time.
Finally
[TABLE]
where we used Lemma 41 (ii) and the Hölder continuity of in space (9).
Hence by Lemma 39
[TABLE]
if
[TABLE]
Then the following are upper bounds for
[TABLE]
Both are satisfied under our assumptions.
Then
[TABLE]
**Time regularity
**As on homogeneity [math] we write . We only treat the term involving .
[TABLE]
Now using (11) and Lemma 41 (i)
[TABLE]
Further, again using (11) and Lemma 41 (i)
[TABLE]
if
[TABLE]
We then need
[TABLE]
Both are satisfied under our assumptions.
Then
[TABLE]
∎
We used the following lemmas.
Lemma 39**.**
Let , and assume
[TABLE]
Let such that , . Then
[TABLE]
Proof.
Indeed
[TABLE]
and
[TABLE]
∎
The following result on heat kernel asymptotics is classical and its proof can be found for example in [D, Theorem 3.10] and [BGV92, Theorem 2.30] See also [Ros97, Section 3.2]. In these references the norm is defined via a partition of unity as in Definition 10. There is a slight difference to our notation. In the cited references, for example means “continuously differentiable”, while in our notation it only means “Lipschitz continuous”. But it is enough to know that our norm is dominated by the norm in the references.
Theorem 40**.**
Let be a -dimensional, closed Riemannian manifold and be the heat kernel on . Then there exist smooth functions such that if we define for
[TABLE]
we have
[TABLE]
Here for .
Lemma 41**.**
Let
[TABLE]
* smooth and with for .*
Let and define for in the range of , a tangent vector and a vector field
[TABLE]
(Note that because of the small support of , these are globally well-defined smooth functions by continuation with zero outside of the range of .)
Then for any multiindex , any and .
- (i)
** 2. (ii)
** 3. (iii)
**
Proof.
The summands of are of the same form, apart from the factors , . Since for they improve the singularity at , it is enough to treat .
Then
[TABLE]
Since is smooth, uniformly in , with support in , and the factor in the exponential is irrelevant, we consider
[TABLE]
where we abuse notation and keep the same name. Now this is the Schwartz function scaled by a factor of , and so part (i) with follows from by Remark 9.
Now
[TABLE]
The first term is treated as above, now having the additional prefactor .
We write the second term as
[TABLE]
where is Schwartz. By Remark 9 part (i) with is proven.
For the second statement
[TABLE]
The first term has worse blowup in and the factor in the exponential is irrelevant, so it is enough to consider where
[TABLE]
Now for a multiindex
[TABLE]
By Lemma 42
[TABLE]
and by Lemma 44
[TABLE]
Hence for
[TABLE]
For we have and then
[TABLE]
The second statement then follows, since is a Schwartz function, for any .
The third statement follows in a similar fashion from Lemma 42 and Lemma 43. ∎
Lemma 42**.**
Let acting on the first component of as follows
[TABLE]
Then
[TABLE]
Proof.
Since is smooth, we only need to show .
Let . Fix and take coordinates . Then
[TABLE]
Then as desired. ∎
Lemma 43**.**
Let
[TABLE]
Then, for any multi-index
[TABLE]
Proof.
This follows from the fact that is smooth. ∎
Lemma 44**.**
For any multiindex
[TABLE]
Proof.
This can be verified using the Faa di Bruno formula. ∎
7 Fixpoint argument
The following lemma follows from a direct application of the definition of modelled distribution.
Lemma 45**.**
Define “multiplication by ” as the vector bundle morphism satisfying
[TABLE]
If then and for
[TABLE]
Theorem 46**.**
Let . Define and lift it to the regularity structure as
[TABLE]
Let be given as in Definition 32 and let be the corresponding models given by Lemma 33, . Let , and . Then there exists and a unique such that on
[TABLE]
Proof.
We follow a standard fixpoint argument. Denote
[TABLE]
Denote for
[TABLE]
Claim: for any there is such that .
Indeed, by Theorem 35 and Lemma 45, for a constant possibly changing from line to line,
[TABLE]
since . Hence for small enough and large enough, , for any .
Let us show that is a contraction on : for any
[TABLE]
Hence for small enough and large enough, is a contraction on for any .
We therefore get unique existence of a solution for small . ∎
8 Appendix - The Gaussian model
Let be white noise on . We recall that is a Gaussian process associated to the Hilbert space on a probability space
Lemma 47**.**
There exists a realization of such that almost surely for any .
Proof.
