variational methods for a singular spde yielding the
TRANSCRIPT
VARIATIONAL METHODS FOR A SINGULAR SPDE YIELDING THE UNIVERSALITYOF THE MAGNETIZATION RIPPLE
RADU IGNAT, FELIX OTTO, TOBIAS RIED, AND PAVLOS TSATSOULIS
Abstract. The magnetization ripple is a microstructure formed in thin ferromagnetic lms. It canbe described by minimizers of a nonconvex energy functional leading to a nonlocal and nonlinearelliptic SPDE in two dimensions driven by white noise, which is singular. We address the universalcharacter of the magnetization ripple using variational methods based on ฮ-convergence. Due tothe innite energy of the system, the (random) energy functional has to be renormalized. Usingthe topology of ฮ-convergence, we give a sense to the law of the renormalized functional thatis independent of the way white noise is approximated. More precisely, this universality holdsin the class of (not necessarily Gaussian) approximations to white noise satisfying the spectralgap inequality, which allows us to obtain sharp stochastic estimates. As a corollary, we obtain theexistence of minimizers with optimal regularity.
Contents
1. Introduction 12. Estimates for the Burgers equation 143. ฮ-convergence of the renormalized energy 194. A priori estimate for minimizers in Hรถlder spaces 265. Approximations to white noise under the spectral gap assumption 30Appendix A. Hรถlder spaces 39Appendix B. Besov spaces 45Appendix C. Stochastic estimates 53Appendix D. Some estimates for the linear equation 55Appendix E. Regularity of nite-energy solutions for smooth data 56Appendix F. Approximation of quadratic functionals of the noise by cylinder functionals 60References 62
1. Introduction
We study minimizers of the energy functional
๐ธ๐ก๐๐ก (๐ข) :=โซT2(๐1๐ข)2 d๐ฅ +
โซT2( |๐1 |โ
12 (๐2๐ข โ ๐1
12๐ข
2))2 d๐ฅ โ 2๐โซT2b๐ข d๐ฅ (1.1)
where b is (periodic) white noise, ๐ โ R, T2 = [0, 1)2 is the two-dimensional torus and ๐ข : T2 โ Ris a periodic function with vanishing average in ๐ฅ1, i.e.,โซ 1
0๐ข d๐ฅ1 = 0 for all ๐ฅ2 โ [0, 1) .
Date: October 27, 2020, version ripple-arxiv-v1.2020 Mathematics Subject Classication. 60H17, 35J60; 78A30, 82D40.Key words and phrases. Singular stochastic PDE, nonlocal elliptic PDE, regularity theory, renormalized energy,
ฮ-convergence, micromagnetics, Burgers equation.ยฉ2020 by the authors. Faithful reproduction of this article, in its entirety, by any means is permitted for noncommercialpurposes.
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2 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
The energy functional ๐ธ๐ก๐๐ก was considered in [IO19] as a reduced model describing the mag-netization ripple, a microstructure formed by the magnetization in a thin ferromagnetic lm,which is a result of the polycrystallinity of the material. In thin lms, the magnetization canapproximately be described by a two-dimensional unit-length vector eld (in the lm plane);the ripple is a perturbation of small amplitude of the constant state, say (1, 0). In this context,the function ๐ข corresponds to the transversal component of the magnetization, after a suitablerescaling. The theoretical treatment in the physics literature [Hof68, Har68] takes it for grantedthat the ripple is universal, in the sense that it does not depend on the precise composition andgeometry of the polycrystalline material. Our main result gives a rigorous justication of theuniversal behavior of the ripple (see Remark 1.5).
The rst term in ๐ธ๐ก๐๐ก can be interpreted as the exchange energy, an attractive short-rangeinteraction of the spins. The second term is the energy of the stray eld generated by themagnetization; the fractional structure is due to the scaling of the stray eld in the thin lmregime. On the scales that are relevant for the description of the magnetization ripple, the noiseacts like a random transversal eld of white-noise character. It comes via the crystalline anisotropyfrom the fact that the material is made up of randomly oriented grains that are smaller than theripple scale, which is set to unity in the abovemodel. In view of its origin, it is reasonable to assumethat this noise, which is quenched as opposed to thermal in character, is isotropic, neverthelessthe nonlocal interaction given by the stray eld energy leads to an anisotropic response of themagnetization. For a more in-depth description and formal derivation of the energy ๐ธ๐ก๐๐ก we referto the discussion in [IO19, Section 2], which in turn follows [SSWMO12].
Formally, critical points of ๐ธ๐ก๐๐ก are solutions to the Euler-Lagrange equation
(โ๐21 โ |๐1 |โ1๐22)๐ข + ๐(๐ข๐ 1๐2๐ข โ 1
2๐ข๐ 1๐1๐ข2)+ 12๐ 1๐2๐ข
2 = ๐๐b, (1.2)
where ๐ 1 = |๐1 |โ1๐1 is the Hilbert transform acting on the ๐ฅ1 variable, see (1.15), and ๐ is the๐ฟ2-orthogonal projection on functions of zero average in ๐ฅ1 (extended to periodic Schwartzdistributions in the natural way). One of the main challenges of this equation is that the right-hand side of (1.2) is too irregular to make sense of the nonlinear terms, even though the nonlocalelliptic operator
L := โ๐21 โ |๐1 |โ1๐22has the expected regularizing properties.
If we endow our space with a CarnotโCarathรฉodory metric which respects the natural scalinginduced by L, that is, one derivative in the ๐ฅ1 direction costs as much as 2
3 derivatives in the ๐ฅ2direction, the eective dimension in terms of scaling is given by dim = 5
2 . It is well-known that inthis case b is a Schwartz distribution of regularity just below โdim
2 , i.e., a Schwartz distributionof order โ 5
4โ (measured in a scale of Hรถlder spaces C๐ผ associated to this CarnotโCarathรฉodorymetric; see Section 1.1.3 below for the denition), where for ๐ผ โ R, we use the notation ๐ผโ todenote ๐ผ โ Y for any Y > 0 (suitably small).
We now argue that the nonlinear term ๐ข๐ 1๐2๐ข on the left-hand side of (1.2) is ill-dened:On the one hand, Schauder theory for the operator L improves regularity by 2 degrees on theHรถlder scale, indicating that the expected regularity of a solution ๐ข is (2 โ 5
4 )โ = 34โ. On the
other hand, in our anisotropic scaling, one derivative in the ๐ฅ2 direction reduces regularity by32 , while the Hilbert transform has a negligible eect on the regularity. Hence the regularity ofthe Schwartz distribution ๐ 1๐2๐ข is โ 3
4โ. It is well-known that the product of a function and aSchwartz distribution can be classically and unambiguously dened only if the regularities ofthe individual terms sum up to a strictly positive number. In the case of the product ๐ข๐ 1๐2๐ข ofthe function ๐ข and the Schwartz distribution ๐ 1๐2๐ข, the sum of regularities is 0โ, not allowing itstreatment by means of classical analysis.
This is a common problem in the theory of singular Stochastic Partial Dierential Equations(SPDEs), which has become a very active eld in the recent years. Here the word singular relates
VARIATIONAL METHODS FOR A SINGULAR SPDE 3
to the fact that the driving noise of these equations is so irregular that their nonlinear terms(which usually involve products of the solution and its derivatives) are not classically dened. Werefer the reader to [Hai14] for a more detailed exposition of the theory of singular SPDEs.
In [IO19] the well-posedness of (1.2) for noise strength ๐ below a โ random โ threshold wasstudied based on Banachโs xed point argument. The ill-dened product ๐ข๐ 1๐2๐ข was treatedvia a more direct renormalization technique (in contrast to the more general one appearingin the framework of Regularity Structures), known as Wick renormalization. In fact, a similartechnique had been introduced by Da Prato and Debussche in their work [DD03] on the stochasticquantization equations of the P(๐)2-Euclidean Quantum Field theory.
One of the goals of this paper is to get rid of the smallness condition from [IO19]. Without lossof generality we may therefore assume that the parameter ๐ = 1, which we will always do in thefollowing.1 This means in particular that we have to give up the use of a xed point theorem onthe level of the Euler-Lagrange equation, and use instead the direct method of the calculus ofvariations on the level of the functional. The functional ๐ธ๐ก๐๐ก is in need of a renormalization. Thisis indicated by the fact that if ๐ฃ is the unique solution with zero average in ๐ฅ1 to the linearizedEulerโLagrange equation2
(โ๐21 โ |๐1 |โ1๐22)๐ฃ = ๐b, (1.3)which is explicit on the level of its Fourier transform, one has that ๐ธ๐ก๐๐ก (๐ฃ) = โโ almost surely,see Proposition C.1. As in [DD03] and [IO19], we decompose any admissible conguration ๐ข in(1.1) into ๐ข = ๐ฃ +๐ค , where the remainder๐ค is a periodic function with vanishing average in ๐ฅ1.
As is usual in renormalization, we may approximate white noise by a probability measure thatis supported on smooth b โs. This allows for a pathwise approach: For smooth (and periodic) b ,the solution ๐ฃ of (1.3) is smooth, too (see Lemma D.3). In view of the almost sure divergence of๐ธ๐ก๐๐ก (๐ฃ) in case of the white noise, we consider the renormalized functional
๐ธ๐๐๐ := ๐ธ๐ก๐๐ก (๐ฃ + ยท) โ ๐ธ๐ก๐๐ก (๐ฃ) . (1.4)
It follows from Lemma D.3 that for smooth b , ๐ธ๐๐๐ is well-dened (with values in R) on the space
W :={๐ค โ ๐ฟ2(T2) :
โซ 1
0๐ค d๐ฅ1 = 0 for every ๐ฅ2 โ [0, 1), H(๐ค) < โ
}, (1.5)
whereH denotes the harmonic energy, i.e., the quadratic part of ๐ธ๐ก๐๐ก given by
H(๐ค) :=โซT2(๐1๐ค)2 d๐ฅ +
โซT2( |๐1 |โ
12 ๐2๐ค)2 d๐ฅ . (1.6)
Loosely speaking, the task now is to show that ๐ธ๐๐๐ can still be given a sense as we approximatethe white noise. We will consider approximations that belong to the following class of probabilitymeasures:
Assumption 1.1. We consider the class of probability measures ใยทใ on the space of periodic Schwartzdistributions
3 b (endowed with the Schwartz topology), satisfying the following:
(i) ใยทใ is centered: ใbใ = 0, that is, ใ|b (๐) |ใ < โ and ใb (๐)ใ = 0 for all ๐ โ Cโ(T2).(ii) ใยทใ is stationary, that is, for every shift vector โ โ R2, b and b (ยท + โ) have the same law.
4
1Note however, that all our results also hold for ๐ โ 1 by considering ๐๐ฃ instead of ๐ฃ .2From now on, given b , we denote by ๐ฃ the unique solution with zero average in ๐ฅ1 to the linearized equation
L๐ฃ = ๐b from (1.3).3In our notation, we do not distinguish between the probability measure and its expectation, and use ใยทใ to denote
in particular the latter. In the probability jargon, b plays the role of a dummy variable like the popular ๐ . We prefer toadopt this point of view, but sometimes it is convenient to also think of b as a random variable taking values in the spaceof periodic Schwartz distributions by identifying it with the canonical evaluation b โฆโ ev(b), where ev(b) (๐) := b (๐)for all ๐ โ Cโ (T2). In our notation, when we refer to the law of b , we mean the law of the random variable ev orrather the probability measure ใยทใ.
4More precisely, for any test function ๐ โ Cโ (T2) and shift vector โ โ T2, b (๐) = b (๐ (ยท โ โ)) in law.
4 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
(iii) ใยทใ is invariant under reection in ๐ฅ1, that is, b and ๐ฅ โฆโ b (โ๐ฅ1, ๐ฅ2) have the same law.5
(iv) ใยทใ satises the spectral gap inequality (SGI), meaning that6
โจ|๐บ (b) โ ใ๐บ (b)ใ|2
โฉ 12 โค
โจ ๐๐b๐บ (b) 2๐ฟ2
โฉ 12
, (1.7)
for every functional๐บ on the space of Schwartz distribution such that ใ|๐บ (b) |ใ < โ and which
is well-approximated by cylindrical functionals. More precisely, for cylindrical functionals
๐บ (b) = ๐(b (๐1), . . . , b (๐๐)) with ๐ โ Cโ(R๐) which itself and all its derivatives have at
most polynomial growth, ๐1, . . . , ๐๐ โ Cโ(T2), and ๐ โ N we dene
๐
๐b๐บ (b) :=
๐โ๏ธ๐=1
๐๐๐(b (๐1), . . . , b (๐๐))๐๐
which is a random eld, and complete the space of all cylindrical functionals with respect to
the norm
โจ|๐บ (b) |2
โฉ 12 +
โจ ๐๐b๐บ (b)
2๐ฟ2
โฉ 12, which can be identied with a subspace of ๐ฟ2ใยทใ for
which (1.7) is well-dened. 7
Remark 1.2. Note that the white noise as well as any Gaussian probability measure with aCameronโMartin space that is weaker than ๐ฟ2(T2) satisfy the spectral gap inequality (1.7), (see[Hel98, Theorem 2.1]). In particular, if we convolve white noise with a smooth mollier, theresulting random eld satises (1.7).
Remark 1.3. For a linear functional ๐บ , i.e. ๐บ of the form ๐บ (b) = b (๐), for some ๐ โ Cโ(T2),the spectral gap inequality (1.7) turns into ใb (๐)2ใ โค
โซ๐2 d๐ฅ , which is a dening property of
white noise turned into an inequality. Note that this allows us to extend b (๐) to ๐ โ ๐ฟ2(T2) asa centered random variable in ๐ฟ2ใยทใ which is admissible in (1.7). In our application, the spectralgap inequality implies that ใยทใ gives full measure to the Hรถlder space Cโ 5
4โ (see Proposition 1.8below), which is the same as the regularity of white noise.
The merit of SGI is that it also applies to nonlinear ๐บ (in this paper, we need it for quadratic๐บ)8. In addition, it allows us to obtain sharp stochastic estimates for non-Gaussian measures byproviding a substitute for Nelsonโs hyper-contractivity.
The second, and more subtle, goal of this paper, is to establish universality of the ripple. Bythis we mean that the limiting law of the renormalized energy functional ๐ธ๐๐๐ is independentof the way white noise is approximated, provided the natural symmetry condition in form ofAssumption 1.1 (iii), is satised. In view of its physical origin, ใยทใ derives from the randomorientation of the grains. Such a model could be based on random tessellations, which suggestsa modelling through a non-Gaussian process.9 This motivates our interest in non-Gaussianapproximations of white noise. Our substitute for Gaussian calculus is the spectral gap inequality10(1.7), see Assumption 1.1 (iv).
5That is, for any test function ๐ โ Cโ (T2), denoting ๐ (๐ฅ) = ๐ (โ๐ฅ1, ๐ฅ2), there holds b (๐) = b (๐) in law. We notethat for our results to hold one could also ask for invariance under reection in ๐ฅ2.
6Without loss of generality we have set the constant equal to one.7Incidentally, for cylindrical functionals ๐บ we also have the relation ๐๐b ๐บ (b)
2๐ฟ2
= sup๐ฟb โ๐ฟ2 (T2)โ๐ฟb โ
๐ฟ2 โค1
lim inf๐กโ0
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๐บ (b + ๐ก๐ฟb) โ๐บ (b)๐ก
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ2 .8Actually, in order to obtain the ๐ฟ๐ version of SGI in Proposition 5.1 we need it for more general ๐บ , but the main
application concerns the quadratic functional in Lemma 5.5.9Incidentally, random tessellations based on Poisson point processes are known to satisfy a variant of the spectral
gap inequality, see [DG20].10In a Gaussian setting the right-hand side of (1.7) would correspond to having ๐ฟ2 as the CameronโMartin space.
VARIATIONAL METHODS FOR A SINGULAR SPDE 5
Since we cannot expect almost-sure uniqueness of the absolute minimizer ๐ค due to non-convexity of ๐ธ๐๐๐ , this universality is better expressed on the level of the variational problems๐ธ๐๐๐ themselves. Hence, rather than considering the (ill-dened) random elds ๐ค of minimalcongurations, we consider the random functionals ๐ธ๐๐๐ . The latter notion calls for a topology onthe space of variational problems, that is, of lower semicontinuous functionals ๐ธ onW (takingvalues in R โช {+โ}) that have compact sublevel sets (with respect to the strong ๐ฟ2-topology).The appropriate topology is the one generated by ฮ-convergence11; this is tautological sinceฮ-convergence of functionals in this topology is essentially equivalent to convergence of theminimizers, which do exist provided the functionals have compact sublevel sets (with respectto the strong ๐ฟ2-topology). Hence we are lead to consider probability measures on the space oflower semicontinuous functionals ๐ธ on W endowed with the topology of ฮ-convergence12. Fromthis point of view, the universality of the ripple takes the following form:
Theorem 1.4. Every probability measure ใยทใ on the space periodic Schwartz distributions b satisfyingDenition 1.1 extends to a probability measure ใยทใext on the product space of periodic Schwartz
distributions b in the Hรถlder space Cโ 54โ and lower semicontinuous functionals ๐ธ on W endowed
with the topology of ฮ-convergence with the following three properties:
(i) If b is smooth ใยทใ-almost surely, then ๐ธ = ๐ธ๐๐๐ (๐ฃ ; ยท) for ใยทใext-almost every (b, ๐ธ), where๐ฃ = Lโ1๐b and ๐ธ๐๐๐ (๐ฃ ; ยท) is given by (1.4).
(ii) If a sequence {ใยทใโ }โโ0 of probability measures that satisfy Assumption 1.1 converges weakly
to ใยทใ (which automatically satises Assumption 1.1), then {ใยทใextโ }โโ0 converges weakly to
ใยทใext.
Remark 1.5. Let us explain why Theorem 1.4 expresses the desired universality of the ripple. Weare given a sequence {ใยทใโ }โโ0 which converges weakly to white noise ใยทใ, such that ใยทใโ satisesAssumption 1.1, and such that for โ > 0, b is smooth ใยทใโ -almost surely. In view of Theorem 1.4 (i),as long as โ > 0, the pathwise dened ๐ธ๐๐๐ , see (1.4), can be identied with the random functional๐ธ associated to ใยทใextโ . According to Theorem 1.4 (ii), as โ โ 0, the law of (b, ๐ธ๐๐๐) under ใยทใextโ
converges weakly to ใยทใext associated to the law of white noise ใยทใ.
As a corollary of our results we have the following stronger statement.
Corollary 1.6. Assume that the probability measure ใยทใ satises Assumption 1.1 and consider its
extension ใยทใext to the product space of periodic Schwartz distributions b in the Hรถlder space Cโ 54โ
and lower semicontinuous functionals ๐ธ onW endowed with the topology of ฮ-convergence. Thenminimizers of ๐ธ exist in W for ใยทใext-almost every (b, ๐ธ). Moreover, for every 1 โค ๐ < โ, the
following estimate holds,13 โจ
inf๐คโargmin๐ธ
[๐ค]๐54โ
โฉextโค ๐ถ, (1.8)
for a constant ๐ถ that only depends on ๐ , uniformly in the class of probability measures ใยทใ satisfyingAssumption 1.1.
Remark 1.7. Since under ใยทใext functionals ๐ธ are non-convex (see the discussion below Propo-sition 1.10) we do not expect uniqueness of minimizers. In that sense, Corollary 1.6 shows theexistence of minimizers๐ค โ W with nite C 5
4โ-norm. However, we do not know if all minimizershave this regularity.14 The C 5
4โ-regularity in (1.8) relies on the EulerโLagrange equation (1.13)(see the discussion below Proposition 1.10). If minimizers were unique, the uniformity of (1.8) inthe class of probability measures satisfying Assumption 1.1 and tightness would imply that if a
11Based on the strong ๐ฟ2-topology.12Recall that the space of lower semicontinuous functionals ๐ธ : W โ R โช {+โ} is a compact space, see [Dal93,
Theorem 8.5 and Theorem 10.6].13Note that the inf in (1.8) is +โ if argmin๐ธ = โ .14We have no reason to assume that this is not the case.
6 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
sequence {ใยทใโ }โโ0 satisfying Assumption 1.1 converges weakly to ใยทใ, then the law of the uniqueminimizer under ใยทใextโ converges weakly to the law of the unique minimizer under ใยทใext.
In establishing Theorem 1.4, we follow very much the spirit of rough path theory of a clear sep-aration between a stochastic and a deterministic (pathwise) ingredient. The genuinely stochasticingredient is formulated in Proposition 1.8, where we extend the probability distribution of b โsto a (joint) law of (b, ๐ฃ, ๐น ). Compared to rough paths, ๐ฃ is the analogue of (multi-dimensional)Brownian motion ๐ต, and ๐น similar to the iterated โintegrandโ15 ๐ต ๐๐ต
๐๐ก, see Proposition 1.8 (iii),
which relates ๐น to ๐ฃ๐ 1๐2๐ฃ . The degree of indeterminacy reected by the dierence betweenStratonovich (midpoint rule) and Itรด (explicit) is suppressed by the symmetry condition in As-sumption 1.1 (iii), which feeds into the characterizing property given by (1.9). The crucial stabilityof this construction is provided by Proposition 1.8 (iv).