For any coordinate chart defined on an open subset and a positive function with support in is a Gaussian process associated to the Hilbert space Note that has the same law as , with and a white-noise on . According to [Hai14, Lemma 10.2] has a version which is almost surely in and hence .
Let now be a partition a unity subordinated to an atlas Then, there is a realization of such that almost surely for all Then, is a realization of belonging almost surely to . ∎
Thanks to this realization, we can already define the transport map used in the following Lemma (point (i)).
Lemma 48**.**
Let be the white noise on and , be a collection of random distributions on such that for some , some ,
- (i)
Z^{t}_{q}(\cdot)=Z^{t}_{p}(\cdot)+\int_{0}^{t}\Big{\langle}\mathsf{p}_{t-r}(p,\cdot)-\mathsf{p}_{t-r}(q,\cdot),\xi\Big{\rangle}dr\xi(\cdot), 2. (ii)
[TABLE] 3. (iii)
*for any
is in the second Wiener chaos.*
Then, there is a version of and a constant such that a.s.
[TABLE]
Proof.
For define for a chart
[TABLE]
Note that and are elements of . Then
[TABLE]
where we denote .
Define the regularity structure and model (in the stronger sense of [Hai14])
[TABLE]
and the sector (in the sense of [Hai14, Definition 2.5])
[TABLE]
One can then apply [Hai14, Proposition 3.32] to get for every compacta , and555in the notation of [Hai14, Proposition 3.32], stands for , , with
[TABLE]
Then, for large enough, using (iii), equivalence of moments and then (i)
[TABLE]
Let now be a finite atlas with subordinate partition of unity . Then for , ,
[TABLE]
Now for small enough, implies that and in particular . Hence
[TABLE]
where . We can apply Remark 7 to and can estimate, using (15),
[TABLE]
here for every , is some compactum satisfying . Then, by (16),
[TABLE]
Let us formulate a setting where we can apply Kolmogorov’s continuity theorem in time. Endow the linear space of maps , such that for any , with the norm
[TABLE]
and consider the Banach space We apply this to
[TABLE]
Here , with smooth, and on for some small enough. Then, from the argument before, for any and large enough, we have
[TABLE]
The result now follows from the Kolmogorov continuity theorem. ∎
A simple way to define is to consider the Wick product of the random variables involved. For any the heat kernel and the heat operator are denoted respectively by and and we write for any According to Lemma 47 and Theorem 40, we can consider as a function and the map is continuous.
We set for any and any function
[TABLE]
where for any and
[TABLE]
Note that for any
[TABLE]
For any let us consider the operator and for any with set Let us note that the operator
[TABLE]
has a continuous kernel according to Theorem 40, that we shall denote .
Proposition 49**.**
For any almost surely for any and is well-defined and there exists a modification of the process given by such that almost surely (13) holds true. 666In particular, almost surely, for all and is measurable and bounded.
Proof of Proposition 6.
It is enough to prove the assumption of Lemma 48. Let us fix Recall that is the radius of injectivity of and let .
Let us first check that for any is well defined. Therefor, let us recall – see Theorem 40 – that
[TABLE]
The Wick formulas imply for any
[TABLE]
It follows that
[TABLE]
Besides, so that is well defined. We shall now prove that for any
[TABLE]
which together with Lemma 47 shall yield the claim. We fix now Let us first prove that the expectation of the second integrand in is almost surely of homogeneity . Indeed, according to [D], for fixed, there exists , such that, for all with
[TABLE]
Since
[TABLE]
it follows that for any
[TABLE]
Setting and 777 Where me denote the distribution .
it remains to estimate
[TABLE]
For any
[TABLE]
and
[TABLE]
where the second line follows from the Cauchy-Schwarz inequality. It follows from the bound (21) that there exists , such that for any
[TABLE]
Hence for any and ,
[TABLE]
∎
Lemma 50**.**
For any , there exists such that for any
[TABLE]
Proof.
On the one hand, according to (17) and Theorem 40, the left-hand-side of (21) is uniformly bounded by for all for some On the other hand, the estimate (21) would hold true, with if would be replaced by symmetric function on . Indeed if is a symmetric function,
[TABLE]
where the index below the connexion symbol indicate the variable on which the latter is acting, and is a geodesic from to . According to Theorem 40, one can therefore consider in place of as soon as is large enough. This same Theorem ensures that there exists a smooth function such that for all
[TABLE]
Let us set for any We shall apply (22) to for any fixed Up to a constant, the integrand of the right-hand-side of (22) is bounded by Let us set The first term can be bounded by
[TABLE]
and the second by
[TABLE]
for some constant These two bounds, once integrated in (22), imply that for any the left-hand-side of (21) is bounded by uniformly on and Using the bound for gives (21). ∎
9 Appendix - Higher order “polynomials”
We recall the regularity structure of polynomial functions in flat space given in [Hai14]. It is used to abstractly describe functions in , , and also forms a central ingredient for general regularity structures associated with singular SPDEs. Let and , that is and . For simplicity of notation let . Define
[TABLE]
where denotes the one-dimensional vector space spanned by the abstract symbol . Hence .
Given and we define the linear maps, and which are uniquely determined by
[TABLE]
In this case one has for all One can use this regularity structure to describe regular functions.
Lemma 51** ([Hai14, Lemma 2.12]).**
Let . Then if and only if there exists with and
[TABLE]
In that case . 888 Here we recall the notation of as the component of on the -th homogeneity, i.e. the coefficient in front of .
9.1 Higher order covariant derivatives
We want to mirror as best we can the flat space polynomial model described above, in the general context of a dimensional Riemannian manifold. In order to do to this we need to store higher order derivatives of functions in a coordinate independent fashion. There is a canonical way to do this on a Riemannian manifold by making use of the associated Levi-Civita connection.
We recall the notion of higher order covariant derivatives of functions on a Riemannian manifold with Levi-Civita999In general, can be any affine connection. connection (see for example [Lee06, Lemma 4.6]).
Definition 52**.**
Define by,
[TABLE]
and then inductively by;
[TABLE]
where are arbitrary vector fields on
A few remarks are in order.
As the notation suggests, is indeed tensorial, i.e. the right side of the previously displayed equation really only depends on the vector fields, , through their values at 2. 2.
In the literature sometimes denotes the gradient of . We never use the gradient of a function in this work. 3. 3.
We shall also sometimes write for any
Lemma 53**.**
If is an -times continuously differentiable function in a neighborhood of and then
[TABLE]
More generally, if is an -times continuously differentiable function in a neighborhood of is parallel translation along and then
[TABLE]
Proof.
Let so that solves the geodesic differential equation, with The proof is completed by showing (by induction) that
[TABLE]
The case amounts to the definition that for all For the induction step we have by the product rule;
[TABLE]
wherein the last equality we have again used the product rule to conclude that The result now follows by evaluating (26) at and The more general assertion in (25) is proved similarly. One only need observe that and hence the presence of in the expressions in no way changes the computations. ∎
Definition 54** (Symmetrizations).**
If is a real vector space and we let denote the symmetrization projection uniquely determined by
[TABLE]
where is the permutation group on Often we will simplyt write for as it will typically be clear what is from the argument put into the symmetrization function.
As usual we let denote the dual space to a vector space and let denote the pairing between a vector space and its dual. We will often identify with where the identification is uniquely determined by
[TABLE]
We also identify with the space of multi-linear maps from using,
[TABLE]
Under these identification we have
[TABLE]
and
[TABLE]
Remark 55**.**
If and then
[TABLE]
and therefore,
[TABLE]
This formula shows that the symmetric part of is completely determined by the knowledge of for all
Definition 56**.**
Let denote the symmetric tensors in and for let denote the symmetrization of as above.
Example 57**.**
If is an open subset of and is -times continuously differentiable on , then defines a local section (over of Moreover since is symmetric for all we may write (24) as
[TABLE]
Theorem 58** (Taylor’s Theorem on ).**
Let and If is -times continuously differentiable on , where is an open set containing then
[TABLE]
When the previous equation is to be interpreted as (also see [DS15, Theorem 6.1])
[TABLE]
where
[TABLE]
Proof.
Let and recall that the standard Taylor’s theorem with remainder states;
[TABLE]
The results now follow by using Lemma 53 in order to compute the for ∎
Theorem 58 has the following immediate corollaries.
Corollary 59**.**
Moreover,
[TABLE]
where and as
Proof.
According to (30), (31) holds with
[TABLE]
where
[TABLE]
Therefore where
[TABLE]
∎
Remark 60**.**
Since parallel translation is isometric it follows (continuing the notation in Theorem 58) that
[TABLE]
and hence
[TABLE]
Since is a compact Riemannian manifold it is necessarily complete and therefore, by the Hopf–Rinow theorem, for each we may find at least one such that and Using these remarks we can reformulate (29) as follows.