Like for rough paths this unfolding into several random building blocks allows for a pathwisesolution theory, i.e. the construction of a continuous solution map on this augmented space. Inour variational case this turns into a continuous map from the space of (b, ๐ฃ, ๐น )โs into the space offunctionals, with the above-advertised topology of ฮ-convergence, see Proposition 1.10).
Proposition 1.8. Every probability measure ใยทใ satisfying Assumption 1.1 is concentrated on the
Hรถlder space Cโ 54โ and lifts to a probability measure ใยทใli on the space of triples (b, ๐ฃ, ๐น ) in Cโ 5
4โ รC 3
4โ ร Cโ 34โ with the following properties:
(i) The law of b under ใยทใli is ใยทใ.(ii) ๐ฃ = Lโ1๐b ใยทใli-almost surely.
(iii) The law of ๐น under ใยทใli is characterized by
lim๐ก=2โ๐โ0
โจ[๐น โ ๐ฃ๐ 1๐2๐ฃ๐ก ]๐โ 3
4โ
โฉli= 0, (1.9)
for every 1 โค ๐ < โ. Moreover, if b is smooth ใยทใ-almost surely, we have that ๐น = ๐ฃ๐ 1๐2๐ฃใยทใli-almost surely.
(iv) Finally, if a sequence {ใยทใโ }โโ0 of probability measures that satisfy Assumption 1.1 converges
weakly to a probability measure ใยทใ, then also {ใยทใliโ }โโ0 converges weakly to ใยทใli.
Remark 1.9. Let us point out that (1.9) implies that ๐น is actually a ใยทใ-measurable function of b .Indeed, by (i), (ii), and the triangle inequality for ๐ , ๐ก โ (0, 1] dyadic we haveโจ
[๐ฃ๐ 1๐2๐ฃ๐ โ ๐ฃ๐ 1๐2๐ฃ๐ก ]๐โ 34โ
โฉ 1๐
=
(โจ[๐ฃ๐ 1๐2๐ฃ๐ โ ๐ฃ๐ 1๐2๐ฃ๐ก ]๐โ 3
4โ
โฉli) 1๐
โค(โจ[๐น โ ๐ฃ๐ 1๐2๐ฃ๐ ]๐โ 3
4โ
โฉli) 1๐
+(โจ[๐น โ ๐ฃ๐ 1๐2๐ฃ๐ก ]๐โ 3
4โ
โฉli) 1๐
,
which in turn implies that the sequence {๐ฃ๐ 1๐2๐ฃ๐ก }๐กโ0 is Cauchy in ๐ฟ๐ใยทใCโ 3
4โ. Hence it convergesto a random variable ๐น (b) โ ๐ฟ๐ใยทใC
โ 34โ and it is easy to check that ๐น = ๐น (b) ใยทใli-almost surely.
This allows us to identify the lift measure ใยทใli as the joint law of (b,Lโ1๐b, ๐น (b)) under ใยทใ.
The main idea of the deterministic ingredient, Proposition 1.10, is to extend the denition (1.4)of ๐ธ๐๐๐ from only depending on (b, ๐ฃ)16 to depending on (b, ๐ฃ, ๐น ), in such a way that the denitions
15As opposed to its integralโซ๐ต d๐ต, which is called the iterated integral. We refer to [FH14, Chapter 3] for details.
16That is, eectively only on b . Since ๐ธ๐๐๐ no longer depends explicitly on b , we drop b in the notation for ๐ธ๐๐๐ .
VARIATIONAL METHODS FOR A SINGULAR SPDE 7
(formally) coincide for ๐น = ๐ฃ๐ 1๐2๐ฃ . This is achieved by17
๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) := E(๐ค) + G(๐ฃ, ๐น ;๐ค), (1.10)where the anharmonic energy E is given by the rst two contributions of ๐ธ๐ก๐๐ก ,
E(๐ค) :=โซT2(๐1๐ค)2 d๐ฅ +
โซT2
(|๐1 |โ
12 (๐2๐ค โ ๐1 12๐ค
2))2
d๐ฅ . (1.11)
Note that E contains the Burgers nonlinearity [๐ค := ๐2๐ค โ ๐1 12๐ค2, which will play an important
role in our analysis. Only the remainder G depends on ๐ฃ and ๐น , and is given by
G(๐ฃ, ๐น ;๐ค) :=โซT2
(๐ค2๐ 1๐2๐ฃ + ๐ฃ2๐ 1[๐ค + 2๐ฃ๐ค๐ 1[๐ค + 2๐ค๐น โ๐ค๐ฃ๐ 1๐1๐ฃ2 + (๐ 1 |๐1 |
12 (๐ฃ๐ค))2
)d๐ฅ .(1.12)
Equipped with these denitions, we now may state the main deterministic ingredient.
Proposition 1.10. The application (b, ๐ฃ, ๐น ) โฆโ ๐ธ๐๐๐ described through (1.10) is well-dened and
continuous when the space of (b, ๐ฃ, ๐น ) is endowed with the norm Cโ 54โรC 3
4โรCโ 34โ and the space of
lower semicontinuous functionals ๐ธ๐๐๐ on W is endowed with the topology of ฮ-convergence (basedon the ๐ฟ2-topology).
ใยทใ โผ b
ใยทใli โผ (b, ๐ฃ, ๐น ) ใยทใext โผ (b, ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท))
Figure 1. Construction of the extension measure ใยทใext. The vertical arrowcorresponds to the probabilistic step, Proposition 1.8, while the horizontal arrowis the deterministic step, Proposition 1.10. For smooth b โs ๐น is given by ๐ฃ๐ 1๐2๐ฃ .
On the level of the EulerโLagrange equation, minimizers๐ค of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) are weak solutionsof
L๐ค + ๐(๐น +๐ค๐ 1๐2๐ฃ + ๐ฃ๐ 1๐2๐ค +๐ค๐ 1๐2๐ค โ 1
2 (๐ฃ +๐ค)๐ 1๐1(๐ฃ +๐ค)2)
+ 12๐ 1๐2(๐ฃ +๐ค)2 = 0,
(1.13)
whose existence is established by Theorem 1.4 (see also Theorem 1.14 (iv) for the validity of (1.13)in the sense of Schwartz distributions). By a simple power counting the expected regularity ofsolutions ๐ค to (1.13) is 5
4โ, which justies the existence of minimizers ๐ค โ W with nite C 54โ
norm proved in Corollary 1.6. This generalizes the existence of solutions to (1.13) in [IO19] whichwas shown for small values of the noise strength |๐ |.
From a variational point of view, the main challenge is to establish the coercivity of therenormalized energy ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท). Ideally, one would like to control the remainder G(๐ฃ, ๐น ; ยท) bythe โgoodโ term of the renormalized energy, namely, the anharmonic energy E(๐ค) given in (1.11).At rst sight, this is not obvious since the remainder G(๐ฃ, ๐น ; ยท) contains quadratic and cubic terms
17This can be seen by the identity [๐ข = [๐ฃ + [๐ค โ ๐1 (๐ฃ๐ค) for the Burgers operator [๐ข = ๐2๐ข โ ๐1 12๐ข2, as well as the
equality โซT2
(๐1๐ค ๐1๐ฃ + ๐2๐ค |๐1 |โ1๐2๐ฃ โ๐ค b
)d๐ฅ = 0,
which follows from testing (1.3) with๐ค .
8 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
in๐ค , and it is not immediate that the anharmonic energy E(๐ค) provides higher than quadraticcontrol to absorb these terms. Hence, we need to exploit the control on the nonlinear part comingfrom the Burgers operator [๐ค .18 We do this using tools from uid mechanics, more precisely, theHowarthโKรกrmรกnโMonin identities (2.5) and (2.6), following [GJO15]. Based on these identitieswe can prove that the anharmonic energy E(๐ค) grows cubically in suitable Besov spaces (seeProposition 2.4). This allows us to absorb G(๐ฃ, ๐น ; ยท) and obtain the coercivity of the renormalizedenergy (see Theorem 1.14 (i)).
Let us point out that here, we prove existence of solutions for any value of the noise strength๐ using the coercivity of the renormalized energy functional through the direct method of thecalculus of variations. Recent works on the dynamic ฮฆ4 model (or stochastic GinzburgโLandaumodel), where the system is favoured by the โgoodโ sign of the cubic nonlinearity, have usedcoercivity on the level of the EulerโLagrange equation. For example, in [MW17a, TW18, MW17b]energy estimates have been used to obtain global-in-time existence in the parabolic case, while in[GH19] both the parabolic and the elliptic cases have been treated based on a dierent approachthat uses coercivity through a maximum principle. A maximum principle has been used also in[CMW19] where the parabolic model is considered in the full subcritical regime.
A further challenge, which turns out to be more on the technical side, comes from the factthat L is nonlocal. We recall that this feature arises completely naturally from the magnetostaticenergy in the thin-lm limit (see [IO19, Section 2]), but resonates well with the recent surge inactivity on nonlocal operators. It was worked out in [IO19, Lemma 5] that the robust approach of[OW19] to negative (parabolic) Hรถlder spaces and Schauder theory extends to this situation. Thisapproach involves a suitable convolution semigroup๐๐ก ; the fact that it extends from the smoothparabolic symbol ๐21 + ๐๐2 to our nonsmooth symbol ๐21 + |๐1 |โ1๐22 is not obvious due to the poordecay properties of the corresponding convolution kernel.
Variational problems that in a singular limit require subtraction of a divergent term are well-known in deterministic settings. A famous example concerns S1-valued harmonic maps denedin a two-dimensional smooth bounded simply-connected domain ๐ท . The aim there is to minimizethe Dirichlet energy of maps ๐ข : ๐ท โ S1 that satisfy a smooth boundary condition ๐ : ๐๐ท โ S1.When ๐ carries a nontrivial winding number ๐ > 019, the problem is singular, that is, everyconguration ๐ข has innite energy as they generate vortex point singularities. The question isto determine the least โinniteโ Dirichlet energy of a harmonic S1-valued map satisfying theboundary condition ๐ on ๐๐ท . The seminal book of BethuelโBrezisโHรฉlein [BBH94] presentstwo methods to achieve this goal, both reaching the same renormalized energy associated to theproblem.
First approach: One prescribes ๐ > 0 vortex points ๐1, . . . , ๐๐ in ๐ท and determines theunique harmonic S1-valued map ๐ขโ with ๐ขโ = ๐ on ๐๐ท that has the prescribed singularities๐1, . . . , ๐๐ in ๐ท , each one carrying a winding number equal to one20. Then one cuts-odisks ๐ต(๐๐ , ๐ ) centered at ๐๐ of small radius ๐ > 0 carrying the diverging logarithmicenergy of ๐ขโ and introduces the renormalized energy
๐ (๐1, . . . , ๐๐ ) = lim๐โ0
(โซ๐ท\โช๐๐ต (๐๐ ,๐ )
|โ๐ขโ(๐ฅ) |2 d๐ฅ โ 2๐๐ log 1๐
).
18Incidentally, despite dierent physical origins, the inviscid Burgers part [๐ค arises as in the KPZ equation fromexpanding a square root nonlinearity. Not unlike there, the coercivity comes from the interaction between the rstand second term in E(๐ค), the rst term being the analogue to the viscocity in KPZ.
19For simplicity, we assume ๐ > 0; the case ๐ < 0 follows by complex conjugation.20In fact, ๐ขโ belongs to the Sobolev space๐ 1,1 (๐ท, S1) and the nonlinear PDE satised by ๐ขโ, i.e., โฮ๐ขโ = |โ๐ขโ |2๐ขโ
in ๐ท , can be written in a โlinearโ way in terms of the current ๐ (๐ขโ) = ๐ขโ ร โ๐ขโ โ ๐ฟ1 (๐ท) of ๐ขโ that satises the systemโ ร ๐ (๐ขโ) = 2๐
โ๐ ๐ฟ๐๐ in ๐ท , and โ ยท ๐ (๐ขโ) = 0 in ๐ท . In terms of the so-called conjugate harmonic function ๐ given by
โโฅ๐ = ๐ (๐ขโ), the problem becomes โฮ๐ = 2๐โ๐ ๐ฟ๐๐ in ๐ท and ๐a๐ = ๐ ร ๐๐๐ on ๐๐ท . One could think of ๐ as playing
the role of our solution ๐ฃ to the linearized Euler-Lagrange equation (1.3) that carries the โinniteโ part of the energy.
VARIATIONAL METHODS FOR A SINGULAR SPDE 9
The minimum of the renormalized energymin
๐1,...๐๐ โ๐ท๐ (๐1, . . . , ๐๐ ) (1.14)
represents the minimal second order term in the expansion of the Dirichlet energy andyields optimal positions of the ๐ vortex point singularities (which might not be unique ingeneral).Second approach: One considers a nonlinear approximation of the harmonicmap problemgiven by the Ginzburg-Landau model for a small parameter Y > 0:
๐ธY (๐ข) =โซ๐ท
|โ๐ข |2 + 1Y2(1 โ |๐ข |2)2 d๐ฅ, ๐ข : ๐ท โ R2, ๐ข = ๐ on ๐๐ท.
Note that the maps ๐ข are no longer with values into S1, but their distance to S1 is stronglypenalized as Y โ 0. It is proved in [BBH94, Theorem X.1] that if ๐ขY is a minimizer of theabove GinzburgโLandau problem, then for a subsequence, ๐ขY โ ๐ขโ weakly in๐ 1,1(๐ท) asY โ 0 where ๐ขโ is an S1 valued harmonic map whose ๐ vortex points of winding numberone correspond to a minimizer of the renormalized energy (1.14). Moreover,
๐ธY (๐ขY) = 2๐๐ log 1Y+ min
๐1,...๐๐ โ๐ท๐ (๐1, . . . , ๐๐ ) + ๐๐พ + ๐ (1), as Y โ 0,
where ๐พ is a constant coming from the nonlinear penalization in ๐ธY .We also refer to [SS07, SS15], [Kur06], [IM16], and [IJ19] for similar renormalized energies.
1.1. Notation. For a periodic function ๐ : T2 โ R we dene its Fourier coecients by
๐ (๐) =โซT2๐โi๐ ยท๐ฅ ๐ (๐ฅ) d๐ฅ for ๐ โ (2๐Z)2,
which extends to periodic Schwartz distributions in the natural way. We also denote by ๐ the๐ฟ2-orthogonal projection onto the set of functions of vanishing average in ๐ฅ1, extended in thenatural way to periodic Schwartz distributions.
For ๐ โ [1,โ] we write โ ยท โ๐ฟ๐ to denote the usual ๐ฟ๐ norm on T2, unless indicated otherwise.For example, we write โ ยท โ๐ฟ๐ (R2) for the ๐ฟ๐ norm of a function dened on R2. We sometimeswrite ๐ฟ๐๐ฅ (respectively ๐ฟ๐๐ฅ ๐
, ๐ = 1, 2) to denote the ๐ฟ๐ space with respect to the ๐ฅ (respectively ๐ฅ ๐ )variable. We also write ๐ฟ๐ใยทใ to denote the usual ๐ฟ๐ space with respect to the measure ใยทใ.
We will often make use of the notation ๐ . ๐ meaning that there exists a constant ๐ถ > 0 suchthat ๐ โค ๐ถ๐. Moreover, for ^ โ R, the notation .^ will be used to stress the dependence of theimplicit constant ๐ถ on ^, i.e., ๐ถ โก ๐ถ (^). Similarly, ๐ โผ ๐ means ๐ . ๐ and ๐ . ๐.
1.1.1. Hilbert transform. We will frequently make use of the Hilbert transform ๐ ๐ for ๐ = 1, 2, actingon periodic functions ๐ : T2 โ R in ๐ฅ ๐ as
๐ ๐ :=๐๐
|๐๐ |, i.e., ๐ ๐ ๐ (๐) =
{i sgn(๐ ๐ ) ๐ (๐) if ๐ ๐ โ 2๐Z \ {0},0 if ๐ ๐ = 0,
(1.15)
where sgn is the sign function. In particular, ๐ ๐๐ = ๐๐ ๐ = ๐ ๐ .
1.1.2. Anisotropic metric and kernel. The leading-order operator L = โ๐21 โ |๐1 |โ1๐22 suggests toendow the space T2 with a CarnotโCarathรฉodory metric that is homogeneous with respect to thescaling (๐ฅ1, ๐ฅ2) = (โ๐ฅ1, โ
32๐ฅ2). The simplest expression is given by
๐ (๐ฅ,๐ฆ) := |๐ฅ1 โ ๐ฆ1 | + |๐ฅ2 โ ๐ฆ2 |23 , ๐ฅ,๐ฆ โ T2,
which in particular means that we take the ๐ฅ1 variable as a reference.We now introduce the convolution semigroup used in [IO19]. This is the โheat kernelโ {๐๐ }๐>0
of the operatorA := |๐1 |3 โ ๐22 = |๐1 |L,
10 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
which, in Fourier space R2, is given by
๐๐ (๐) = exp(โ๐ ( |๐1 |3 + ๐22)), for all ๐ โ R2. (1.16)
It is easy to check that the kernel has scaling properties in line with the metric ๐ , that is,
๐๐ (๐ฅ1, ๐ฅ2) =1
(๐ 13 )1+ 3
2๐
(๐ฅ1
๐13,๐ฅ2
(๐ 13 ) 3
2
), for all ๐ฅ โ R2, (1.17)
where for simplicity we write๐ := ๐1. Note that๐ is a symmetric smooth function with integrablederivatives and we have for every ๐ โ [1,โ] (see [IO19, Proof of Lemma 10]),
โ๐ท๐ผ1๐ท
๐ฝ
2๐๐ โ๐ฟ๐ (R2) โผ (๐ 13 )โ๐ผโ
32 ๐ฝโ
52 (1โ
1๐), (1.18)
for every ๐ > 0, ๐ท ๐ โ {๐๐ , |๐๐ |}, ๐ = 1, 2, and ๐ผ, ๐ฝ โฅ 0. For a periodic Schwartz distribution ๐ , wedenote by ๐๐ its convolution with๐๐ , i.e., ๐๐ = ๐๐ โ ๐ , which yields a smooth periodic function.Notice that {๐๐ }๐>0 is a convolution semigroup, so that
(๐๐ก )๐ = ๐๐ก+๐ for all ๐ก,๐ > 0.
Remark 1.11. By the space of periodic Schwartz distributions ๐ we understand the (topologi-cal) dual of the space of Cโ-functions ๐ on the torus (endowed with the family of seminorms{โ๐ ๐1๐๐2๐ โ๐ฟโ} ๐,๐โฅ0).
For a Cโ-function ๐ on R2 with integrable derivatives, i.e.โซR2
|๐ ๐1๐๐2๐ | d๐ฅ < โ for all ๐, ๐ โฅ0, and a periodic Schwartz distribution ๐ we write (๐ โ ๐ ) (๐ฅ) to denote ๐ (ฮจ(๐ฅ โ ยท)), whereฮจ :=
โ๐งโZ2 ๐ (ยท โ ๐ง) is the periodization of ๐ , which is well-dened and belongs to Cโ(T2). In
particular, if ฮจ๐ denotes the periodization of our โheat kernelโ๐๐ , then ฮจ๐ is a smooth semigroupwhose Fourier coecients are given by๐๐ (๐) in (1.16) for ๐ โ (2๐Z)2, yielding for any ๐ โ (0, 1],๐ท ๐ โ {๐๐ , |๐๐ |}, ๐ = 1, 2, and ๐ผ, ๐ฝ โฅ 0: 21
โ๐ท๐ผ1๐ท
๐ฝ
2ฮจ๐ โ๐ฟ๐ . โ๐ท๐ผ1๐ท
๐ฝ
2๐๐ โ๐ฟ๐ (R2)(1.18). (๐ 1
3 )โ๐ผโ32 ๐ฝโ
52 (1โ
1๐). (1.19)
Therefore, for a periodic function ๐ โ ๐ฟ๐ , we will often use Youngโs inequality for convolutionwith 1 + 1
๐= 1
๐+ 1
๐in the form
โ ๐ โ ๐ท๐ผ1๐ท
๐ฝ
2๐๐ โ๐ฟ๐ โค โ ๐ โ๐ฟ๐ โ๐ท๐ผ1๐ท
๐ฝ
2ฮจ๐ โ๐ฟ๐ . (๐ 13 )โ๐ผโ
32 ๐ฝโ
52 (1โ
1๐) โ ๐ โ๐ฟ๐ .
We sometimes write ฮ for the integral kernel of Lโ1๐ , given by
ฮฬ(๐) = 1๐21 + |๐1 |โ1๐22
, for ๐1 โ 0. (1.20)
Note that
โฮโ2๐ฟ2 =
โ๏ธ๐1โ 0
1(๐21 + |๐1 |โ1๐22)2
โคโ๏ธ๐1โ 0
1๐ (0, ๐)4 < โ. (1.21)
21Indeed, for ๐ = 1, we have
โ๐ท๐ผ1 ๐ท
๐ฝ
2 ฮจ๐ โ๐ฟ1 โค โ๐งโZ2
โซT2 |๐ท
๐ผ1 ๐ท
๐ฝ
2๐๐ (๐ฅ โ ๐ง) | d๐ฅ = โ๐ท๐ผ1 ๐ท
๐ฝ
2๐๐ โ๐ฟ1 (R2) ,
while for ๐ = โ,
โ๐ท๐ผ1 ๐ท
๐ฝ
2 ฮจ๐ โ๐ฟโ โค 1 + โ๐โ(2๐Z)2\{(0,0) } |๐1 |๐ผ |๐2 |๐ฝ |๐๐ (๐) | . 1 +
โซR2 |b1 |
๐ผ |b2 |๐ฝ exp(โ๐ ( |b1 |3 + b22)) db
. (๐13 )โ๐ผโ
32 ๐ฝโ
52(1.18). โ๐ท๐ผ
1 ๐ท๐ฝ
2๐๐ โ๐ฟโ (R2) .
For ๐ โ (1,โ), one argues by interpolation.
VARIATIONAL METHODS FOR A SINGULAR SPDE 11
1.1.3. Denition of Hรถlder spaces. We now introduce the scale of Hรถlder seminorms based on thedistance function ๐ , where we restrict ourselves to the range ๐ผ โ (0, 32 ) needed in this work (see[IO19, Denition 1]).
Denition 1.12. For a function ๐ : T2 โ R and ๐ผ โ (0, 32 ), we dene
[๐ ]๐ผ :=sup๐ฅโ ๐ฆ
|๐ (๐ฆ)โ๐ (๐ฅ) |๐๐ผ (๐ฆ,๐ฅ) for ๐ผ โ (0, 1],
sup๐ฅโ ๐ฆ|๐ (๐ฆ)โ๐ (๐ฅ)โ๐1 ๐ (๐ฅ) (๐ฆโ๐ฅ)1 |
๐๐ผ (๐ฆ,๐ฅ) for ๐ผ โ (1, 32 ) .
We denote by C๐ผ the closure of periodic Cโ-functions ๐ : T2 โ R with respect to [๐ ]๐ผ .
We will also need the following Hรถlder spaces of negative exponents. We will restrict to therange required in this work, namely ๐ฝ โ (โ 3
2 , 0) (see [IO19, Denition 3]).
Denition 1.13. Let ๐ be a periodic Schwartz distribution on T2. For ๐ฝ โ (โ1, 0) we dene[๐ ]๐ฝ := inf{|๐ | + [๐]๐ฝ+1 + [โ]๐ฝ+ 3
2: ๐ = ๐ + ๐1๐ + ๐2โ}
and for ๐ฝ โ (โ 32 ,โ1] we dene
[๐ ]๐ฝ := inf{|๐ | + [๐]๐ฝ+2 + [โ]๐ฝ+ 32: ๐ = ๐ + ๐21๐ + ๐2โ}.
We denote by C๐ฝ the closure of periodic Cโ-functions ๐ : T2 โ R with respect to [๐ ]๐ฝ .
In Appendix A we provide all the necessary estimates on Hรถlder spaces needed in this work.
1.2. Strategy of the proofs. Recall the setW dened in (1.5), endowed with the strong topologyin ๐ฟ2(T2). We will show that the harmonic energyH(๐ค) dened in (1.6) controls the anharmonicpart E(๐ค) dened in (1.11) of the total energy, that is,
E(๐ค) . 1 + H (๐ค)2,for every๐ค โ W, and vice-versa, the anharmonic energy controls the harmonic part, that is, forevery ^ > 0 we have
H(๐ค) .^ 1 + E(๐ค) 32+^,
for any๐ค โ W, see Proposition 2.5 below. By standard embedding theorems (see Lemma B.5),any sublevel set ofH (respectively E) overW is relatively compact in ๐ฟ2 andH (respectively E)is lower semicontinuous with respect to the ๐ฟ2-norm (see (3.3)).
In the following, for Y > 0 suciently small, we will also write
T =
{(b, ๐ฃ, ๐น ) โ Cโ 5
4โY ร C 34โY ร Cโ 3
4โY : L๐ฃ = ๐b}.
Note that T is a closed subspace of Cโ 54โY ร C 3
4โY ร Cโ 34โY endowed with the product metric.
The deterministic ingredient in the proof of Theorem 1.4, that is Proposition 1.10, is essentiallya consequence of the following theorem.
Theorem 1.14.(i) (Coercivity) For every _ โ (0, 1) and ๐ > 0, there exists a constant ๐ถ > 0 which depends
on _ and polynomially on๐ 22such that for every Y โ (0, 1
100 ) and every (b, ๐ฃ, ๐น ) โ T with
[b]โ 54โY, [๐ฃ] 3
4โY, [๐น ]โ 3
4โYโค ๐ , the functional G dened in (1.12) satises
|G(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ, for every๐ค โ W .
In particular, ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) dened in (1.4) is coercive.(ii) (Continuity) Let Y โ (0, 1
100 ) and (bโ , ๐ฃโ , ๐นโ ) โ (b, ๐ฃ, ๐น ) in T and ๐คโ โ ๐ค in W with the
property that lim supโโ0 E(๐คโ ) < โ. Then
G(๐ฃโ , ๐นโ ;๐คโ ) โ G(๐ฃ, ๐น ;๐ค) as โ โ 0.22We say that a constant๐ถ > 0 depends polynomially on๐ if there exist ๐ > 0 and ๐ โฅ 1 such that๐ถ โค ๐ (1+๐๐ ).
12 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
(iii) (Compactness) Let Y โ (0, 1100 ) and (b, ๐ฃ, ๐น ) โ T be xed. Then for any๐ โ R the sublevel
sets of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) dened in (1.10), given by{๐ค โ ๐ฟ2 :
โซ 1
0๐ค d๐ฅ1 = 0, ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) โค ๐
},
are compact in the ๐ฟ2-norm.
(iv) (Existence of minimizers) If Y โ (0, 1100 ) and (b, ๐ฃ, ๐น ) โ T , then there exists a minimizer
๐ค โ W of the renormalized energy ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) which is a weak solution of (1.13).
Note that ๐ธ๐๐๐ (๐ฃ, ๐น ; 0) = 0, therefore every minimizer of ๐ธ๐๐๐ belongs to the sublevel set๐ = 0of ๐ธ๐๐๐ . Using Theorem 1.14, we obtain the following ฮ-convergence result.
Corollary 1.15 (ฮ-convergence). Let Y โ (0, 1100 ) and (bโ , ๐ฃโ , ๐นโ ) โ (b, ๐ฃ, ๐น ) in T . Then
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค) โ ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) for every ๐ค โ W as โ โ 0.Also, ๐ธ๐๐๐ (๐ฃโ , ๐นโ ; ยท) โ ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) in the sense of ฮ-convergence over W, that is,
(i) (ฮ โ lim inf) For all sequences {๐คโ }โโ0 โ W with๐คโ โ ๐ค strongly in ๐ฟ2, we have
lim infโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐คโ ) โฅ ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) .
(ii) (ฮโ lim sup) For every๐ค โ W, there exists a sequence {๐คโ }โโ0 โ W with๐คโ โ ๐ค strongly
in ๐ฟ2 such that
limโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐คโ ) = ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) .
Proof of Proposition 1.10. Corollary 1.15 establishes the continuity of the map that associates to each(b, ๐ฃ, ๐น ) โ T the functional ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), when the space of (lower semicontinuous) functionals isequipped with the topology of ฮ-convergence (based on the ๐ฟ2-topology). In particular, this mapis Borel measurable when T is endowed with its Borel ๐-algebra. ๏ฟฝ
Taking the main stochastic ingredient from Proposition 1.8 for granted (which we prove inSection 5), we can now give the proof of Theorem 1.4.
Proof of Theorem 1.4. Let ใยทใ be a probability measure on the space of periodic Schwartz distribu-tions b that satises Assumption 1.1. By Proposition 1.8 ใยทใ lifts to a probability measure ใยทใli onthe space of triples (b, ๐ฃ, ๐น ) โ Cโ 5
4โ ร C 34โ ร Cโ 3
4โ.By Proposition 1.10 the mapping (b, ๐ฃ, ๐น ) โฆโ ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) is continuous. Hence, the push-
forward ๐ธ๐๐๐#ใยทใli is well-dened as a probability measure on the space of lower semicontinuousfunctionals equipped with the Borel ๐-algebra corresponding to the topology of ฮ-convergence(based on the strong ๐ฟ2-topology). We now dene ใยทใext as the joint law of b and ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท).23
(i) If b is smooth ใยทใ-almost surely, by Proposition 1.8 (iii) we have that ๐น = ๐ฃ๐2๐ 1๐ฃ ใยทใ-almostsurely. In this case, ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) = ๐ธ๐๐๐ (๐ฃ, ๐ฃ๐2๐ 1๐ฃ ; ยท) ใยทใ-almost surely and agrees with thedenition given in (1.4).
(ii) Let {ใยทใโ }โโ0 be a sequence of probability measures that satisfy Assumption 1.1 and con-verges weakly to ใยทใ, which then automatically satises Assumption 1.1. Then by Proposi-tion 1.8 (iv), the sequence {ใยทใliโ }โโ0 converges weakly to ใยทใli. Given a bounded continuousfunction ๐บ : (b, ๐ธ) โฆโ ๐บ (b, ๐ธ) โ R we have that
ใ๐บใextโ = ใ๐บ (b, ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท))ใliโโโ0โโ ใ๐บ (b, ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท))ใli = ใ๐บใext,
which in turn implies that ใยทใextโ โ ใยทใext weakly as โ โ 0. ๏ฟฝ
Finally, we have an a priori estimate for the C 54โ norm of minimizers of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), which we
prove in Section 4.23Here we understand ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) as a measurable function of b , which is a composition of the measurable function
b โฆโ (b, ๐ฃ, ๐น ) and the continuous function (b, ๐ฃ, ๐น ) โฆโ ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท).
VARIATIONAL METHODS FOR A SINGULAR SPDE 13
Proposition 1.16 (Hรถlder regularity). For any๐ > 0 and Y โ (0, 1100 ), there exists a constant๐ถ > 0
which depends on Y and polynomially on๐ such that
[๐ค] 54โ2Y
โค ๐ถ,
for every minimizer ๐ค โ W โฉ C 54โ2๐ of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) with (b, ๐ฃ, ๐น ) โ T satisfying the bound
[b]โ 54โY, [๐ฃ] 3
4โY, [๐น ]โ 3
4โYโค ๐ .
Combined with an approximation argument, this is the main ingredient in the proof of Corol-lary 1.6, which we give now.
Proof of Corollary 1.6. We dene the functional ๐ : W โ R โช {+โ} given by
๐(๐ค) :={[๐ค] 5
4โ2Y, if ๐ค โ C 5
4โ2Y,
+โ, otherwise.
By [IO19, Lemma 13] we know that ๐ is lower semicontinuous onW endowed with the strongtopology in ๐ฟ2(T2). We dene the non-negative functional ๐บ : ๐ธ โฆโ ๐บ (๐ธ) on the space of lowersemicontinuous functionals ๐ธ onW by
๐บ (๐ธ) := inf๐คโargmin๐ธ
๐(๐ค), if argmin๐ธ โ โ ,
+โ, otherwise.
We claim that๐บ is lower semicontinuous, that is, if ๐ธโ โ ๐ธ as โ โ 0 in the sense of ฮ-convergence,then
๐บ (๐ธ) โค lim infโโ0
๐บ (๐ธโ ) .
Indeed, without loss of generality we may assume that๐บ (๐ธโ ) โ lim inf โโ0๐บ (๐ธโ ) < โ by possiblyextracting a subsequence. This implies that supโโ(0,1] ๐บ (๐ธโ ) < โ, hence by the denition of ๐บthere exists a sequence of minimizers๐คโ of ๐ธโ such that
[๐คโ ] 54โ2Y
โค ๐บ (๐ธโ ) + โ โค supโโ(0,1]
๐บ (๐ธโ ) + 1.
By Lemma A.6 there exists๐ค โ C 54โ2Y such that๐คโ โ ๐ค in C 5
4โ3Y along a subsequence, and[๐ค] 5
4โ2Yโค lim inf
โโ0[๐คโ ] 5
4โ2Y.
This, in particular, implies that ๐คโ โ ๐ค strongly in ๐ฟ2(T2) and since ๐ธโ โ ๐ธ in the sense ofฮ-convergence,๐ค is a minimizer of ๐ธ. Thus, we have the estimate
๐บ (๐ธ) โค [๐ค] 54โ2Y
โค lim infโโ0
[๐คโ ] 54โ2Y
โค lim infโโ0
๐บ (๐ธโ ),
which proves the desired claim.Let now {ใยทใโ }โโ0 be a sequence of probability measures such that ใยทใโ โ ใยทใ weakly and
for every โ โ (0, 1], b is smooth ใยทใโ-almost surely. Since under ใยทใโ , b is smooth, by LemmaD.3 ๐ฃ is smooth. By Theorem 1.14 (iv) there exists a minimizer ๐ค โ W of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), whichis a weak solution to (1.13). If we let ๐ข = ๐ฃ +๐ค , then ๐ข โ W and since ๐น = ๐ฃ๐ 1๐1๐ฃ ใยทใโ-almostsurely (see Proposition 1.8 (iii)), ๐ข is a weak solution to (1.2). By Proposition E.2 we know thatโ|๐1 |๐ ๐ขโ2 + โ|๐2 |
23๐ ๐ขโ2 . 1 for every ๐ < 3, hence by Lemma B.8 ๐ข โ C 5
4โ2Y , which in turn impliesthat๐ค = ๐ข โ ๐ฃ โ C 5
4โ2Y . By Proposition 1.16 we have the estimate[๐ค] 5
4โ2Yโค ๐ถ,
where the constant ๐ถ depends polynomially on max{[b]โ 54โY, [๐ฃ] 3
4โY, [๐น ]โ 3
4โY}. In particular, this
implies that๐บ (๐ธ๐๐๐ (๐ฃ, ๐น ; ยท)) โค ๐ถ.
14 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
By Corollaries 5.4 and 5.7 we know that for every 1 โค ๐ < โ,
supโโ(0,1]
ใ๐ถ๐ใliโ .๐ 1.
Hence, for the functional ๐บ we have that
supโโ(0,1]
ใ๐บ (๐ธ)๐ใextโ = supโโ(0,1]
ใ๐บ (๐ธ๐๐๐ (๐ฃ, ๐น ; ยท))๐ใliโ โค supโโ(0,1]
ใ๐ถ๐ใliโ .๐ 1.
Since by Theorem 1.4 (ii) ใยทใextโ โ ใยทใext weakly and ๐บ is lower semicontinuous we have that
ใ๐บ (๐ธ)๐ใext โค lim infโโ0
ใ๐บ๐ใextโ .๐ 1,
which completes the proof. ๏ฟฝ
1.3. Outline. In Section 2 we show how the HowarthโKรกrmรกnโMonin identities can be used tocontrol certain Besov and ๐ฟ๐ norms by the anharmonic energy E.
In Section 3 we prove Theorem 1.14 and the ฮ-convergence result for the renormalized energy,see Corollary 1.15.
In Section 4 we prove the optimal Hรถlder regularity 54โ of minimizers of the renormalized
energy, see Proposition 1.16.In Section 5, based on the spectral gap inequality (1.7), we provide the stochastic arguments to
prove of Proposition 1.8.
2. Estimates for the Burgers eqation
In this section we bound certain Besov and ๐ฟ๐ norms of a function๐ค โ W by the anharmonicenergy E(๐ค). These bounds will be used in later sections to study the ฮ-convergence of therenormalized energy (1.10) and regularity properties of its minimizers (see Sections 3 and 4 below).The proof of these estimates is based on the application of the HowarthโKรกrmรกnโMonin identityfor the Burgers operator.
We rst need to introduce (directional) Besov spaces. These spaces appear naturally throughthe application of the HowarthโKรกrmรกnโMonin identity (see Proposition 2.3).
Throughout this section, for a function ๐ : T2 โ R we write
๐โ๐ ๐ (๐ฅ) := ๐ (๐ฅ + โ๐ ๐ ) โ ๐ (๐ฅ)
where ๐ฅ โ T2, ๐ โ {1, 2}, โ โ R, ๐1 = (1, 0) and ๐2 = (0, 1).
Denition 2.1. For a function ๐ : T2 โ R, ๐ โ {1, 2}, ๐ โ (0, 1] and ๐ โ [1,โ) we dene thefollowing (directional) Besov seminorm24
โ ๐ โ ยคB๐ ๐ ;๐
:= supโโ(0,1]
1โ๐
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐ d๐ฅ) 1๐
. (2.1)
Notice that in comparison to standard Besov spaces our denition measures regularity in ๐ฅ1and ๐ฅ2 separately. We have also omitted the second lower index which usually appears in standardBesov spaces since in our case it is alwaysโ (corresponding to ยคB๐
๐,โ).
Remark 2.2. For ๐ โฅ 0, given a periodic function ๐ : T2 โ R, we dene |๐๐ |๐ ๐ in Fourier spacevia ๏ฟฝ|๐๐ |๐ ๐ (๐) := |๐ ๐ |๐ ๐ (๐), ๐ โ (2๐Z)2.
24Note that one can take the supremum over all โ โ R in (2.1) by replacing โ๐ with |โ |๐ . Indeed, if โ โ [โ1, 0) thequantity on the right-hand side of (2.1) does not change by symmetry. If โ โ R \ [โ1, 1], one writes โ = โfr + โint withโfr โ (0, 1] and โint โ Z and uses that โ๐โ
๐๐ โ๐ฟ๐ = โ๐โfr
๐๐ โ๐ฟ๐ (by periodicity) while 1
|โ |๐ โค 1โ๐ fr
.
VARIATIONAL METHODS FOR A SINGULAR SPDE 15
For ๐ < 0 and a periodic distribution ๐ of vanishing average in ๐ฅ ๐ 25, we can dene |๐๐ |๐ ๐ in thesame way for ๐ ๐ โ 0. For ๐ = 2, ๐ โ (0, 1) and ๐ โฒ โ (๐ , 1), the Parseval identity implies theequivalence 26โซT2
๏ฟฝ๏ฟฝ|๐๐ |๐ ๐ ๏ฟฝ๏ฟฝ2 d๐ฅ =โ๏ธ
๐โ(2๐Z)2|๐ ๐ |2๐ |๐ (๐) |2 = ๐๐
โซR
1|โ |2๐
โซT2
|๐โ๐ ๐ (๐ฅ) |2 d๐ฅdโ|โ | . ๐ถ (๐ , ๐
โฒ)โ ๐ โ2ยคB๐ โฒ2;๐
(2.2)
for some positive constant ๐ถ (๐ , ๐ โฒ) depending only on ๐ and ๐ โฒ, where we used (B.4) below.
In the next proposition we prove two core estimates based on the HowarthโKรกrmรกnโMoninidentities [GJO15, Lemma 4.1] for the Burgers operator. In [GJO15, Lemma 4.1] the authors dealwith the operator๐ค โฆโ ๐2๐ค + ๐1 12๐ค
2, but the same proof extends to our setting.
Proposition 2.3. There exists ๐ถ > 0 such that for every๐ค โ ๐ฟ2(T2) with vanishing average in ๐ฅ1and for every โ โ (0, 1) we have โซ
T2|๐โ1๐ค |3 d๐ฅ โค ๐ถโ 3
2E(๐ค), (2.3)
sup๐ฅ2โ[0,1)
1โ
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ค |2 d๐ฅ1dโโฒ โค ๐ถโ
12E(๐ค) . (2.4)
Proof. By the HowarthโKรกrmรกnโMonin identities [GJO15, Lemma 4.1] for the Burgers operatorwe know that for every โโฒ โ (0, 1)
๐212
โซ 1
0|๐โโฒ1 ๐ค |๐โโฒ1 ๐ค d๐ฅ1 โ ๐โโฒ
16
โซ 1
0|๐โโฒ1 ๐ค |3 d๐ฅ1 =
โซ 1
0๐โ
โฒ1 [๐ค |๐โ
โฒ1 ๐ค | d๐ฅ1, (2.5)
๐212
โซ 1
0|๐โโฒ1 ๐ค |2 d๐ฅ1 โ ๐โโฒ
16
โซ 1
0(๐โโฒ1 ๐ค)3 d๐ฅ1 =
โซ 1
0๐โ
โฒ1 [๐ค๐
โโฒ1 ๐ค d๐ฅ1. (2.6)
To prove (2.3), we integrate (2.5) over ๐ฅ2 and use the periodicity of๐ค to obtain,
๐โโฒ
โซT2
|๐โโฒ1 ๐ค |3 d๐ฅ = โ6โซT2[๐ค๐
โโโฒ1 |๐โโฒ1 ๐ค | d๐ฅ . (2.7)
The last term is estimated as follows,(โซT2[๐ค๐
โโโฒ1 |๐โโฒ1 ๐ค | d๐ฅ
)2โค
โซT2( |๐1 |โ
12[๐ค)2 d๐ฅ
โซT2( |๐1 |
12 ๐โโ
โฒ1 |๐โโฒ1 ๐ค |)2 d๐ฅ
. |โโฒ |โซT2( |๐1 |โ
12[๐ค)2 d๐ฅ
โซT2(๐1๐ค)2 d๐ฅ,
where we use thatโซT2( |๐1 |
12 ๐โโ
โฒ1 |๐โโฒ1 ๐ค |)2 d๐ฅ .