Corollary 61**.**
If is -times continuously differentiable on , and is chosen so that and then
[TABLE]
where
[TABLE]
Furthermore if is -times continuously differentiable on then
[TABLE]
Definition 62** (Taylor approximations).**
Suppose that is an open subset of a -times continuously differentiable function on and is sufficiently small so that and is smaller than the injectivity radius of We then define, by
[TABLE]
With this notation we have the following local version of Corollary 61.
Corollary 63**.**
If is a -times continuously differentiable function on , with smaller than the injectivity radius of then
[TABLE]
Remark 64**.**
In the case and is a polyonmial of degree at most it follows by Taylor’s theorem that for all So in the flat case the error term in (35) is no longer present.
Lemma 65**.**
If is a -times continuously differentiable function on and then for any - order differential operator and in particular, for all
Proof.
Let be a chart on with and and define Then the give assumption implies and therefore for any and small we have from which it easily follows that
[TABLE]
As is symmetric and was arbitrary we may conclude that for As any - order differential operator on may be written locally as
[TABLE]
for some smooth functions, for each it follows that
[TABLE]
∎
Corollary 66**.**
If a -times continuously differentiable function on and is an - order differential operator, then
[TABLE]
and in particular,
[TABLE]
from which it follows that is a linear combination of
We will make the last assertion of Corollary 66 more explicitly in Corollary 72 and Remark 74. The upshot is that there is no loss of information in only keeping track of the symmetrizations of the covariant derivatives.
Corollary 67**.**
If with then for we have
[TABLE]
where
Proof.
Let us apply the estimtate in (32) with replaced by keeping in mind that for by Corollary 66. This allows us to conlude for that
[TABLE]
where As the map is an isometry it follows that
[TABLE]
∎
9.1.1 Symmetric parts of covariant derivatives determine all
derivatives
We will now make Corollary 66 more precise.
Definition 68**.**
If is a chart on let denote the flat covariant derivative on determined by for
Remark 69**.**
If is a vector field on and then Using , it easily follows that for all and -times continuously differentiable we have
[TABLE]
and in particular
Lemma 70**.**
Suppose that is a chart on is the covariant derivative of Notation 68. Then, there exists a family of sections for such that and for all -times continuously differentiable functions
[TABLE]
Proof.
Let and be the – valued connection one form on so that It is enough to verify that (36) holds on a basis for To this end, let for and let Then,
[TABLE]
which shows that (36) holds for For the sake of completing the proof by induction, let us now assume that (36) holds at level and below. In particular we assume
[TABLE]
On one hand,
[TABLE]
while on the other hand (using the induction hypothesis, the product rule, and for all
[TABLE]
Comparing the last two displayed equations shows,
[TABLE]
From this expression it follows that may be expressed in the form claimed in (36). ∎
Corollary 71**.**
Let us continue the notation in Lemma 70. Then, there exists
[TABLE]
such that and for all -times continuously differentiable functions
[TABLE]
Proof.
The proof is again by induction on For we have so there is nothing to prove. For the inductive step, suppose that (37) holds at level and below. From (36) with replaced by it follows that,
[TABLE]
wherein the last equality we have used that is already symmetric. From the previous equation along with the inductive hypothesis, we conclude that may be expressed as described in (37). ∎
Corollary 72**.**
If is a covariant derivative on then there exists
[TABLE]
such that and for all -times continuously differentiable functions
[TABLE]
Proof.
First suppose that as in Lemma 70. Then combining the results of Lemma 70 and Corollary 71, there exists such that (38) holds for all Let be a collection of charts on such that is an open cover of and be a partition of unity relative to this cover. To complete the proof we define
[TABLE]
∎
We note the following corollary for completeness.
Corollary 73**.**
If is a covariant derivative on on is a linear - order differential operator on then there exists smooth sections, for such that
[TABLE]
Proof.
By definition is locally given by for some Using Corollaries 71 and 72, we may locally express as in (39). The global picture may then be constructed using a partition of unity argument. ∎
Remark 74**.**
Our proof of Corollary 72 was local in nature and hence does not give much information about how the depend on It is possible to give a global proof of Corollary 72 which would show that may be constructed from certain combinations of covariant derivatives of the torsion and curvature tensor of Here is a sketch of this argument. In this sketch we let for any
If and then
[TABLE]
where is the appropriate action of the curvature tensor of on and is the torsion tensor of 2. 2.
As a consequence of item 1. and the fact that every permutation is a composition of transpositions, it follows that for any permutation
[TABLE]
where are constructed from certain combinations of covariant derivatives of the torsion and curvature tensor of 3. 3.