(โซT2(๐โโโฒ1 |๐โโฒ1 ๐ค |)2 d๐ฅ
) 12(โซT2(๐1 |๐โ
โฒ1 ๐ค |)2 d๐ฅ
) 12
. |โโฒ |โซT2(๐1 |๐โ
โฒ1 ๐ค |)2 d๐ฅ .
Integrating (2.7) over โโฒ โ (0, โ), we obtain thatโซT2
|๐โ1๐ค (๐ฅ) |3 d๐ฅ . โ 32
(โซT2(๐1๐ค)2 d๐ฅ
) 12(โซT2( |๐1 |โ
12[๐ค)2 d๐ฅ
) 12
which in turns implies (2.3).
25We say that a periodic distribution ๐ has vanishing average in ๐ฅ1 if ๐ (eโi๐2 ยท) = 0 for all ๐2 โ 2๐Z, and analogouslyfor ๐ with vanishing average in ๐ฅ2.
26Note that ๐ถ (๐ , ๐ โฒ) โ โ as ๐ โฒ โ ๐ .
16 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
To prove (2.4), we integrate (2.6) over โโฒ โ (0, โ) to obtain with ๐01๐ค = 0
๐212
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ค |2 d๐ฅ1dโโฒ โ
16
โซ 1
0(๐โ1๐ค)3 d๐ฅ1 =
โซ โ
0
โซ 1
0๐โ
โฒ1 [๐ค๐
โโฒ1 ๐ค d๐ฅ1 dโโฒ.
By the Sobolev embedding๐ 1,1(T) โ ๐ฟโ(T) on the torus T = [0, 1) in the form
sup๐งโT
|๐ (๐ง) | โคโซT|๐ (๐ง) | d๐ง +
โซT|๐ โฒ(๐ง) | d๐ง,
we can therefore estimate
sup๐ฅ2โ[0,1)
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ค |2 d๐ฅ1dโโฒ .
โซ โ
0
โซT2
|๐โโฒ1 ๐ค |2 d๐ฅdโโฒ +โซT2
|๐โ1๐ค |3 d๐ฅ
+โซ โ
0
โซ 1
0
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ 1
0๐โ
โฒ1 [๐ค๐
โโฒ1 ๐ค d๐ฅ1
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ d๐ฅ2dโโฒ.The rst term on the right-hand side can be bounded usingโซ
T2|๐โโฒ1 ๐ค |2 d๐ฅ โค (โโฒ)2
โซT2
|๐1๐ค |2 d๐ฅ โค (โโฒ)2E(๐ค).
For the second term we use (2.3). Last, for the third term, the same argument used to estimate theright-hand side of (2.7) leads toโซ โ
0
โซ 1
0
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ 1
0๐โ
โฒ1 [๐ค๐
โโฒ1 ๐ค d๐ฅ1
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ d๐ฅ2dโโฒ . โ|๐1 |โ12[๐ค โ๐ฟ2 โ๐1๐ค โ๐ฟ2
โซ โ
0(โโฒ) 1
2 dโโฒ . โ32E(๐ค) .
Hence, we can bound
sup๐ฅ2โ[0,1)
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ค |2 d๐ฅ1dโโฒ . (โ3 + โ 3
2 )E(๐ค) . โ 32E(๐ค)
for all โ โ (0, 1). ๏ฟฝ
We are now ready to prove the main result of this section.
Proposition 2.4. We have the following estimates:
(i) โ๐ค โ ยคB๐ 3;1
โค ๐ถE(๐ค) 13 , for every ๐ โ (0, 12 ], (2.8)
(ii) โ๐ค โ ยคB๐ 2;1
โค ๐ถE(๐ค) 2๐ +16 , for every ๐ โ [ 12 , 1], (2.9)
(iii) โ๐ค โ๐ฟ๐ โค ๐ถ (๐)E(๐ค)๐โ12๐ , for every ๐ โ [3, 7), (2.10)
(iv) โ๐ค2โยคB2๐โ62๐
2;1
โค ๐ถ (๐)E(๐ค)2๐โ32๐ , for every ๐ โ [6, 7), (2.11)
for every๐ค โ ๐ฟ2(T2) with vanishing average in ๐ฅ1, where๐ถ > 0 is a universal constant and๐ถ (๐) > 0depends on ๐ .
Note that a result similar to (2.8) was obtained in [OS10, Lemma 4] using dierent techniques.
Proof. (i) This is immediate from (2.3), Denition 2.1 and (B.3).(ii) By interpolation we have for ๐ โ [ 12 , 1]:
โ๐ค โ ยคB๐ 2;1
โค โ๐ค โ2(1โ๐ )ยคB122;1
โ๐ค โ2๐ โ1ยคB12;1.
Using (B.3) and (2.8) we get
โ๐ค โยคB122;1
โค โ๐ค โยคB123;1
. E(๐ค) 13 ,
VARIATIONAL METHODS FOR A SINGULAR SPDE 17
with an implicit constant independent of ๐ . We also have the bound
โ๐ค โ ยคB12;1
โค โ๐1๐ค โ๐ฟ2 โค E(๐ค) 12 .
Combining these estimates implies (2.9).(iii) We divide the proof into several steps.Step 1: We rst prove that
sup๐ฅ2โ[0,1)
(โซ 1
0|๐ค (๐ฅ) |๐ d๐ฅ1
) 1๐
.๐ E(๐ค) 12 for all 2 โค ๐ < 4.
Indeed, by (B.12) for ๐ โ [2, 4), ๐ = 2 and ๐ = ๐ค (ยท, ๐ฅ2) (with ๐ฅ2 โ [0, 1) xed) we know that
sup๐ฅ2โ[0,1)
(โซ 1
0|๐ค (๐ฅ) |๐ d๐ฅ1
) 1๐
.๐ sup๐ฅ2โ[0,1)
โซ 1
0
(โซ 1
0|๐โ1๐ค (๐ฅ) |2 d๐ฅ1
) 12 1
โ12โ
1๐
dโโ.
Since ๐ < 4 we have that
sup๐ฅ2โ[0,1)
โซ 1
0
(โซ 1
0|๐โ1๐ค (๐ฅ) |2 d๐ฅ1
) 12 1
โ12โ
1๐
dโโ.๐ sup
๐ฅ2โ[0,1)sup
โโ(0,1]
1โ
14
(โซ 1
0|๐โ1๐ค (๐ฅ) |2 d๐ฅ1
) 12
.
By (B.18) and (2.4) we also know that
sup๐ฅ2โ[0,1)
supโโ(0,1]
1โ
14
(โซ 1
0|๐โ1๐ค (๐ฅ) |2 d๐ฅ1
) 12
. sup๐ฅ2โ[0,1)
supโโ(0,1]
1โ
14
(1โ
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ค (๐ฅ) |2 d๐ฅ1dโโฒ
) 12
. E(๐ค) 12 ,
which combined with the previous estimates implies the desired estimate.Step 2: We prove that (โซ 1
0sup
๐ฅ1โ[0,1)|๐ค (๐ฅ) |3 d๐ฅ2
) 13
. E(๐ค) 13 .
By (B.12) for ๐ = โ, ๐ = 3 and ๐ = ๐ค (ยท, ๐ฅ2), we know that
sup๐ฅ1โ[0,1)
|๐ค (๐ฅ) | .โซ 1
0
(1โ
โซ 1
0|๐โ1๐ค (๐ฅ) |3 d๐ฅ1
) 13 dโโ
for every ๐ฅ2 โ [0, 1). Using Minkowskiโs inequality we obtain the bound(โซ 1
0sup
๐ฅ1โ[0,1)|๐ค (๐ฅ) |3 d๐ฅ2
) 13
.
โซ 1
0
(1โ
โซT2
|๐โ1๐ค (๐ฅ) |3d๐ฅ) 1
3 dโโ.
Using (2.3), the last term in the above inequality is bounded byโซ 1
0
(โซT2
|๐โ1๐ค (๐ฅ) |3d๐ฅ 1โ
) 13 dโโ.
โซ 1
0
1โ
56E(๐ค) 1
3 dโ
which implies the desired estimate.Step 3: We are now ready to prove (2.10). For 5 โค ๐ < 7 this is immediate from Step 1 and Step2, since we have that(โซ
T2|๐ค (๐ฅ) |๐ d๐ฅ
) 1๐
.
(โซ 1
0sup
๐ฅ1โ[0,1)|๐ค (๐ฅ) |3 d๐ฅ2 sup
๐ฅ2โ[0,1)
โซ 1
0|๐ค (๐ฅ) |๐โ3 d๐ฅ1
) 1๐
.๐ E(๐ค)๐โ12๐ .
18 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Step 2 also implies that โ๐ค โ๐ฟ3 . E(๐ค) 13 which proves the bound for ๐ = 3, so it remains to prove
the bound for ๐ โ (3, 5] โ [3, 6]. We proceed using interpolation for 1๐= 1
36โ๐๐
+ 16 (2 โ
6๐) to
bound
โ๐ค โ๐ฟ๐ โค โ๐ค โ6โ๐๐
๐ฟ3โ๐ค โ
2โ 6๐
๐ฟ6. E(๐ค)
6โ๐3๐ E(๐ค) (2โ
6๐) 512 = E(๐ค)
๐โ12๐ .
(iv) We rst notice that by Hรถlderโs inequality, with exponents ๐โ2๐+ 2๐= 1, translation invariance
and Minkowskiโs inequality, we have thatโซT2
(๐โ1๐ค
2(๐ฅ))2
d๐ฅ โค(โซT2
|๐โ1๐ค (๐ฅ) |2๐๐โ2 d๐ฅ
) ๐โ2๐
(โซT2
|๐ค (๐ฅ + โ๐1) +๐ค (๐ฅ) |๐ d๐ฅ) 2๐
โค 4(โซT2
|๐โ1๐ค (๐ฅ) |2๐๐โ2 d๐ฅ
) ๐โ2๐
(โซT2
|๐ค (๐ฅ) |๐ d๐ฅ) 2๐
. (2.12)
As ๐ โ [6, 7), we have 2๐๐โ2 โ (2, 3], and by interpolation we obtain the boundโซ
T2|๐โ1๐ค (๐ฅ) |
2๐๐โ2 d๐ฅ โค
(โซT2
|๐โ1๐ค (๐ฅ) |2 d๐ฅ) ๐โ6๐โ2
(โซT2
|๐โ1๐ค (๐ฅ) |3 d๐ฅ) 4๐โ2
.
Using thatโซT2
|๐โ1๐ค (๐ฅ) |2 d๐ฅ . โ2E(๐ค) and (2.3), the last inequality implies thatโซT2
|๐โ1๐ค (๐ฅ) |2๐๐โ2 d๐ฅ . โ2
(๐โ6๐โ2
)+ 32
(4
๐โ2
)E(๐ค). (2.13)
Combining (2.12), (2.13) and (2.10) we getโซT2
(๐โ1๐ค
2(๐ฅ))2
d๐ฅ .๐(โ2(๐โ6๐โ2
)+ 32
(4
๐โ2
)E(๐ค)
) ๐โ2๐
E(๐ค)๐โ1๐ = โ
2๐โ6๐ E(๐ค)
2๐โ3๐
which implies (2.11). ๏ฟฝ
As (B.4) and (2.11) imply that E(๐ค) (to some power) controls the quantity โ|๐1 |12๐ค2โ2, it follows
that the harmonic part H(๐ค) given in (1.6) of the energy E(๐ค) is also controlled by E(๐ค).Moreover, E(๐ค) controls the ๐ฟ2 norm of the 2
3 -fractional derivative in ๐ฅ2 because the harmonicpartH(๐ค) does. We summarize this in the next proposition, where we also prove that E(๐ค) iscontrolled byH(๐ค).Proposition 2.5.
(i) For every ^ โ (0, 114 ), there exists a constant ๐ถ (^) > 0 such that
H(๐ค) โค ๐ถ (^)(1 + E(๐ค) 3
2+^), (2.14)
for every๐ค โ ๐ฟ2(T2) with vanishing average in ๐ฅ1. In addition, there exists a constant ๐ถ > 0such that โซ
T2|๐1๐ค |2 d๐ฅ +
โซT2
| |๐2 |23๐ค |2d๐ฅ โค ๐ถH(๐ค), (2.15)
for every๐ค โ ๐ฟ2(T2) with vanishing average in ๐ฅ1. In particular, [๐ค]โ 14. H(๐ค) 1
2 .
(ii) There exists a constant ๐ถ > 0 such that
E(๐ค) . 1 + H (๐ค)2 for every๐ค โ W . (2.16)
Proof. (i) Fix ^ โ (0, 114 ) and choose ๐ = ๐ (^) โ (6, 7) such that 2๐โ3
๐= 3
2 + ^. Recalling that[๐ค = ๐2๐ค โ ๐1 12๐ค
2, by (B.4) and the fact that 2๐โ62๐ โ ( 12 , 1) we have
H(๐ค) .โซT2
|๐1๐ค |2 d๐ฅ +โซT2
| |๐1 |โ12[๐ค |2d๐ฅ +
โซT2
| |๐1 |12๐ค2 |2d๐ฅ .^ E(๐ค) + โ๐ค2โ2
ยคB2๐โ62๐
2;1
.
VARIATIONAL METHODS FOR A SINGULAR SPDE 19
By (2.11) we know that โ๐ค2โ2ยคB2๐โ62๐
2;1
.^ E(๐ค)2๐โ3๐ , thus (2.14) follows by Youngโs inequality.
Inequality (2.15) is proved in a more general context in Lemma B.6 and the last statementfollows from Lemma B.8.
(ii) We have
E(๐ค) = H(๐ค) โโซT2
(|๐1 |โ
12 ๐2๐ค |๐1 |โ
12 ๐1๐ค
2)d๐ฅ + 1
4
โซT2
(|๐1 |โ
12 ๐1๐ค
2)2
d๐ฅ
โค H(๐ค) + H (๐ค) 12
(โซT2
(|๐ | 12๐ค2
)2d๐ฅ
) 12+ 14
โซT2
(|๐ | 12๐ค2
)2d๐ฅ .
By Lemma B.7 the claimed inequality (2.16) follows. ๏ฟฝ
3. ฮ-convergence of the renormalized energy
In this section we study the ฮ-convergence of the renormalized energy as the regularizationof white noise is removed, i.e., the limit โ โ 0. As a consequence we will get the existence ofminimizers of the limiting โrenormalized energyโ, in particular, the existence of weak solutions ofthe Euler-Lagrange equation in (1.13).
3.1. Proof of Theorem 1.14. We begin with the proof of coercivity statement (i) in Theorem 1.14.
Proof of Theorem 1.14 (i). Let (b, ๐ฃ, ๐น ) โ T be xed. Since ๐ฃ has vanishing average in ๐ฅ1 we canestimate โ๐ฃ โ๐ฟโ . [๐ฃ] 3
4โY(see e.g., [IO19, Lemma 12]), where the implicit constant is universal for
small Y (e.g., Y โ (0, 1100 )). We will use this estimate several times in what follows. We split
G(๐ฃ, ๐น ;๐ค) =โซT2
(๐ค2๐ 1๐2๐ฃ + ๐ฃ2๐ 1[๐ค + 2๐ฃ๐ค๐ 1[๐ค + 2๐ค๐น โ๐ค๐ฃ๐ 1๐1๐ฃ2 + (๐ 1 |๐1 |
12 (๐ฃ๐ค))2
)d๐ฅ
=:6โ๏ธ
๐=1G๐ (๐ฃ, ๐น ;๐ค), (3.1)
and bound each term separately:(T1) Notice that setting ๐ := |๐1 |โ1๐2๐ฃ we have
๐1๐ = ๐ 1๐2๐ฃ
and ๐ โ C 14โY , with [๐] 1
4โY. [b]โ 5
4โY, (see Lemma D.1). We can therefore integrate by partsโซ
T2๐ค2๐ 1๐2๐ฃ d๐ฅ =
โซT2๐ค2๐1๐ d๐ฅ = โ2
โซT2๐ค๐1๐ค ๐ d๐ฅ
and obtain the bound
|G1(๐ฃ, ๐น ;๐ค) | โค๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ค2๐ 1๐2๐ฃ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค 2โ๐โ๐ฟโ โ๐ค โ๐ฟ2 โ๐1๐ค โ๐ฟ2 . [๐] 14โY
โ๐ค โ๐ฟ3 โ๐1๐ค โ๐ฟ2
. [๐] 14โY
E(๐ค) 13+
12 . [b]โ 5
4โYE(๐ค) 5
6 ,
where we used Hรถlderโs and Jensenโs inequality, together with (2.10), as well as โ๐โ๐ฟโ . [๐] 14โY
because ๐ has zero average. By Youngโs inequality, it follows for any _ โ (0, 1)
|G1(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (1)_
[b]6โ 54โY.
(T2) For the term G2 we have that
|G2(๐ฃ, ๐น ;๐ค) | =๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2( |๐1 |
12 ๐ฃ2) (๐ 1 |๐1 |โ
12[๐ค) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ|๐1 |12 ๐ฃ2โ๐ฟ2 โ|๐1 |โ
12[๐ค โ๐ฟ2
. โ๐ฃ2โยคB232;1
E(๐ค) 12 . [๐ฃ2] 2
3E(๐ค) 1
2 . [๐ฃ]234โY
E(๐ค) 12 ,
20 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
where we used the CauchyโSchwarz inequality, boundedness of ๐ 1 on ๐ฟ2, the estimates (B.4),(B.1) and [IO19, Lemma 12]. Hence, by Youngโs inequality, for any _ โ (0, 1),
|G2(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (2)_
[๐ฃ]434โY.
(T3) We estimate G3 using CauchyโSchwarz, the boundedness of ๐ 1 on ๐ฟ2, and (B.4) by
|G3(๐ฃ, ๐น ;๐ค) | =๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ2โซT2( |๐1 |
12 (๐ฃ๐ค)) (๐ 1 |๐1 |โ
12[๐ค) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ. โ|๐1 |
12 (๐ฃ๐ค)โ๐ฟ2 โ|๐1 |โ
12[๐ค โ๐ฟ2 . โ๐ฃ๐ค โ
ยคB232;1
E(๐ค) 12 .
By the fractional Leibniz rule (Lemma B.2 (i)) we can further bound
โ๐ฃ๐ค โยคB232;1
. โ๐ฃ โ๐ฟโ โ๐ค โยคB232;1
+ [๐ฃ] 23โ๐ค โ๐ฟ2 . [๐ฃ] 3
4โY
(โ๐ค โ
ยคB232;1
+ โ๐ค โ๐ฟ3),
where we also used Jensenโs inequality. Combined with (2.9) and (2.10), this gives
|G3(๐ฃ, ๐น ;๐ค) | . [๐ฃ] 34โY
(E(๐ค) 7
18 + E(๐ค) 13)E(๐ค) 1
2
so that Youngโs inequality yields for any _ โ (0, 1),
|G3(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (3)_
([๐ฃ]63
4โY+ [๐ฃ]93
4โY
).
(T4) By the duality Lemma B.3, G4(๐ฃ, ๐น ;๐ค) = 2โซT2๐ค๐น d๐ฅ can be bounded by
|G4(๐ฃ, ๐น ;๐ค) | .(โ๐1๐ค โ๐ฟ2 + โ|๐2 |
23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ1
)[๐น ]โ 8
9
.(โ๐1๐ค โ๐ฟ2 + โ|๐2 |
23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ3
)[๐น ]โ 3
4โY
with a uniform implicit constant for every Y โ (0, 1100 ), where in the second step we used Jensenโs
inequality and [IO19, Remark 2]. With (2.14), (2.15) and (2.10) we obtain that
โ๐1๐ค โ๐ฟ2 + โ|๐2 |23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ3 . 1 + E(๐ค) 3
4+^ + E(๐ค) 13 ,
where ^ > 0 can be chosen arbitrarily small (e.g., ^ = 1100 ). This yields the estimate
|G4(๐ฃ, ๐น ;๐ค) | .(1 + E(๐ค) 3
4+^ + E(๐ค) 13)[๐น ]โ 3
4โY.
It follows for any _ โ (0, 1),
|G4(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (4)_,^
([๐น ]โ 3
4โY+ [๐น ]
32โ 3
4โY+ [๐น ]
41โ4^โ 3
4โY
).
(T5) For G5(๐ฃ, ๐น ;๐ค) = โโซT2๐ค ๐ฃ๐ 1๐1๐ฃ
2 d๐ฅ , we use again the duality estimate Lemma B.3,
|G5(๐ฃ, ๐น ;๐ค) | .(โ๐1๐ค โ๐ฟ2 + โ|๐2 |
23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ1
)[๐ฃ๐ 1๐1๐ฃ2]โ 2
5.
By [IO19, Lemmata 6 and 12] together with (A.13), we have the uniform bound for any Y โ (0, 1100 )
[๐ฃ๐ 1๐1๐ฃ2]โ 25. [๐ฃ] 1
2[๐ 1๐1๐ฃ2]โ 2
5. [๐ฃ] 3
4โY[๐1๐ฃ2]โ 1
3. [๐ฃ]33
4โY.
Hence, as in (T4), we can bound G5(๐ฃ, ๐น ;๐ค) for some small ^ > 0 (e.g., ^ = 1100 ) by
|G5(๐ฃ, ๐น ;๐ค) | .(1 + E(๐ค) 3
4+^ + E(๐ค) 13)[๐ฃ]33
4โY.
So, for any _ โ (0, 1), by Youngโs inequality,
|G5(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (5)_,^
([๐ฃ]
9234โY
+ [๐ฃ]334โY
+ [๐ฃ]12
1โ4^34โY
).
VARIATIONAL METHODS FOR A SINGULAR SPDE 21
(T6) For the term G6(๐ฃ, ๐น ;๐ค) =โซT2(๐ 1 |๐1 |
12 (๐ฃ๐ค))2 d๐ฅ , we rst notice that by boundedness of ๐ 1
on ๐ฟ2 and the basic estimate (B.4),
G6(๐ฃ, ๐น ;๐ค) = โ|๐1 |12 (๐ฃ๐ค)โ2
๐ฟ2 . โ๐ฃ๐ค โ2ยคB232;1
.
Hence, by Lemma B.2 and Jensenโs inequality,
|G6(๐ฃ, ๐น ;๐ค) | . โ๐ฃ โ2๐ฟโ โ๐ค โ2ยคB232;1
+ [๐ฃ]223โ๐ค โ2
๐ฟ2 . [๐ฃ]234โY
(โ๐ค โ2
ยคB232;1
+ โ๐ค โ2๐ฟ3
).
Together with (2.11) and (2.10) we can therefore estimate
|G6(๐ฃ, ๐น ;๐ค) | . [๐ฃ]234โY
(E(๐ค) 7
9 + E(๐ค) 23).
Youngโs inequality then yields for any _ โ (0, 1)
|G6(๐ฃ, ๐น ;๐ค) | โค _E(๐ค) +๐ถ (6)_
([๐ฃ]63
4โY+ [๐ฃ]93
4โY
). ๏ฟฝ
In the proof of the continuity statement Theorem 1.14 (ii), we need the following lemma.
Lemma 3.1. Let {๐คโ }โโ0 โ W with uniformly bounded energy supโ E(๐คโ ) < โ, and assume that
๐คโ โ ๐ค strongly in ๐ฟ2 as โ โ 0 for some๐ค โ W. Then as โ โ 0,
๐1๐คโ โ ๐1๐ค, |๐1 |โ12 ๐2๐คโ โ |๐1 |โ
12 ๐2๐ค, |๐1 |โ
12[๐คโ
โ |๐1 |โ12[๐ค, |๐2 |
23๐คโ โ |๐2 |
23๐ค,
weakly in ๐ฟ2, and for any ๐ 1 โ (0, 1) and ๐ 2 โ (0, 23 ),
|๐1 |๐ 1๐คโ โ |๐1 |๐ 1๐ค, |๐2 |๐ 2๐คโ โ |๐2 |๐ 2๐ค strongly in ๐ฟ2.
Proof. For the rst part, we use the fact that a uniformly bounded sequence in ๐ฟ2 converging in thedistributional sense converges weakly in ๐ฟ2. By Proposition 2.5, we have that supโ H(๐คโ ) < โ .Therefore, {๐1๐คโ }โ , {|๐1 |โ
12 ๐2๐คโ }โ , {|๐1 |โ
12[๐คโ
}โ , and {|๐2 |23๐คโ }โ are uniformly bounded in ๐ฟ2. They
also converge in the distributional sense since๐คโ โ ๐ค strongly in ๐ฟ2 (in particular, (๐คโ )2 โ ๐ค2
strongly in ๐ฟ1, so [๐คโโ [๐ค in the distributional sense). For the second part, by Lemma B.5, for
any ๐ 1 โ (0, 1), ๐ 2 โ (0, 23 ), we have that {|๐1 |๐ 1๐คโ }โ is uniformly bounded in the homogeneous
Sobolev space ยค๐ป 23 (1โ๐ 1) , and {|๐2 |๐ 2๐คโ }โ is uniformly bounded in ยค๐ป 2
3โ๐ 2 . The compact embeddingยค๐ปmin{ 23 (1โ๐ 1),
23โ๐ 2 } โฉโ ๐ฟ2 (of periodic functions with vanishing average) yields the conclusion. ๏ฟฝ
Proof of Theorem 1.14 (ii). First, all the convergence statements from Lemma 3.1 hold for the se-quence {๐คโ }โ . As (bโ , ๐ฃโ , ๐นโ ) โ (b, ๐ฃ, ๐น ) in T , by Lemma D.1 we also have that ๐โ := |๐1 |โ1๐2๐ฃโ โ|๐1 |โ1๐2๐ฃ =: ๐ in C 1
4โY . We will prove the continuity of G using the decomposition G =โ6
๐=1 G๐
in (3.1) and study each term G๐ separately.(Tโฒ1) For the term G1(๐ฃโ , ๐นโ ;๐คโ ) =
โซT2(๐คโ )2๐ 1๐2๐ฃโ d๐ฅ , we use integration by parts, and that
๐คโ โ ๐ค strongly in ๐ฟ2, ๐1๐คโ โ ๐1๐ค weakly in ๐ฟ2, and ๐โ โ ๐ uniformly on T2,
G1(๐ฃโ , ๐นโ ;๐คโ ) =โซT2(๐คโ )2๐1๐โ d๐ฅ = โ2
โซT2๐คโ๐1๐คโ ๐โ d๐ฅ
โ โ2โซT2๐ค๐1๐ค ๐ d๐ฅ =
โซT2๐ค2๐1๐ d๐ฅ =
โซT2๐ค2๐ 1๐2๐ฃ d๐ฅ = G1(๐ฃ, ๐น ;๐ค).
(Tโฒ2) For the term G2(๐ฃโ , ๐นโ ;๐คโ ) =โซT2๐ฃ2โ๐ 1[๐คโ
d๐ฅ we use that |๐1 |โ12[๐คโ
โ |๐1 |โ12[๐ค weakly in
๐ฟ2 (hence also ๐ 1 |๐1 |โ12[๐คโ
โ ๐ 1 |๐1 |โ12[๐ค weakly in ๐ฟ2), and |๐1 |
12 ๐ฃ2โ โ |๐1 |
12 ๐ฃ2 strongly in C 1
4โY
(see Lemma A.5),
G2(๐ฃโ , ๐นโ ;๐คโ ) =โซT2( |๐1 |
12 ๐ฃ2โ ) (๐ 1 |๐1 |โ
12[๐คโ
) d๐ฅ โโซT2( |๐1 |
12 ๐ฃ2) (๐ 1 |๐1 |โ
12[๐ค) d๐ฅ = G2(๐ฃ, ๐น ;๐ค) .
22 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
(Tโฒ3) Since G3(๐ฃโ , ๐นโ ;๐คโ ) = 2โซT2๐ฃโ๐คโ๐ 1[๐คโ
d๐ฅ = 2โซT2
|๐1 |12 (๐ฃโ๐คโ ) ๐ 1 |๐1 |โ
12[๐คโ
d๐ฅ and, as in (Tโฒ2),๐ 1 |๐1 |โ
12[๐คโ
โ ๐ 1 |๐1 |โ12[๐ค weakly in ๐ฟ2, the claimed convergence follows if we show that
|๐1 |12 (๐ฃโ๐คโ ) โ |๐1 |
12 (๐ฃ๐ค) strongly in ๐ฟ2. For this, we use the triangle inequality, Lemma B.2
(ii), and that ๐คโ โ ๐ค , |๐1 |12๐คโ โ |๐1 |
12๐ค strongly in ๐ฟ2 as well as ๐ฃโ โ ๐ฃ in C 3
4โY โ C 23 which
yield as โ โ 0,
โ|๐1 |12 (๐ฃโ๐คโ ) โ |๐1 |
12 (๐ฃ๐ค)โ๐ฟ2 โค โ|๐1 |
12 ((๐ฃโ โ ๐ฃ)๐คโ )โ๐ฟ2 + โ|๐1 |
12 (๐ฃ (๐คโ โ๐ค))โ๐ฟ2
. โ๐ฃโ โ ๐ฃ โ๐ฟโ โ|๐1 |12๐คโ โ๐ฟ2 + [๐ฃโ โ ๐ฃ] 2
3โ๐คโ โ๐ฟ2
+ โ๐ฃ โ๐ฟโ โ|๐1 |12 (๐คโ โ๐ค)โ๐ฟ2 + [๐ฃ] 2
3โ๐คโ โ๐ค โ๐ฟ2
. [๐ฃโ โ ๐ฃ] 34โY
(โ|๐1 |
12๐คโ โ๐ฟ2 + โ๐คโ โ๐ฟ2
)+ [๐ฃ] 3
4โY
(โ|๐1 |
12 (๐คโ โ๐ค)โ๐ฟ2 + โ๐คโ โ๐ค โ๐ฟ2
)โ 0.
(Tโฒ4) The term G4(๐ฃโ , ๐นโ ;๐คโ ) = 2โซT2๐คโ๐นโ d๐ฅ is treated by duality. Since ๐นโ โ ๐น in Cโ 3
4โY โ Cโ 45
(see e.g., [IO19, Remark 2]). By Lemmata 3.1 and B.3 we have for โ โ 0,|G4(๐ฃโ , ๐นโ ;๐คโ ) โ G4(๐ฃ, ๐น ;๐ค) |
.
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2(๐คโ โ๐ค)๐นโ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ + ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ค (๐นโ โ ๐น ) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ. [๐นโ ]โ 4
5
(โ|๐1 |
56 (๐คโ โ๐ค)โ๐ฟ2 + โ|๐2 |
23 ยท
56 (๐คโ โ๐ค)โ๐ฟ2 + โ๐คโ โ๐ค โ๐ฟ2
)+ [๐นโ โ ๐น ]โ 4
5
(โ|๐1 |
56๐ค โ๐ฟ2 + โ|๐2 |
23 ยท
56๐ค โ๐ฟ2 + โ๐ค โ๐ฟ2
)โ 0.
(Tโฒ5) For the continuity of the term G5(๐ฃโ , ๐นโ ;๐คโ ) = โโซT2๐คโ ๐ฃโ๐ 1๐1๐ฃ
2โ d๐ฅ we again use the du-
ality Lemma B.3. Here, the situation is even easier than in (Tโฒ4), as ๐ฃโ๐ 1๐1๐ฃ2โ converges to thenonsingular product ๐ฃ๐ 1๐1๐ฃ2 in Cโ 1
4โ2Y . This convergence follows by[๐ฃโ๐ 1๐1๐ฃ2โ โ ๐ฃ๐ 1๐1๐ฃ2]โ 1
4โ2Y
= [(๐ฃโ โ ๐ฃ)๐ 1๐1๐ฃ2 + ๐ฃโ๐ 1๐1((๐ฃโ โ ๐ฃ) (๐ฃโ + ๐ฃ))]โ 14โ2Y
. [๐ฃโ โ ๐ฃ] 34โY
[๐ 1๐1๐ฃ2]โ 14โ2Y
+ [๐ฃโ ] 34โY
[๐ 1๐1((๐ฃโ โ ๐ฃ) (๐ฃโ + ๐ฃ))]โ 14โ2Y
. [๐ฃโ โ ๐ฃ] 34โY
[๐ฃ2] 34โY
+ [๐ฃโ ] 34โY
[(๐ฃโ โ ๐ฃ) (๐ฃโ + ๐ฃ)] 34โY
. [๐ฃโ โ ๐ฃ] 34โY
([๐ฃ]23
4โY+ [๐ฃโ ]23
4โY
)โ 0,
where we used that ๐ฃโ โ ๐ฃ in C 34โY and [IO19, Lemmata 6, 7, and 12]. We conclude as for G4 (with
๐ฃโ๐ 1๐1๐ฃ2โ corresponding to ๐นโ and ๐ฃ๐ 1๐1๐ฃ2 to ๐น , using also that Cโ 1
4โ2Y โ Cโ 34โY ).
(Tโฒ6) Noting that G6(๐ฃโ , ๐นโ ;๐คโ ) =โซT2(๐ 1 |๐1 |
12 (๐ฃโ๐คโ ))2 d๐ฅ = โ|๐1 |
12 (๐ฃโ๐คโ )โ2๐ฟ2 , continuity follows
since |๐1 |12 (๐ฃโ๐คโ ) โ |๐1 |
12 (๐ฃ๐ค) in ๐ฟ2 used in (Tโฒ3). ๏ฟฝ
We now prove the compactness Theorem 1.14 (iii) of the sublevel sets of ๐ธ๐๐๐ with respect tothe strong topology in ๐ฟ2.
Proof of Theorem 1.14 (iii). By the coercivity Theorem 1.14 (i) for _ = 12 , it follows that
๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) = E(๐ค) + G(๐ฃ, ๐น ;๐ค) โฅ 12E(๐ค) โ๐ถ โฅ โ๐ถ. (3.2)
Thus ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) is bounded from below and the sublevel set {๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) โค ๐} over W isincluded in a sublevel set of E overW which is relatively compact in ๐ฟ2 by Lemma B.5. It remainsto prove that the sublevel set {๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) โค ๐} over W is closed in ๐ฟ2. By the continuity of
VARIATIONAL METHODS FOR A SINGULAR SPDE 23
G(๐ฃ, ๐น ; ยท) (Theorem 1.14 (ii)), it suces to show that E is lower semicontinuous in W, i.e., forevery {๐ค โ }โโ0 โ W with๐ค โ โ ๐ค in ๐ฟ2, there holds
lim infโโ0
E(๐ค โ ) โฅ E(๐ค) . (3.3)
Indeed, since ๐2 โฅ ๐2 + 2(๐ โ ๐)๐, it follows that
E(๐ค โ ) โฅ E(๐ค) + 2โซT2
(๐1๐ค
โ โ ๐1๐ค)๐1๐ค d๐ฅ + 2
โซT2
(|๐1 |โ
12[๐คโ โ |๐1 |โ
12[๐ค
)|๐1 |โ
12[๐ค d๐ฅ .
Without loss of generality, we may assume that lim inf โโ0 E(๐ค โ ) = lim supโโ0 E(๐ค โ ) < โ. Hence,by Lemma 3.1, ๐1๐ค โ โ ๐1๐ค and |๐1 |โ
12[๐คโ โ |๐1 |โ
12[๐ค weakly in ๐ฟ2, and thus, (3.3) follows. The
same argument shows thatH is lower semicontinuous inW. ๏ฟฝ
We are now ready to prove the existence of minimizers Theorem 1.14 (iv).
Proof of Theorem 1.14 (iv). Note that ๐ธ๐๐๐ (๐ฃ, ๐น ; 0) = 0 and recall that ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) is bounded frombelow (see (3.2)) and lower semicontinuous in ๐ฟ2 over its zero sublevel set (due to (1.10), G(๐ฃ, ๐น ; ยท)being continuous over any sublevel set of E and E being lower semicontinuous in ๐ฟ2). By the๐ฟ2-compactness of the zero sublevel set of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) over W (Theorem 1.14 (iii)), the directmethod in the calculus of variations yields the existence of minimizers.
In order to show that the minimizer is a distributional solution of the EulerโLagrange equation1.13, we do the following splitting:
๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) = H(๐ค) + (E(๐ค) โ H (๐ค)) + G(๐ฃ, ๐น ;๐ค) = H(๐ค) +4โ๏ธ๐=1
๐ฟ ๐ (๐ค),
where
๐ฟ1(๐ค) =โซT2
(2๐ค๐น โ๐ค๐ฃ๐ 1๐1๐ฃ2 + ๐ฃ2๐ 1๐2๐ค
)d๐ฅ
๐ฟ2(๐ค) =โซT2
(๐ค2๐ 1๐2๐ฃ โ
12๐ฃ
2๐ 1๐1๐ค2 + 2๐ฃ๐ค๐ 1๐2๐ค + (๐ 1 |๐1 |
12 (๐ฃ๐ค))2
)d๐ฅ
๐ฟ3(๐ค) =โซT2
(โ๐ 1 |๐1 |
12๐ค2 |๐1 |โ
12 ๐2๐ค โ ๐ฃ๐ค๐ 1๐1๐ค2
)d๐ฅ
๐ฟ4(๐ค) =โซT2
14
(|๐1 |
12๐ค2
)2.
We will show that, given (b, ๐ฃ, ๐น ) โ T , the functional ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) is Cโ on the spaceW endowedwith the normH 1
2 , denoted by (W,H 12 ).
Step 1 (Estimating the linear functional ๐ฟ1). We claim that ๐ฟ1 is a continuous linear functionalon (W,H 1
2 ), i.e.,
|๐ฟ1(๐ค) | โค ๐ถH(๐ค) 12 , (3.4)
where ๐ถ depends polynomially on [๐ฃ] 34โ๐, [๐น ]โ 3
4โ๐. Indeed, as in (T4) in the proof of (i), by the
duality Lemma B.3 and Poincarรฉโs inequality, we may bound๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT22๐ค๐น d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . (โ๐1๐ค โ๐ฟ2 + โ|๐2 |
23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ2
)[๐น ]โ 8
9. [๐น ]โ 3
4โ๐H(๐ค) 1
2 .
By the same argument, see also (T5) above, we have๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ค๐ฃ๐ 1๐1๐ฃ
2 d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . (
โ๐1๐ค โ๐ฟ2 + โ|๐2 |23๐ค โ๐ฟ2 + โ๐ค โ๐ฟ2
)[๐ฃ๐ 1๐1๐ฃ2]โ 2
5. [๐ฃ]33
4โ๐H(๐ค) 1
2 .
As in (T2), the last term of ๐ฟ1 is estimated using CauchyโSchwarz, (B.4), and (B.1), by๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ฃ2๐ 1๐2๐ค d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ|๐1 |12 ๐ฃ2โ๐ฟ2 โ|๐1 |โ
12 ๐2๐ค โ๐ฟ2 . [๐ฃ]23
4โ๐H(๐ค) 1
2 .
24 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Step 2 (Estimating the quadratic functional ๐ฟ2). We claim that ๐ฟ2 is a continuous quadraticfunctional on (W,H 1
2 ), i.e., there exists a continuous bilinear functional๐2 given by๐2(๐ค1,๐ค2)
=
โซT2
(๐ค1๐ค2๐ 1๐2๐ฃ โ
12๐ฃ
2๐ 1๐1(๐ค1๐ค2) + 2๐ฃ๐ค1๐ 1๐2๐ค2 + (|๐1 |12 (๐ฃ๐ค1)) ( |๐1 |
12 (๐ฃ๐ค2))
)d๐ฅ
such that ๐ฟ2(๐ค) = ๐2(๐ค,๐ค), and satisfying the inequality
|๐2(๐ค1,๐ค2) | โค ๐ถH(๐ค1)12H(๐ค2)
12 , (3.5)
where ๐ถ depends polynomially on [b]โ 54โ๐, [๐ฃ] 3
4โ๐, [๐น ]โ 3
4โ๐. To prove (3.5), we again treat each
term separately. Similarly to (T1), let ๐ := |๐1 |โ1๐2๐ฃ , such that ๐ 1๐2๐ฃ = ๐1๐. Recall that by LemmaD.1, [๐] 1
4โ๐. [b]โ 5
4โ๐. Then integration by parts and CauchyโSchwarz, together with Poincarรฉโs
inequality, gives๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ค1๐ค2๐ 1๐2๐ฃ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐1(๐ค1๐ค2)๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . [๐] 14โ๐
โซT2
|๐ค1๐1๐ค2 +๐ค2๐1๐ค1 | d๐ฅ
. [b]โ 54โ๐
H(๐ค1)12H(๐ค2)
12 .
Similarly, the second term can be estimated by๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2
12๐ฃ
2๐ 1๐1(๐ค1๐ค2) d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2
12๐ 1๐ฃ
2(๐ค1๐1๐ค2 +๐ค2๐1๐ค1) d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . [๐ 1๐ฃ2] 3
4โ2๐H(๐ค1)
12H(๐ค2)
12
. [๐ฃ]234โ๐
H(๐ค1)12H(๐ค2)
12 .