Summing (40) on and then dividing by and setting
[TABLE]
shows
[TABLE]
where the are constructed from certain combinations of covariant derivatives of the torsion and curvature tensor of 4. 4.
Using (41) recursively then shows there exists such that
[TABLE]
where each is constructed from certain combinations of covariant derivatives of the torsion and curvature tensor of
9.2 The regularity structure and model
We are now ready to set up to regularity structure for “polynomials” up to order on a manifold.
Definition 75**.**
Fix and let be the vector bundle over with fiber at given by
[TABLE]
For and near let
[TABLE]
The vector bundle will be used to store higher order derivatives of functions. On flat space such “abstract Taylor expansions” were realized as honest functions using polynomials, see (23). Polynomials are the simplest function that have specified derivatives at one point. On the manifold we instead choose polynomials in exponential coordinates.
Definition 76** (Model).**
For define
[TABLE]
These local “Taylor polynomials” are a good substitute for the usual Taylor polynomials in the flat space theory, as Lemma 77 and Corollary 78 below demonstrate.
Lemma 77**.**
Let with for and define
[TABLE]
Then,
[TABLE]
Proof.
Let . Then,
[TABLE]
and hence by Lemma 53
[TABLE]
which suffices to complete the proof by Remark 55. ∎
We now have the immediate corollary of this lemma.
Corollary 78**.**
Let . Then, for
[TABLE]
Remark 79**.**
Let be exponential coordinates around , i.e. suppose that where are the coordinates of relative to some basis of Then with
[TABLE]
from which it follows that
[TABLE]
Definition 80** (Transportation).**
Let be defined by where
[TABLE]
which makes sense for , the radius of injectivity of .
Remark 81**.**
For this transport will in general also go “upwards.” That is, if some , then in general will have components in homogeneities strictly larger than . This is not allowed in the original formulation of a regularity structure by Hairer [Hai14, Definition 2.1]. As we have seen in the main text, this poses no problem, since our modified definition of a model (Definition 14) allows for it. We moreover believe that any transport that wants to achieve the following lemma for a “polynomial model” is forced to do this.
The definitions have been arranged so that and agree at to order i.e. and along with all derivatives up to order agree at
Lemma 82**.**
Let and where is a sufficiently small neighborhood of If is a differential operator of order defined on then
[TABLE]
Proof.
Let
[TABLE]
so that
[TABLE]
Using Corollary 67, we have the estimate,
[TABLE]
where For and let so that is the geodesic joining to parametrized by Then we have
[TABLE]
and so we have
[TABLE]
∎
For the proof of the first half of Theorem 90 below, it is convenient to introduce the notion of a parallelism on a vector bundle, , over
Definition 83** (Diagonal domains).**
Let be an open set on . An open set is a** ** – **diagonal domain **if it contains the diagonal of , that is . A local diagonal domain is a – diagonal domain for some nonempty open .
If we write and refer to simply as a diagonal domain.
Definition 84** (Parallelisms).**
Let be a vector bundle over and be the associated vector bundle over with fibers, for where denote the set of all linear transformations from to A smooth local section with domain (i.e. for all ) is called a **parallelism **if . If is only defined on a local diagonal domain, we refer to as a local parallelism.
Example 85** (Parallel translation and parallelisms).**
One natural example of a parallelism when is a Riemannian manifold and is equipped with a covariant derivative, is to define
[TABLE]
where are “close enough” so there is a unique vector with minimum length such that and denotes the parallel translation operator on relative to For our purposes below will be a bundle associated to and will be the induced connection on this bundle associated to the Levi-Civita covariant derivative on
Example 86** (Charts and parallelisms).**
Each chart induces a local parallelism on for any as follows. If is expressed as
[TABLE]
then we define by
[TABLE]
In other words, is uniquely determined by requiring
[TABLE]
for all and [This example is basically a special case of Example 85 where one takes to be the flat connection, defined in Notation 68.]
With the aid of a parallelism, we can now define the notion of – Hölder section, on In what follows we assume that is equipped with a smoothly varying inner product, We do not necessarily assume that is compatible with or that is unitary for all
Lemma 87**.**
Let be a continuous section of a vector bundle . Let be parallelisms on . Then for every compactum
[TABLE]
Proof.