By CauchyโSchwarz, Lemma B.2 (i), interpolation and Poincarรฉโs inequality, we can bound thethird term by๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT22๐ฃ๐ค1๐ 1๐2๐ค2 d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = 2๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2
|๐1 |12 (๐ฃ๐ค1)๐ 1 |๐1 |โ
12 (๐2๐ค2) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค 2โ|๐1 |12 (๐ฃ๐ค1)โ๐ฟ2 โ|๐1 |โ
12 ๐2๐ค โ๐ฟ2
.(โ|๐1 |
12๐ค1โ๐ฟ2 โ๐ฃ โ๐ฟโ + โ๐ค1โ๐ฟ2 [๐ฃ] 1
2+๐
)H(๐ค2)
12 . [๐ฃ] 3
4โ๐H(๐ค1)
12H(๐ค2)
12 .
Analogously, the fourth term is estimated by๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2( |๐1 |
12 (๐ฃ๐ค1)) ( |๐1 |
12 (๐ฃ๐ค2)) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ|๐1 |12 (๐ฃ๐ค1)โ๐ฟ2 โ|๐1 |
12 (๐ฃ๐ค2)โ๐ฟ2 . [๐ฃ]23
4โ๐H(๐ค1)
12H(๐ค2)
12 .
Step 3 (Estimating the cubic functional ๐ฟ3). We claim that ๐ฟ3 is a continuous cubic functional on(W,H 1
2 ), i.e., there exists a continuous three-linear functional๐3 given by
๐3(๐ค1,๐ค2,๐ค3) = โโซT2
(๐ 1 |๐1 |
12 (๐ค1๐ค2) |๐1 |โ
12 ๐2๐ค3 + ๐ฃ๐ค1๐ 1๐1(๐ค2๐ค3)
)d๐ฅ,
such that ๐ฟ3(๐ค) = ๐3(๐ค,๐ค,๐ค), and๐3 is controlled by
|๐3(๐ค1,๐ค2,๐ค3) | โค ๐ถH(๐ค1)12H(๐ค2)
12H(๐ค3)
12 , (3.6)
where ๐ถ depends polynomially on [๐ฃ] 34โ๐, [๐น ]โ 3
4โ๐. Indeed, the rst term is estimated using
CauchyโSchwarz and Lemma B.7,๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ 1 |๐1 |
12 (๐ค1๐ค2) |๐1 |โ
12 ๐2๐ค3 d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ|๐1 |12 (๐ค1๐ค2)โ๐ฟ2 โ|๐1 |โ
12 ๐2๐ค3โ๐ฟ2
. H(๐ค1)12H(๐ค2)
12H(๐ค3)
12 .
Similarly, Lemma B.2 (i) and Lemma B.7 imply that๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ฃ๐ค1๐ 1๐1(๐ค2๐ค3) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ|๐1 |12 (๐ฃ๐ค1)โ๐ฟ2 โ|๐1 |
12 (๐ค2๐ค3)โ๐ฟ2 . [๐ฃ] 3
4โ๐H(๐ค1)
12H(๐ค2)
12H(๐ค3)
12 .
VARIATIONAL METHODS FOR A SINGULAR SPDE 25
Step 4 (Estimating the quartic functional ๐ฟ4). We claim that ๐ฟ4 is a continuous quartic functionalon (W,H 1
2 ), i.e., there exists a continuous four-linear functional๐4 given by
๐4(๐ค1,๐ค2,๐ค3,๐ค4) =โซT2
14
(|๐1 |
12 (๐ค1๐ค2) |๐1 |
12 (๐ค3๐ค4)
)d๐ฅ,
such that ๐ฟ4(๐ค) = ๐4(๐ค,๐ค,๐ค,๐ค). Indeed, CauchyโSchwarz and Lemma B.7 implies that
|๐4(๐ค1,๐ค2,๐ค3,๐ค4) | โค ๐ถH(๐ค1)12H(๐ค2)
12H(๐ค3)
12H(๐ค4)
12 , (3.7)
where ๐ถ depends polynomially on [๐ฃ] 34โ๐, [๐น ]โ 3
4โ๐.
Therefore, the gradient โ๐ค๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) belongs to the dual space of (W,H 12 ), in particular, it
is a distribution, so that
โ๐ค๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) = 0
is the EulerโLagrange equation (1.13). ๏ฟฝ
3.2. ฮ-convergence. In view of Theorem 1.14, we give the proof of ฮ-convergence of the renor-malized energy for sequences (bโ , ๐ฃโ , ๐นโ ) โ (b, ๐ฃ, ๐น ) in T as โ โ 0.
Proof of Corollary 1.15. Assume that (bโ , ๐ฃโ , ๐นโ ) โ (b, ๐ฃ, ๐น ) in T as โ โ 0. By the decomposi-tion of ๐ธ๐๐๐ in (1.10) and the continuity of G in Theorem 1.14 (ii), the pointwise convergence๐ธ๐๐๐ (๐ฃโ , ๐นโ ; ยท) โ ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) overW is immediate. We proceed with the proof of the remainingstatements.
(i) (ฮ โ lim inf): Without loss of generality, we may assume that
lim inf โโ0 ๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) = lim supโโ0 ๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) < โ.
As {(bโ , ๐ฃโ , ๐นโ )}โ is uniformly bounded in T , the coercivity Theorem 1.14 (i) implies via (3.2)the existence of a constant ๐ถ > 0 (uniform in โ) such that ๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) โฅ 1
2E(๐คโ ) โ๐ถ ,
i.e., lim supโโ0 E(๐ค โ ) < โ. The desired inequality is a consequence of (1.10) combinedwith the continuity of G (Theorem 1.14 (ii)) and the lower semicontinuity of E over W in(3.3).
(ii) (ฮ โ lim sup): For๐ค โ W, one sets๐คโ = ๐ค for all โ โ (0, 1] and the conclusion follows bythe pointwise convergence of ๐ธ๐๐๐ (๐ฃโ , ๐นโ ; ยท) to ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท).
(iii) (Convergence of minimizers): Let {๐คโ }โโ0 โ W be a sequence of minimizers of thesequence of functionals {๐ธ๐๐๐ (๐ฃโ , ๐นโ ; ยท)}โโ0 (the existence of minimizers follows from The-orem 1.14 (iv)). As {(bโ , ๐ฃโ , ๐นโ )}โ is uniformly bounded in T as โ โ 0, the coercivityTheorem 1.14 (i) implies via (3.2) the existence of a constant ๐ถ > 0 (uniform in โ) such thatfor all โ
0 = ๐ธ๐๐๐ (๐ฃโ , ๐นโ , 0) โฅ ๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) โฅ 12E(๐ค
โ ) โ๐ถ.
This implies that {๐คโ }โโ0 belongs to the sublevel set 2๐ถ of the energy E. Hence, by LemmaB.5, there exists๐ค โ W such that, upon a subsequence,๐คโ โ ๐ค strongly in ๐ฟ2. Moreover,๐ค is a minimizer of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท) over W because for every ๐ค0 โ W, by the ฮ โ lim infinequality and the pointwise convergence of ๐ธ๐๐๐ (๐ฃโ , ๐นโ ; ยท) to ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), we have
๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) โค lim infโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) โค lim supโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ )
โค lim supโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค0) = ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค0) .
Choosing๐ค0 = ๐ค in the above relation, we deduce that
๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) = limโโ0
๐ธ๐๐๐ (๐ฃโ , ๐นโ ;๐ค โ ) .
๏ฟฝ
26 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
4. A priori estimate for minimizers in Hรถlder spaces
In this section we prove an a priori estimate for minimizers of the renormalized energy ๐ธ๐๐๐ ,as stated in Proposition 1.16. We rst need the following proposition.
Proposition 4.1. There exists ๐ถ > 0 such that for every๐ค โ W and periodic distribution ๐ ,
[๐ค๐ ]โ 34โค ๐ถH(๐ค) 1
2 [๐ ]โ 12.
Proof. Case 1 (๐ โ ๐ฟ2โฉCโ 12 (T2)). Since๐ค โ W, the product๐ค๐ belongs to ๐ฟ1(T2). We estimate
[๐ค๐ ]โ 34via (A.1) by studying the blow-up of โ(๐ค๐ )๐ โ๐ฟโ for ๐ โ (0, 1]. We use the โtelescopicโ
decomposition
(๐ค๐ )๐ = (๐ค๐๐2)๐2+
โ๏ธ๐โฅ2, ๐ก= ๐
2๐
((๐ค๐๐ก )๐โ๐ก โ (๐ค๐2๐ก )๐โ2๐ก
). (4.1)
Step 1 (Bound on โ(๐ค๐๐2)๐2โ๐ฟโ ): For ๐ = 10, Youngโs inequality for convolution in Remark 1.11,
Lemma B.4, (2.15) and (A.2) yield for every ๐ โ (0, 1],
โ(๐ค๐๐2)๐2โ๐ฟโ .
(๐
13)โ 5
2๐ โ๐ค๐๐2โ๐ฟ๐ .
(๐
13)โ 1
4 โ๐ค โ๐ฟ10 โ ๐๐2 โ๐ฟโ
.(๐
13)โ 1
4โ12 H(๐ค) 1
2 [๐ ]โ 12=
(๐
13)โ 3
4 H(๐ค) 12 [๐ ]โ 1
2.
Step 2 (Bound on the telescopic sum): By Youngโs inequality for convolution in Remark 1.11 andLemma 4.2 (see below), we obtain via (A.2) for every ๐ โ (0, 1], โ๏ธ
๐โฅ2, ๐ก= ๐
2๐
((๐ค๐๐ก )๐โ๐ก โ (๐ค๐2๐ก )๐โ2๐ก
) ๐ฟโ
โคโ๏ธ
๐โฅ2, ๐ก= ๐
2๐
((๐ค๐๐ก )๐ก โ๐ค๐2๐ก )๐โ2๐ก ๐ฟโ . โ๏ธ๐โฅ2, ๐ก= ๐
2๐
((๐ โ 2๐ก) 1
3)โ 5
4 โ(๐ค๐๐ก )๐ก โ๐ค๐2๐ก โ๐ฟ2
.(๐
13)โ 5
4โ๏ธ
๐โฅ2, ๐ก= ๐
2๐
๐ก13H(๐ค) 1
2 โ ๐๐ก โ๐ฟโ .(๐
13)โ 5
4โ๏ธ
๐โฅ2, ๐ก= ๐
2๐
(๐ก 13 ) 1
2H(๐ค) 12 [๐ ]โ 1
2
.(๐
13)โ 3
4 H(๐ค) 12 [๐ ]โ 1
2.
Step 3 (Hรถlder regularity): By Step 1 and Step 2 we know that for every ๐ โ (0, 1],
โ(๐ค๐ )๐ โ๐ฟโ .(๐
13)โ 3
4 H(๐ค) 12 [๐ ]โ 1
2,
which combined with (A.1) completes the proof.
Case 2 (๐ โ Cโ 12 (T2)). We consider an arbitrary approximation ๐โ โ ๐ฟ2 โฉ Cโ 1
2 (T2) of ๐ withrespect to [ยท]โ 1
2. By Case 1we deduce that๐ค๐โ is a Cauchy sequence in Cโ 3
4 , therefore it convergesto the product๐ค๐ by the same argument as in [IO19, Lemma 6]. ๏ฟฝ
Lemma 4.2. There exists a constant ๐ถ > 0 such that for every ๐ก โ (0, 1], ๐ค โ W and periodic
distribution ๐ ,
โ(๐ค๐๐ก )๐ก โ๐ค๐2๐ก โ๐ฟ2 โค ๐ถ๐ก13H(๐ค) 1
2 โ ๐๐ก โ๐ฟโ .
Proof. We start with the identity((๐ค๐๐ก )๐ก โ๐ค๐2๐ก
)(๐ฅ) =
โซR2๐๐ก (๐ฆ) (๐ค (๐ฅ โ ๐ฆ) โ๐ค (๐ฅ)) ๐๐ก (๐ฅ โ ๐ฆ) ๐๐ฆ, ๐ฅ โ T2.
VARIATIONAL METHODS FOR A SINGULAR SPDE 27
By Minkowskiโs inequality, we deduce
โ(๐ค๐๐ก )๐ก โ๐ค๐2๐ก โ๐ฟ2 โค โ ๐๐ก โ๐ฟโโซR2
|๐๐ก (๐ฆ) |โ๐ค (ยท โ ๐ฆ) โ๐ค (ยท)โ๐ฟ2 d๐ฆ
โค โ ๐๐ก โ๐ฟโโซR2
|๐๐ก (๐ฆ) |โ๐โ๐ฆ11 ๐ค (๐ฅ1, ๐ฅ2 โ ๐ฆ2)โ๐ฟ2๐ฅ d๐ฆ
+ โ ๐๐ก โ๐ฟโโซR2
|๐๐ก (๐ฆ) |โ๐โ๐ฆ22 ๐ค โ๐ฟ2 d๐ฆ,
where we used that ๐ค (๐ฅ โ ๐ฆ) โ๐ค (๐ฅ) = ๐โ๐ฆ11 ๐ค (๐ฅ1, ๐ฅ2 โ ๐ฆ2) + ๐โ๐ฆ22 ๐ค (๐ฅ1, ๐ฅ2) for every ๐ฅ โ T2 and๐ฆ โ R2.
The rst integral can be estimated using the mean value theorem and translation invariance ofthe torus byโซ
R2|๐๐ก (๐ฆ) |
(โซT2
|๐โ๐ฆ11 ๐ค (๐ฅ1, ๐ฅ2 โ ๐ฆ2) |2 d๐ฅ) 1
2d๐ฆ โค
โซR2
|๐ฆ1๐๐ก (๐ฆ) |d๐ฆ โ๐1๐ค โ๐ฟ2 . ๐ก13 โ๐1๐ค โ๐ฟ2,
since by Step 1 in [IO19, proof of Lemma 10] we know that ๐ฆ โฆโ ๐ฆ1๐ (๐ฆ) โ ๐ฟ1(R2).The second integral can be estimated using the Cauchy-Schwarz inequality and (2.2) byโซ
R2|๐๐ก (๐ฆ) |
(โซT2
|๐โ๐ฆ22 ๐ค (๐ฅ) |2 d๐ฅ) 1
2d๐ฆ
= (๐ก 13 ) 3
2 ( 23+
12 )
โซR
โซR
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ ๐ฆ2
(๐ก 13 ) 3
2
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ23+
12
|๐๐ก (๐ฆ) | d๐ฆ1
(โซT2
|๐โ๐ฆ22 ๐ค (๐ฅ) |2
|๐ฆ2 |43
d๐ฅ) 1
2 d๐ฆ2|๐ฆ2 |
12
. (๐ก 13 ) 3
2 ( 23+
12 )
โซR
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ ๐ฆ2
(๐ก 13 ) 3
2
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ23+
12
|๐๐ก (๐ฆ) | d๐ฆ1
๐ฟ2๐ฆ2 (R)
โ|๐2 |23๐ค โ๐ฟ2 . ๐ก
13 โ|๐2 |
23๐ค โ๐ฟ2,
where we also used Minkowskiโs inequality and a change of variables to deduce that โซR
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ ๐ฆ2
(๐ก 13 ) 3
2
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ23+
12
|๐๐ก (๐ฆ) | d๐ฆ1
๐ฟ2๐ฆ2 (R)
โค 1(๐ก 1
3 ) 34
โ|๐ฆ2 | 23+ 12๐ (๐ฆ1, ๐ฆ2)โ๐ฟ2๐ฆ2 (R)
๐ฟ1๐ฆ1 (R)
, (4.2)
along with the fact that ๐ฆ1 โฆโ โ|๐ฆ2 |23+
12๐ (๐ฆ1, ๐ฆ2)โ๐ฟ2๐ฆ2 (R) โ ๐ฟ
1๐ฆ1 (R).
27
Combining the previous estimates with (2.15) implies the desired bound. ๏ฟฝ
We are now ready to prove Proposition 1.16.
Proof of Proposition 1.16. By Theorem 1.14 (iv) if๐ค โ W is a minimizer of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), then๐ค isa weak solution to (1.13). By the Schauder theory for the operator L (see [IO19, Lemma 5]), if๐ค โ W โฉ C 5
4โ2๐ satises (1.13), we have that
[๐ค] 54โ2Y.
[๐(๐น +๐ค๐ 1๐2๐ฃ + ๐ฃ๐ 1๐2๐ค +๐ค๐ 1๐2๐ค
โ 12 (๐ฃ +๐ค)๐ 1๐1(๐ฃ +๐ค)2
)+ 12 ๐2๐ 1(๐ฃ +๐ค)2
]โ 3
4โ2Y.
(4.3)
27 This follows easily from the bound โ|๐ฆ2 | 23+ 12๐ (๐ฆ1, ๐ฆ2)โ๐ฟ2๐ฆ2 (R)
๐ฟ1๐ฆ1 (R)
. โ(1 + |๐ฆ1 |) (1 + |๐ฆ2 |2)๐ (๐ฆ)โ๐ฟ2๐ฆ (R2)
and Plancherelโs identity, using that๐ (๐) = eโ|๐1 |3โ๐22 , see also Step 1 in [IO19, proof of Lemma 10] and Footnote 32.
28 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
We estimate each term on the right-hand side of (4.3) separately. The idea is to bound anyterm containing๐ค in the seminorm [ยท]โ 3
4โ2Yby a productH(๐ค)๐พ (\ ) [๐ค]\5
4โ2Ywith \ โ (0, 1) and
๐พ (\ ) > 0. To prove the statement, the main tools areโฆ the interpolation inequality in Lemma A.2,โฆ Lemma B.8 which yields thatH(๐ค) controls [๐ค]2โ 1
4,
โฆ [IO19, Lemmata 6 and 12] stating that for a distribution ๐ โ C๐ฝ , ๐ฝ โ (โ 32 , 0) \ {โ1,โ
12 }, and two
functions ๐ โ C๐พ , ๐ โ C๐พ with ๐พ,๐พ โ (0, 32 ) both of vanishing average, provided that ๐ฝ + ๐พ > 0and ๐พ โฅ ๐พ , the following estimates hold
[๐ ๐]๐ฝ . [๐ ]๐ฝ [๐]๐พ and [๐๐]๐พ . [๐]๐พ [๐]๐พ .
Also, we use that C๐ผ โ C๐ฝ for any โ 32 < ๐ฝ < ๐ผ < 3
2 with ๐ผ, ๐ฝ โ 0, see [IO19, Remark 2], andLemma A.4 which implies that the Hilbert transform reduces the regularity by Y on Hรถlder spaces.
For [b]โ 54โY, [๐ฃ] 3
4โY, [๐น ]โ 3
4โYโค ๐ , the following estimates hold with an implicit constant
depending on๐ and Y.1. Terms independent of๐ค : First, we notice that [๐๐น ]โ 3
4โ2Yโค [๐น ]โ 3
4โ2Y. [๐น ]โ 3
4โY. 1. Also,
by Denition 1.13, we have that
[๐2๐ 1๐ฃ2]โ 34โ2Y. [๐ 1๐ฃ2] 3
4โ2Y. [๐ฃ2] 3
4โY. [๐ฃ]23
4โY. 1,
[๐ฃ๐1๐ 1๐ฃ2]โ 34โ2Y. [๐ฃ๐1๐ 1๐ฃ2]โ 1
4โ2Y. [๐ฃ] 3
4โY[๐1๐ 1๐ฃ2]โ 1
4โ2Y. [๐ฃ] 3
4โY[๐ฃ2] 3
4โY. [๐ฃ]33
4โY. 1.
2. Linear terms in๐ค : By the interpolation estimate in Lemma A.2 and Lemma B.8, we have
[๐ค] 34+3Y. [๐ค]
13โ2^1โ 1
4[๐ค]
23+2^154โ2Y
. H(๐ค) 16โ^1 [๐ค]
23+2^154โ2Y
, (4.4)
[๐ค] 14+3Y. [๐ค]
23โ2^2โ 1
4[๐ค]
13+2^254โ2Y
. H(๐ค) 13โ^2 [๐ค]
13+2^254โ2Y
, (4.5)
where ^1, ^2 > 0 are small (as functions of Y) for Y > 0 small enough. This yields
[๐ค๐2๐ 1๐ฃ]โ 34โ2Y. [๐ค] 3
4+3Y[๐2๐ 1๐ฃ]โ 3
4โ2Y. H(๐ค) 1
6โ^1 [๐ค]23+2^154โ2Y
[๐ฃ] 34โY
. H(๐ค) 16โ^1 [๐ค]
23+2^154โ2Y
,
[๐ค๐1๐ 1๐ฃ2]โ 34โ2Y. [๐ค๐1๐ 1๐ฃ2]โ 1
4โ2Y. [๐ค] 1
4+3Y[๐1๐ 1๐ฃ2]โ 1
4โ2Y
. H(๐ค) 13โ^2 [๐ค]
13+2^254โ2Y
[๐ฃ]234โY. H(๐ค) 1
3โ^2 [๐ค]13+2^254โ2Y
,
[๐ฃ๐2๐ 1๐ค]โ 34โ2Y. [๐ฃ๐2๐ 1๐ค]โ 3
4+2Y. [๐ฃ] 3
4โY[๐2๐ 1๐ค]โ 3
4+2Y. [๐ค] 3
4+3Y
. H(๐ค) 16โ^1 [๐ค]
23+2^154โ2Y
,
[๐2๐ 1(๐ฃ๐ค)]โ 34โ2Y. [๐ฃ๐ค] 3
4โY. [๐ฃ] 3
4โY[๐ค] 3
4+3Y. H(๐ค) 1
6โ^1 [๐ค]23+2^154โ2Y
,
[๐ฃ๐1๐ 1(๐ฃ๐ค)]โ 34โ2Y. [๐ฃ๐1๐ 1(๐ฃ๐ค)]โ 1
4โ2Y. [๐ฃ] 3
4โY[๐1๐ 1(๐ฃ๐ค)]โ 1
4โ2Y. [๐ฃ๐ค] 3
4โY
. [๐ฃ] 34โY
[๐ค] 34+3Y. H(๐ค) 1
6โ^1 [๐ค]23+2^154โ2Y
.
3. Quadratic terms in๐ค :(a) We start with the term ๐2๐ 1๐ค
2. By the interpolation estimate in Lemma A.2 for ๐พ = 0 andLemma B.8, we have
โ๐ค โ๐ฟโ . [๐ค]56โ2^3โ 1
4[๐ค]
16+2^354โ2Y
. H(๐ค) 512โ^3 [๐ค]
16+2^354โ2Y
, (4.6)
VARIATIONAL METHODS FOR A SINGULAR SPDE 29
where ^3 > 0 is small for Y > 0 small enough. Together with (4.4), it follows that
[๐2๐ 1๐ค2]โ 34โ2Y. [๐2๐ 1๐ค2]โ 3
4+2Y. [๐ค2] 3
4+3Y. โ๐ค โ๐ฟโ [๐ค] 3
4+3Y
. H(๐ค) 712โ(^1+^3) [๐ค]
56+2(^1+^3)54โ2Y
.
Similarly, we estimate
[๐ฃ๐1๐ 1๐ค2]โ 34โ2Y. [๐ฃ๐1๐ 1๐ค2]โ 1
4+2Y. [๐ฃ] 3
4โY[๐1๐ 1๐ค2]โ 1
4+2Y. [๐ค2] 3
4+3Y
. H(๐ค) 712โ(^1+^3) [๐ค]
56+2(^1+^3)54โ2Y
.
(b) The term๐ค๐2๐ 1๐ค is treated via Proposition 4.1,
[๐ค๐2๐ 1๐ค]โ 34. H(๐ค) 1
2 [๐2๐ 1๐ค]โ 12. H(๐ค) 1
2 [๐ 1๐ค]1 . H(๐ค) 12 [๐ค]1+Y .
Then, Lemma A.2 and Lemma B.8 yield
[๐ค]1+Y . [๐ค]16โ2^4โ 1
4[๐ค]
56+2^454โ2Y
. H(๐ค) 112โ^4 [๐ค]
56+2^454โ2Y
,
where ^4 > 0 is small for Y > 0 small enough. Hence we have
[๐ค๐2๐ 1๐ค]โ 34โ2Y. [๐ค๐2๐ 1๐ค]โ 3
4. H(๐ค) 7
12โ^4 [๐ค]56+2^454โ2Y
.
(c) We decompose๐ค๐ 1๐1(๐ฃ๐ค) into๐ค๐ 1(๐ค๐1๐ฃ) +๐ค๐ 1(๐ฃ๐1๐ค) and treat each term separately. ByProposition 4.1, we have
[๐ค๐ 1(๐ฃ๐1๐ค)]โ 34. H(๐ค) 1
2 [๐ 1(๐ฃ๐1๐ค)]โ 12. H(๐ค) 1
2 [๐ 1(๐ฃ๐1๐ค)]โ 12+Y
. H(๐ค) 12 [๐ฃ๐1๐ค]โ 1
2+2Y. H(๐ค) 1
2 [๐ฃ] 34โY
[๐1๐ค]โ 12+2Y. H(๐ค) 1
2 [๐ค] 12+2Y
.
Again, Lemma A.2 and Lemma B.8 yield
[๐ค] 12+2Y. [๐ค]
12โ2^5โ 1
4[๐ค]
12+2^554โ2Y
. H(๐ค) 14โ^5 [๐ค]
12+2^554โ2Y
, (4.7)
where ^5 > 0 is small for Y > 0 small enough. Hence we obtain that
[๐ค๐ 1(๐ฃ๐1๐ค)]โ 34โ2Y. [๐ค๐ 1(๐ฃ๐1๐ค)]โ 3
4. H(๐ค) 3
4โ^5 [๐ค]12+2^554โ2Y
.
The term๐ค๐ 1(๐ค๐1๐ฃ) can be estimated using (4.5) as
[๐ค๐ 1(๐ค๐1๐ฃ)]โ 34โ2Y. [๐ค๐ 1(๐ค๐1๐ฃ)]โ 1
4โ2Y. [๐ค] 1
4+3Y[๐ 1(๐ค๐1๐ฃ)]โ 1
4โ2Y
. [๐ค] 14+3Y
[๐ค๐1๐ฃ]โ 14โY. [๐ค]21
4+3Y[๐1๐ฃ]โ 1
4โY
. H(๐ค) 23โ2^2 [๐ค]
23+4^254โ2Y
[๐ฃ] 34โY. H(๐ค) 2
3โ2^2 [๐ค]23+4^254โ2Y
.
4. Cubic term in๐ค : The cubic term๐ค๐1๐ 1๐ค2 is treated by Proposition 4.1 which yields
[๐ค๐1๐ 1๐ค2]โ 34. H(๐ค) 1
2 [๐ 1๐1๐ค2]โ 12. H(๐ค) 1
2 [๐ 1๐1๐ค2]โ 12+Y. H(๐ค) 1
2 [๐1๐ค2]โ 12+2Y
. H(๐ค) 12 [๐ค2] 1
2+2Y. H(๐ค) 1
2 โ๐ค โ๐ฟโ [๐ค] 12+2Y
.
By (4.6) and (4.7) we have that
โ๐ค โ๐ฟโ [๐ค] 12+2Y. H(๐ค) 2
3โ(^3+^5) [๐ค]23+2(^3+^5)54โ2Y
,
which in turn implies that
[๐ค๐1๐ 1๐ค2]โ 34โ2Y. [๐ค๐1๐ 1๐ค2]โ 3
4. H(๐ค) 3
2โ(^3+^5) [๐ค]23+2(^3+^5)54โ2Y
.
30 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Summing up, Youngโs inequality yields the bound
[๐ค] 54โ2Y
โค ๐ถ (1 + H (๐ค))๐ , (4.8)
for some ๐ โฅ 1, and by our estimates it is clear that the constant ๐ถ depends polynomially on๐ . To conclude, using the fact that๐ค is a minimizer of ๐ธ๐๐๐ (๐ฃ, ๐น ; ยท), we have that ๐ธ๐๐๐ (๐ฃ, ๐น ;๐ค) โค๐ธ๐๐๐ (๐ฃ, ๐น ; 0) = 0. Since ๐ธ๐๐๐ (๐ฃ .๐น ; ยท) = E + G(๐ฃ, ๐น ; ยท) and by Theorem 1.14 (i) we know that|G(๐ฃ, ๐น ;๐ค) | โค 1
2E(๐ค) +๐ถ for some constant๐ถ which also depends polynomially on๐ , we obtainthat E(๐ค) โค 2๐ถ . By (2.14), this implies that ๐ป (๐ค) โค ๐ถ for some constant ๐ถ which dependspolynomially on๐ and combining with (4.8) we obtain the desired bound. ๏ฟฝ
5. Approximations to white noise under the spectral gap assumption
The main goal of this section is to prove Proposition 1.8. Given an probability measure ใยทใwhich satises Assumption 1.1, we prove that ใยทใ is concentrated on Cโ 5
4โ, thus, by Schaudertheory for the operator L, ๐ฃ := Lโ1๐b โ C 3
4โ ใยทใ-almost surely, and we construct ๐น as the๐ฟ๐
ใยทใCโ 3
4โ-limit of the sequence {๐ฃ๐2๐ 1๐ฃ๐ก }๐กโ0. This will allow us to lift ใยทใ to a probability measureใยทใli on Cโ 5
4โ ร C 34โ ร Cโ 3
4โ in a continuous way, i.e., given a sequence of probability measures{ใยทใโ }โโ0 which satisfy Assumption 1.1 and converge weakly to a limit ใยทใ as โ โ 0, then {ใยทใliโ }โโ0converges weakly to ใยทใli.
The proof of Proposition 1.8 is based on suitable estimates on the ๐-moments of multilinearexpressions in the corresponding stochastic objects. In the case of Gaussian approximations, it isenough to bound the second moments, since we can use Nelsonโs hypercontractivity estimateto bound the ๐-moments in a nite Wiener chaos by the second moments for every ๐ > 2 (see[IO19, Lemmata 4 and 8]). On the other hand, for non-Gaussian approximations one has to ndalternative methods to estimate the ๐-moments. This has been achieved with great success in thelast few years under very mild assumptions on the random eld, see for example [HS17, CH16].In these works a direct computation of the ๐-moments is made through explicit formulas in termsof the cumulant functions of the random eld and the nal bounds are obtained by combinatorialarguments.
Here we are interested in approximations of white noise that satisfy the spectral gap inequality(1.7), uniformly in the approximation parameter โ . This covers the Gaussian case, but it allows formore general random elds. The basic observation is that one can bound the ๐-moments directlyby estimating the derivative with respect to the noise, based on the following consequence of thespectral gap assumption (1.7).
Proposition 5.1. The spectral gap inequality (1.7) implies
โจ|๐บ (b) โ ใ๐บ (b)ใ|2๐
โฉ 12๐ โค ๐ถ (๐)
โจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 12๐
, (5.1)
for every 1 โค ๐ < โ and every functional ๐บ on periodic Schwartz distributions which can be
approximated by cylindrical functionals with respect to the norm ใ|๐บ (b) |2๐ใ12๐ + ใโ ๐
๐b๐บ (b)โ2๐
๐ฟ2ใ
12๐,
where the constant ๐ถ (๐) > 0 depends only on ๐ .
Remark 5.2. As in Remark 1.3, using (5.1) we can extend b (๐) for ๐ โ ๐ฟ2(T2) as a centeredrandom variable in ๐ฟ2๐ใยทใ , admissible in (5.1) for any 1 โค ๐ < โ.
Proof. The proof follows [JO20, Lemma 3.1]. Let ๐ > 1. We assume that๐บ is a cylindrical functionalon periodic Schwartz distributions. The general case follows by approximation. Without loss ofgenerality we can assume that ใ๐บ (b)ใ = 0. For _ โ (0, 1] we consider the functional
๐น_ (b) := (๐บ (b)2 + _2)๐
2 .
VARIATIONAL METHODS FOR A SINGULAR SPDE 31
Noting that ๐๐b๐น_ (b) = ๐๐น_ (b)
๐โ2๐ ๐บ (b) ๐
๐b๐บ (b) and using Hรถlderโs inequality, (1.7) applied to ๐น_
yieldsโจ๏ฟฝ๏ฟฝ๐น_ (b) โ ใ๐น_ (b)ใ๏ฟฝ๏ฟฝ2โฉ โค ๐2
โจ๐น_ (b)
2(๐โ2)๐ ๐บ (b)2
๐๐b๐บ (b) 2๐ฟ2
โฉโค ๐2
โจ๐น_ (b)
2(๐โ1)๐
๐๐b๐บ (b) 2๐ฟ2
โฉโค ๐2
โจ๐น_ (b)2
โฉ ๐โ1๐
โจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 1๐
. (5.2)
By CauchyโSchwarz we see thatใ๐น_ (b)ใ2 โค
โจ(๐บ (b)2 + _2)๐โ1
โฉ โจ๐บ (b)2 + _2
โฉ.
By Hรถlderโs inequality and (1.7) applied to๐บ (b) (recall that ใ๐บ (b)ใ = 0) the two terms on the righthand side can be estimated asโจ
(๐บ (b)2 + _2)๐โ1โฉโค ใ๐น_ (b)2ใ
๐โ1๐ ,โจ
๐บ (b)2 + _2โฉโค
โจ ๐๐b๐บ (b) 2๐ฟ2
โฉ+ _2 โค
โจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 1๐
+ _2.
Combining with (5.2) we getโจ๐น_ (b)2
โฉ.
โจ|๐น_ (b) โ ใ๐น_ (b)ใโ |2
โฉ+ ใ๐น_ (b)ใ2
.๐โจ๐น_ (b)2
โฉ ๐โ1๐
โจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 1๐
+ _2ใ๐น_ (b)2ใ๐โ1๐ .
By Youngโs inequality we nally obtain thatโจ(๐บ (b)2 + _2)๐
โฉ=
โจ๐น_ (b)2
โฉ.๐
โจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ+ _2๐ .
The conclusion follows by the monotone convergence theorem as _ โ 0. ๏ฟฝ
Proposition 5.1 allows us to estimate the ๐-moments of multilinear expressions in b (shifted bytheir expectation) by the operator norm of (random) linear functionals on ๐ฟ2(T2) (in the case ofwhite noise this is the CameronโMartin space), after taking one derivative with respect to b . Toestimate the operator norm of these linear functionals we use the regularization properties ofLโ1 in Sobolev spaces.
5.1. Estimates on b and ๐ฃ . In this section, we prove several stochastic estimates for b and๐ฃ := Lโ1๐b which are uniform in the class of probability measures satisfying Assumption 1.1. Asa corollary, we obtain that the law of (b, ๐ฃ) is concentrated on Cโ 5
4โY ร C 34โY (see Corollary 5.4).
A similar result was proved in [IO19, Lemma 4] for ใยทใ being the law of white noise. Here weconsider more general probability measures which are not necessarily Gaussian. Some of theresults of this section will be used in Section 5.2 below in the construction of ๐น .
We start with the following proposition.
Proposition 5.3. Let ใยทใ satisfy Assumption 1.1 and let ๐ฃ := Lโ1๐b . For every 1 โค ๐ < โ,๐ โ (0, 1],and ๐ฆ โ T2 we have that
sup๐ฅ โT2
โจ|b๐ (๐ฅ) |๐
โฉ 1๐ โค ๐ถ
(๐
13)โ 5
4, (5.3)
sup๐ฅ โT2
โจ|๐ฃ (๐ฅ โ ๐ฆ) โ ๐ฃ (๐ฅ) |๐
โฉ 1๐ โค ๐ถ๐ (0, ๐ฆ) 3
4 , (5.4)
sup๐ฅ โT2
โจ| (๐2๐ 1๐ฃ)๐ (๐ฅ) |๐
โฉ 1๐ โค ๐ถ
(๐
13)โ 3
4, (5.5)
32 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
where the constant ๐ถ depends only on ๐ .
Proof. The proof is based on a direct application of the spectral gap inequality (5.1). In thefollowing, for every ๐ฟb โ ๐ฟ2(T2) we consider ๐ฟ๐ฃ the unique solution of zero average in ๐ฅ1 ofL๐ฟ๐ฃ = ๐๐ฟb .Proof of (5.3): Let ๐ฅ0 โ T2 be xed. We consider the linear functional ๐บ (b) = b๐ (๐ฅ0). Sinceb๐ = b โ๐๐ , by Assumption 1.1 (i) we have that ใb๐ (๐ฅ0)ใ = 0. Then, by (5.1) applied to ๐บ (which isa cylindrical functional), we get that for every ๐ โฅ 1โจ
|b๐ (๐ฅ0) |2๐โฉ 12๐ .
โจ ๐๐b b๐ (๐ฅ0) 2๐๐ฟ2โฉ 1
2๐
.
It is easy to check that ๐๐bb๐ (๐ฅ0) = ฮจ๐ (๐ฅ0 โ ยท) โ ๐ฟ2(T2) (with ฮจ๐ the periodization of๐๐ ), and by
Remark 1.11 ๐๐b b๐ (๐ฅ0) ๐ฟ2 = โฮจ๐ (๐ฅ0 โ ยท)โ๐ฟ2 = โฮจ๐ โ๐ฟ2 .(๐
13)โ 5
4,
which proves (5.3) for every 2 โค ๐ < โ, as the implicit constant above does not depend on ๐ฅ0.For ๐ โ [1, 2), the conclusion then follows by Jensenโs inequality.Proof of (5.4): Let ๐ฅ0 โ T2 be xed. For every ๐ฆ โ T2, we consider the linear functional ๐บ (b) =๐ฃ (๐ฅ0 โ ๐ฆ) โ ๐ฃ (๐ฅ0) = b (ฮ(๐ฅ0 โ ๐ฆ โ ยท)) โ b (ฮ(๐ฅ0 โ ยท)), which is well-dened as a centered randomvariable in ๐ฟ2๐ใยทใ for any ๐ โฅ 1 by Remark 5.2 and (1.21) and is admissible in (5.1). Then
๐
๐b๐บ (b) : ๐ฟb โฆโ ๐ฟ๐ฃ (๐ฅ0 โ ๐ฆ) โ ๐ฟ๐ฃ (๐ฅ0) .
By (D.1) we know that
|๐ฟ๐ฃ (๐ฅ0 โ ๐ฆ) โ ๐ฟ๐ฃ (๐ฅ0) | โค [๐ฟ๐ฃ] 34๐ (0, ๐ฆ) 3
4 . ๐ (0, ๐ฆ) 34 โ๐ฟb โ๐ฟ2,
which in turn implies that ๐๐b๐บ (b) ๐ฟ2. ๐ (0, ๐ฆ) 3
4 .
Thus, by (5.1) applied to ๐บ , we have for every ๐ โฅ 1,โจ|๐ฃ (๐ฅ0 โ ๐ฆ) โ ๐ฃ (๐ฅ0) |2๐
โฉ 12๐ . ๐ (0, ๐ฆ) 3
4 ,
which proves (5.4) for 1 โค ๐ < โ, since the implicit constant does not depend on ๐ฅ0. For ๐ โ [1, 2),the conclusion follows by Jensenโs inequality.Proof of (5.5): Let ๐ฅ0 โ T2 be xed. We consider the linear functional๐บ (b) = (๐2๐ 1๐ฃ)๐ (๐ฅ0) (whichis cylindrical). We have that
๐
๐b๐บ (b) : ๐ฟb โฆโ (๐2๐ 1๐ฟ๐ฃ)๐ (๐ฅ0).
By Youngโs inequality for convolution (see Remark 1.11), (D.3), and the fact that ๐ 1 is bounded on๐ฟ
103 (T2), we get that
| (๐2๐ 1๐ฟ๐ฃ)๐ (๐ฅ0) | .(๐
13)โ 3
4 โ๐2๐ 1๐ฟ๐ฃ โ๐ฟ103.
(๐
13)โ 3
4 โ๐2๐ฟ๐ฃ โ๐ฟ103.
(๐
13)โ 3
4 โ๐ฟb โ๐ฟ2,
yielding the estimate ๐๐b๐บ (b) ๐ฟ2.
(๐
13)โ 3
4.
We also note that ใ๐บ (b)ใ = 0. Indeed, since ใ๐ฃ (๐ฅ)ใ = ใb (ฮ(๐ฅ โ ยท))ใ = 0, for every ๐ฅ โ T2, we getthat ใ(๐2๐ 1๐ฃ)๐ (๐ฅ0)ใ = 0. The conclusion then follows as above. ๏ฟฝ
VARIATIONAL METHODS FOR A SINGULAR SPDE 33
As a corollary of (5.3) and the Schauder theory for the operator L, we prove that the laws of band ๐ฃ are concentrated on Cโ 5
4โY and C 34โY .
Corollary 5.4. Let ใยทใ satisfy Assumption 1.1. For every Y โ (0, 1100 ) and 1 โค ๐ < โ there holdsโจ
[b]๐โ 54โY
โฉ 1๐
โค ๐ถ, (5.6)โจ[๐ฃ]๐3
4โY
โฉ 1๐
โค ๐ถ, (5.7)
where the constant ๐ถ depends only on ๐ and Y. Moreover, ใ๐ฃ (๐ฅ)ใ = 0 for every ๐ฅ โ T2.
Proof. The proof of (5.6) follows by (5.3) and Lemma C.2. To prove (5.7), we use Schauder theoryfor the operator L (see [IO19, Lemma 5]), which implies
[๐ฃ] 34โY
= [Lโ1๐b] 34โY. [๐b]โ 5
4โY. [b]โ 5
4โY.