We work in a local trivialization. Let be smooth functions such that which we view to be a parallelism on the trivial bundle, over A continuous section of this bundle may be identified with a continuous function, Then
[TABLE]
The statement then follows from smoothness of , the fact that they coincide at and local boundedness of . ∎
Lemma 88**.**
Let and Then (as in Definition 10) iff a -times continuously differentiable function on and for any (local) parallelisms on the vector bundle satisfies
[TABLE]
where is the Levi-Civita covariant derivative.
Proof.
Recall from Definition 10, that is in iff for every coordinate chart These conditions are equivalent to being -times continuously differentiable and the – derivatives of are locally -Hölder on The latter condition may be expressed as saying
[TABLE]
where is the flat connection defined in Notation 68. From Lemma 70 and Corollary 71 we may express
[TABLE]
where is a linear differential operator of order at most As is continuously differentiable it follows that
[TABLE]
is continuously differentiable and vanishes at and therefore (by the fundamental theorem of calculus)
[TABLE]
From (46) and (47) it follows that (45) is equivalent to
[TABLE]
Lastly using Lemma 87 we conclude that the estimates in (48) and (44) are also equivalent. ∎
Theorem 89**.**
Fix and construct and as above. Then is a regularity structure and is a model of transport precision .
Proof.
The fact that is a regularity structure is immediate. Let us now set to be the injectivity radius of and for let
We have to check that
[TABLE]
The homogeneity estimate, , for follows from the fact that is a monomial of order in -coordinates. Lemma 82 gives the transport precision, i.e.
[TABLE]
Let be the covariant derivative induced by the chart . Using Lemma 70 we get
[TABLE]
and hence , which finishes the proof. ∎
We are finally able to characterize in terms of the “polynomial” regularity structure.
Theorem 90**.**
Let and continuous. Then, if and only if there is 101010The space of modelled distributions was defined in Definition 17. with . In that case,
[TABLE]
Proof.
Let and define
[TABLE]
i.e. for We have to check that , i.e. for all and
[TABLE]
or equivalently, using the definition of , if
[TABLE]
we must show
[TABLE]
**:
**Recall . Now the term to bound in (49) reads as
[TABLE]
By Lemma 78
[TABLE]
and since the expression is smooth in we can focus on
[TABLE]
Define on the vector bundle the parallelism
[TABLE]
Then by Lemma 88
[TABLE]
so for we are done.
: We need to show (49). It is enough to bound for , with ,
[TABLE]
Here denotes the parallel transport along .
For this purpose, define
[TABLE]
and Since and are parallel along it follows that
[TABLE]
Therefore by Taylor’s theorem and the fact that for 111111This follows by the very construction of along with Corollary 72 and Lemma 78., we have
[TABLE]
Since is smooth we apply the fundamental theorem of calculus to find
[TABLE]
Using this estimate, it follows that
[TABLE]
Since
[TABLE]
As shown in the step , we then get
[TABLE]
and hence
[TABLE]
Plugging this estimate back into (51) shows,
[TABLE]
which completes the proof of (49).
Recall that , for some .
Step 1: We will show that is -times differentiable and for . This will be done by induction.
So assume for some we know that
- •
is -times differentiable
- •
By Taylor’s theorem (Theorem 58)
[TABLE]
Now by assumption
[TABLE]
where
[TABLE]
Hence
[TABLE]
Plugging this into (52) and using the fact that we get
[TABLE]
Now, since is smooth and we have
[TABLE]
and therefore by Taylor’s theorem (in one variable) together with Lemma 53
[TABLE]
A simple integration by parts argument shows
[TABLE]
Combining (53), (54) and (55), we get
[TABLE]
As is a local diffeomorphism, it now follows from (56) that is times differentiable at and moreover since,
[TABLE]
we may conclude, using Lemma 53 that
[TABLE]
Then by Remark 55 it follows that
[TABLE]
Step 2: So far we have shown that is -times continuously differentiable and that for . Then with defined in (50) we have
[TABLE]
The second to last term is of order by assumption. Moreover, for , by Corollary 78, we have . Hence the last term is of order . By Lemma 88 we hence get that .
∎
Acknowledgement: The first author was supported in part by RTG 1845 and EPSRC grant EP/I03372X/1.
The second author has received funding by the DAAD P.R.I.M.E. program. He would like to thank Giuseppe Cannizzaro and Konstantin Matetski for discussion on the Schauder estimates.
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- 4[CM 2016] Cannizzaro, Giuseppe, and Konstantin Matetski. ”Space-time discrete KPZ equation.” ar Xiv preprint ar Xiv:1611.09719 (2016).
- 5[D] Driver, Bruce. Heat kernels on compact manifolds.
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