As in the proof of Proposition 5.3, ใ๐ฃ (๐ฅ)ใ = ใb (ฮ(๐ฅ โ ยท))ใ = 0 for every ๐ฅ โ T2, by Remark 5.2 and(1.21). ๏ฟฝ
5.2. Estimates on ๐น . In this section we use the spectral gap inequality (5.1) and (5.4) and (5.5) toconstruct ๐น as the ๐ฟ๐ใยทใC
โ 34โY-limit of the sequence of random variables {๐ฃ๐2๐ 1๐ฃ๐ก }๐กโ0. A similar
result was proved in [IO19, Lemma 8] for ใยทใ being the law of white noise (but instead consideringapproximations {๐ฃโ๐2๐ 1๐ฃโ }โโ0, where ๐ฃโ := Lโ1๐bโ and bโ := ๐โ โ b , for a suitable mollier ๐โ )using Nelsonโs hypercontractivity estimate. As in Section 5.1, our estimate holds for more generalprobability measures which are not necessarily Gaussian.
In what follows, we use the convolution-commutatord๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ := ๐ฃ (๐2๐ 1๐ฃ)2๐ โ (๐ฃ (๐2๐ 1๐ฃ)๐ )๐ .
We will need the following lemma, based on (5.4) and (5.5).
Lemma 5.5. Let ใยทใ satisfy Assumption 1.1 and for a periodic Schwartz distribution let b be ๐ฃ = Lโ1๐b .Then for any 1 โค ๐ < โ and ๐ , ๐ โ (0, 1] there holds
sup๐ฅ โT2
โจ| ( d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ) |๐
โฉ 1๐ โค ๐ถ
((๐
13)โ 1
4(๐ 13) 14 +
(๐
13)โ 3
4(๐ 13) 34), (5.8)
where the constant ๐ถ depends only on ๐ .
Proof. (5.8) is a consequence of the following two claims:Claim 1 For every ๐ , ๐ โ (0, 1] and ๐ โฅ 1,
sup๐ฅ โT2
โจ ๐๐b (d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐
)๐(๐ฅ)
2๐๐ฟ2
โฉ 12๐
.(๐
13)โ 1
4(๐ 13) 14 +
(๐
13)โ 3
4(๐ 13) 34. (5.9)
Claim 2 For every ๐ , ๐ โ (0, 1] and ๐ฅ0 โ T2,ใ(d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0)ใ = ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (๐ฅ0)ใ โ ใ(๐ฃ (๐2๐ 1๐ฃ)๐ )๐ +๐ (๐ฅ0)ใ = 0. (5.10)
Assuming that these claims hold, we may apply for xed ๐ฅ0 โ T2 the ๐ฟ๐-version (5.1) of thespectral gap inequality to the functional ๐บ : b โฆโ (d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0), which yields (5.8) byClaim 1 and Claim 2 for 2 โค ๐ < โ. For ๐ โ [1, 2) (5.8) follows by Jensenโs inequality.
It is easy to see that
๐บ (b) = (d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0) =โฌ
๐ (๐ง, ๐ง โฒ)b (๐ง)b (๐ง โฒ) d๐ง d๐ง โฒ,
where ๐ (๐ง, ๐ง โฒ) is smooth in both variables andโฌ๐ (๐ง, ๐ง โฒ)2 d๐ง d๐ง โฒ < โ. A straightforward calcula-
tion using the CauchyโSchwarz inequality with respect to ใยทใ and (5.4) and (5.5) we also get that
34 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
ใ|๐บ (b) |ใ . 1. Hence, we may apply Lemma F.1 which implies that ๐บ is admissible in the spectralgap inequality (5.1).Proof of Claim 1: Let ๐ฅ0 โ T2 be xed. We rst notice that for every ๐ , ๐ โ (0, 1], the derivative ofthe quadratic functional ๐บ is given by
๐
๐b๐บ (b) : ๐ฟb โฆโ (d๐ฟ๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0) + (d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฟ๐ฃ)๐ )๐ (๐ฅ0),
where ๐ฟ๐ฃ is the unique solution of zero average in ๐ฅ1 to L๐ฟ๐ฃ = ๐๐ฟb for ๐ฟb โ ๐ฟ2(T2).Step 1: We rst show that
supโ๐ฟb โ
๐ฟ2 โค1| ( d๐ฟ๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0) | .
โซR2
|๐ฆ1 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ยท)(๐2๐ 1๐ฃ)๐ (ยท โ ๐ฆ)โ๐ฟ109d๐ฆ
+โซR2
|๐ฆ2 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ยท)(๐2๐ 1๐ฃ)๐ (ยท โ ๐ฆ)โ๐ฟ107d๐ฆ, (5.11)
supโ๐ฟb โ
๐ฟ2 โค1| ( d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฟ๐ฃ)๐ )๐ (๐ฅ0) | .
โซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ยท) (๐ฃ (ยท โ ๐ฆ) โ ๐ฃ) โ๐ฟ107d๐ฆ. (5.12)
Step 1a (Proof of (5.11)): By Fubini and the mean value theorem we have
(d๐ฟ๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0)
=
โซR2๐๐ (๐ฅ0 โ ๐ฅ)
โซR2๐๐ (๐ฆ) (๐ฟ๐ฃ (๐ฅ) โ ๐ฟ๐ฃ (๐ฅ โ ๐ฆ)) (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ) d๐ฆ d๐ฅ
=
โซR2๐๐ (๐ฆ)
โซT2ฮจ๐ (๐ฅ0 โ ๐ฅ)
โซ 1
0(๐ฆ1๐1๐ฟ๐ฃ (๐ฅ โ ๐ก๐ฆ) + ๐ฆ2๐2๐ฟ๐ฃ (๐ฅ โ ๐ก๐ฆ)) d๐ก (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ) d๐ฅ d๐ฆ,
where ฮจ๐ is the periodization of๐๐ . By Hรถlderโs and Minkowskiโs inequalities, as well as transla-tion invariance, it follows that
| ( d๐ฟ๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ0) |
โคโซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ)โ๐ฟ109๐ฅ
โซ 1
0๐ฆ1๐1๐ฟ๐ฃ (๐ฅ โ ๐ก๐ฆ) d๐ก
๐ฟ10๐ฅ
d๐ฆ
+โซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ)โ๐ฟ107๐ฅ
โซ 1
0๐ฆ2๐2๐ฟ๐ฃ (๐ฅ โ ๐ก๐ฆ) d๐ก
๐ฟ103๐ฅ
d๐ฆ
.
โซR2
|๐ฆ1 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ)โ๐ฟ109๐ฅ
d๐ฆ โ๐1๐ฟ๐ฃ โ๐ฟ10
+โซR2
|๐ฆ2 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ)โ๐ฟ107๐ฅ
d๐ฆ โ๐2๐ฟ๐ฃ โ๐ฟ103.
By (D.2) and (D.3) we have โ๐1๐ฟ๐ฃ โ๐ฟ10, โ๐2๐ฟ๐ฃ โ๐ฟ103. โ๐ฟb โ๐ฟ2 , hence (5.11) follows after taking the
supremum over โ๐ฟb โ๐ฟ2 โค 1.Step 1b (Proof of (5.12)): As in Step 1A, we have
(d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฟ๐ฃ)๐ )๐ (๐ฅ0)
=
โซR2๐๐ (๐ฆ)
โซT2ฮจ๐ (๐ฅ0 โ ๐ฅ) (๐ฃ (๐ฅ) โ ๐ฃ (๐ฅ โ ๐ฆ)) (๐2๐ 1๐ฟ๐ฃ)๐ (๐ฅ โ ๐ฆ) d๐ฅ d๐ฆ,
where ฮจ๐ is the periodization of๐๐ . By Hรถlderโs inequality, translation invariance, and the factthat ๐ 1 is bounded on ๐ฟ 10
3 (T2), we obtain that
| ( d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฟ๐ฃ)๐ )๐ (๐ฅ0) |
.
โซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐ฃ (๐ฅ) โ ๐ฃ (๐ฅ โ ๐ฆ)) โ๐ฟ107๐ฅ
โ(๐2๐ 1๐ฟ๐ฃ)๐ (๐ฅ โ ๐ฆ)โ๐ฟ103๐ฅ
d๐ฆ
VARIATIONAL METHODS FOR A SINGULAR SPDE 35
.
โซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ) (๐ฃ (๐ฅ) โ ๐ฃ (๐ฅ โ ๐ฆ)) โ๐ฟ107๐ฅ
d๐ฆ โ๐2๐ฟ๐ฃ โ๐ฟ103.
By (D.3), โ๐2๐ฟ๐ฃ โ๐ฟ103. โ๐ฟb โ๐ฟ2 , which gives (5.12) after taking the supremum over โ๐ฟb โ๐ฟ2 โค 1.
Step 2: For any ๐ โฅ 1 and ๐ฅ0 โ T2, by Step 1 and Minkowskiโs inequality (since 2๐ โฅ max{ 107 ,109 }),
we get thatโจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 12๐
.
โซR2
|๐ฆ1 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ)ใ|(๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ) |2๐ใ12๐ โ
๐ฟ109๐ฅ
d๐ฆ
+โซR2
|๐ฆ2 | |๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ)ใ|(๐2๐ 1๐ฃ)๐ (๐ฅ โ ๐ฆ) |2๐ใ12๐ โ
๐ฟ107๐ฅ
d๐ฆ
+โซR2
|๐๐ (๐ฆ) |โฮจ๐ (๐ฅ0 โ ๐ฅ)ใ|๐ฃ (๐ฅ) โ ๐ฃ (๐ฅ โ ๐ฆ) |2๐ใ12๐ โ
๐ฟ107๐ฅ
d๐ฆ.
By (5.4) and (5.5) this implies the boundโจ ๐๐b๐บ (b) 2๐๐ฟ2
โฉ 12๐
. โฮจ๐ โ๐ฟ109
(๐ 13)โ 3
4โซR2
|๐ฆ1 | |๐๐ (๐ฆ) | d๐ฆ + โฮจ๐ โ๐ฟ107
(๐ 13)โ 3
4โซR2
|๐ฆ2 | |๐๐ (๐ฆ) | d๐ฆ
+ โฮจ๐ โ๐ฟ107
โซR2๐ (0, ๐ฆ) 3
4 |๐๐ (๐ฆ) | d๐ฆ
.(๐
13)โ 1
4(๐ 13)1โ 3
4 +(๐
13)โ 3
4(๐ 13) 32โ
34 +
(๐
13)โ 3
4(๐ 13) 34,
which proves Claim 2, since the implicit constant does not depend on ๐ฅ0.Proof of Claim 2: By stationarity we know that ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (๐ฅ0)ใ = ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ. If wedenote by ๐ฃ the solution to (1.3) with b replaced by bฬ (๐ฅ) = b (โ๐ฅ1, ๐ฅ2), by the symmetry of ฮ (see(1.20)) and the fact that b and bฬ have the same law (see Assumption 1.1 (iii)), we know that ๐ฃ = ๐ฃ inlaw, hence ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ = ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ. By the symmetry of๐๐ก for ๐ก โ (0, 1] and thefact that ๐ 1๐ฃ (๐ฅ) = โ๐ 1๐ฃ (โ๐ฅ1, ๐ฅ2), we get ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ = โใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ, which impliesthat ใ(๐ฃ (๐2๐ 1๐ฃ)2๐ )๐ (0)ใ = 0. Similarly, ใ(๐ฃ (๐2๐ 1๐ฃ)๐ )๐ +๐ (0)ใ = 0. ๏ฟฝ
We then have the following proposition.
Proposition 5.6. Under the assumptions of Lemma 5.5, for every Y โ (0, 1100 ), 1 โค ๐ < โ, and
0 < ๐ โค ๐ก โค 1 dyadically related there holdsโจ[(๐ฃ๐2๐ 1๐ฃ๐ )๐กโ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
โค(๐ก13) 14. (5.13)
Furthermore, the following bound holds,
sup๐ก โ(0,1]
โจ[๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
โค ๐ถ. (5.14)
In the above estimates, the constant ๐ถ depends only on Y and ๐ .
Proof. Step 1: We rst prove that for every 1 โค ๐ < โ, 0 < ๐ โค ๐ก โค 1 (note that by assumption๐ = ๐ก
2๐ for some ๐ โฅ 0) and ๐ โ (0, 1] there holds,
sup๐ฅ โT2
โจ| ( d๐ฃ, (ยท)๐กโ๐ e (๐2๐ 1๐ฃ)๐ )๐ (๐ฅ) |๐
โฉ 1๐ โค ๐ถ
((๐
13)โ 1
4(๐ก13) 14 +
(๐
13)โ 3
4(๐ก13) 34). (5.15)
Together with Lemma C.2 this implies (5.13). We will use the following telescopic sum identity,
d๐ฃ, (ยท)๐กโ๐ e (๐2๐ 1๐ฃ)๐ =โ๏ธ
0โค๐โค๐โ1๐ = ๐ก
22๐
(d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐กโ2๐ .
36 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Combined with Lemma 5.5 we obtain thatโจ| ( d๐ฃ, (ยท)๐กโ๐ e (๐2๐ 1๐ฃ)๐ก )๐ (๐ฅ) |๐
โฉ 1๐ .
โ๏ธ0โค๐โค๐โ1๐ = ๐ก
22๐
โจ| ( d๐ฃ, (ยท)๐ e (๐2๐ 1๐ฃ)๐ )๐+๐กโ2๐ (๐ฅ) |๐
โฉ 1๐
.โ๏ธ
0โค๐โค๐โ1๐ = ๐ก
22๐
(((๐ + ๐ก โ 2๐ ) 1
3)โ 1
4(๐ 13) 14 +
((๐ + ๐ก โ 2๐ ) 1
3)โ 3
4(๐ 13) 34)
.(๐
13)โ 1
4(๐ก13) 14
โ๏ธ0โค๐โค๐โ1
12๐+1
12+
(๐
13)โ 3
4(๐ก13) 34
โ๏ธ0โค๐โค๐โ1
12๐+1
4
.(๐
13)โ 1
4(๐ก13) 14 +
(๐
13)โ 3
4(๐ก13) 34,
which proves the desired claim.Step 2: We now prove that for every Y โ (0, 1
100 ), 1 โค ๐ < โ and ๐ โ (0, 1],
sup๐ก โ(0,1]
sup๐ฅ โT2
โจ| (๐ฃ๐2๐ 1๐ฃ๐ก )๐ (๐ฅ) |๐
โฉ 1๐ .Y,๐
(๐
13)โ 3
4โY, (5.16)
which together with Lemma C.2 implies (5.14).We rst assume that ๐ก โ [๐2 , 1]. Then, by Denition 1.13 of negative Hรถlder norms and
(A.14) we know that [๐2๐ 1๐ฃ]โ 34โ2Y. [๐ 1๐ฃ] 3
4โ2Y. [๐ฃ] 3
4โY. Combined with (A.1) and the fact that
โ๐ฃ โ๐ฟโ . [๐ฃ] 34โY
, we have that
| (๐ฃ๐2๐ 1๐ฃ๐ก )๐ (๐ฅ) | โค โ๐ฃ๐2๐ 1๐ฃ๐ก โ๐ฟโ โค โ๐ฃ โ๐ฟโ โ๐2๐ 1๐ฃ๐ก โ๐ฟโ
.(๐ก13)โ 3
4โ2Y [๐ฃ]234โY.
(๐
13)โ 3
4โ2Y [๐ฃ]234โY. (5.17)
By (5.7), this implies the estimateโจ| (๐ฃ๐2๐ 1๐ฃ๐ก )๐ (๐ฅ) |๐
โฉ 1๐
โ.
(๐
13)โ 3
4โ2Yโจ[๐ฃ]2๐3
4โY
โฉ 1๐
โ
.(๐
13)โ 3
4โ2Y, (5.18)
for every ๐ก โ [๐2 , 1], uniformly in ๐ฅ โ T2 and โ โ (0, 1].We now assume that ๐ก โ (0, ๐2 ]. Then, there exists๐โ โ (๐4 ,
๐2 ] such that ๐ก = ๐โ
2๐ , for some ๐ โฅ 1.Using the semigroup property, we write
(๐ฃ๐2๐ 1๐ฃ๐ก )๐ =((๐ฃ๐2๐ 1๐ฃ๐ก )๐โโ๐ก โ ๐ฃ๐2๐ 1๐ฃ๐โ
)๐โ๐โ+๐ก +
(๐ฃ๐2๐ 1๐ฃ๐โ
)๐โ๐โ+๐ก .
By (5.13), the rst term can be estimated asโจ|((๐ฃ๐2๐ 1๐ฃ๐ก )๐โโ๐ก โ ๐ฃ๐2๐ 1๐ฃ๐โ
)๐โ๐โ+๐ก (๐ฅ) |
๐โฉ 1๐
.((๐ โ๐โ + ๐ก)
13)โ 3
4(๐
13โ
) 34+
((๐ โ๐โ + ๐ก)
13)โ 1
4(๐
13โ
) 14. 1,
where we also used that ๐โ โค ๐2 โค ๐ โ ๐โ + ๐ก . For the second term, noting that ๐โ > ๐
4 andproceeding as in (5.17) and (5.18), we obtain the boundโจ
|(๐ฃ๐2๐ 1๐ฃ๐โ
)๐โ๐โ+๐ก (๐ฅ) |
๐โฉ 1๐
.(๐
13โ
)โ 34โ2Y
โจ[๐ฃ]2๐3
4โY
โฉ 1๐
โ
.(๐
13)โ 3
4โ2Y.
Hence, we also proved that โจ| (๐ฃ๐2๐ 1๐ฃ๐ก )๐ (๐ฅ) |๐
โฉ 1๐ . 1 +
(๐
13)โ 3
4โ2Y, (5.19)
for ๐ก โ (0, ๐4 ], uniformly in ๐ฅ โ T2.Combining (5.18) and (5.19) gives (5.16) upon relabelling Y. ๏ฟฝ
VARIATIONAL METHODS FOR A SINGULAR SPDE 37
As a corollary we obtain,
Corollary 5.7. Let ใยทใ satisfy Assumption 1.1. There exists a unique centered and stationary random
variable b โฆโ ๐น (b) such that for every Y โ (0, 1100 ) and 1 โค ๐ < โ,
lim๐ก=2โ๐โ0
โจ[๐น โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
= 0, (5.20)
and the convergence is uniform in the class of probability measures satisfying Assumption 1.1.
Proof. We prove that for every Y โ (0, 1], 1 โค ๐ < โ and 0 โค ๐ โค ๐ก โค 1 dyadic,
lim๐ก,๐โ0
โจ[๐ฃ๐2๐ 1๐ฃ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
= 0. (5.21)
By the triangle inequality we have thatโจ[๐ฃ๐2๐ 1๐ฃ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
โคโจ[๐ฃ๐2๐ 1๐ฃ๐ โ (๐ฃ๐2๐ 1๐ฃ๐ )๐กโ๐ ]๐โ 3
4โY
โฉ 1๐
+โจ[(๐ฃ๐2๐ 1๐ฃ๐ )๐กโ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
.
To estimate the rst term we use Propositions A.7 and (5.14) which imply thatโจ[๐ฃ๐2๐ 1๐ฃ๐ โ (๐ฃ๐2๐ 1๐ฃ๐ )๐กโ๐ ]๐โ 3
4โY
โฉ 1๐
.((๐ก โ ๐) 1
3) Y
2โจ[๐ฃ๐2๐ 1๐ฃ๐ ]๐โ 3
4โY2
โฉ 1๐
.((๐ก โ ๐) 1
3) Y
2.
Using (5.13), the second term is estimated asโจ[(๐ฃ๐2๐ 1๐ฃ๐ )๐กโ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
.(๐ก13) 14.
Hence, we have proved thatโจ[๐ฃ๐2๐ 1๐ฃ๐ โ ๐ฃ๐2๐ 1๐ฃ๐ก ]๐โ 3
4โY
โฉ 1๐
.((๐ก โ ๐) 1
3) Y
2 +(๐ก13) 14,
which implies (5.21) after taking ๐, ๐ก โ 0. This implies that the sequence {๐ฃ๐2๐ 1๐ฃ๐ก }๐ก โ(0,1] is Cauchyin ๐ฟ๐ใยทใC
โ 34โY , hence it converges to a limit ๐น in ๐ฟ๐ใยทใC
โ 34โY . The fact that the convergence is uniform
in the class of probability measures satisfying Assumption 1.1 follows since our estimates dependon ใยทใ only through the spectral gap inequality (1.7).
Similarly to the proof of Lemma 5.5, we can show that ใ๐ฃ๐2๐ 1๐ฃ๐ก (๐ฅ)ใ = 0 for every ๐ฅ โ T2 and๐ก โ (0, 1]. Hence, as a limit in ๐ฟ๐ใยทใC
โ 34โY , the fact that ๐น is centered and stationary follows from
the corresponding properties of ๐ฃ๐2๐ 1๐ฃ๐ก . ๏ฟฝ
5.3. Proof of Proposition 1.8.
Proof. Let ใยทใli be given by ใ๐บ (b, ๐ฃ, ๐น )ใli := ใ๐บ (b, ๐ฃ, ๐น )ใ for every bounded and continuous๐บ : Cโ 5
4โY ร C 34โY ร Cโ 3
4โY โ R, with the convention that under ใยทใ, ๐ฃ = Lโ1๐b and ๐น is given by(5.20) (under ใยทใli we think of (b, ๐ฃ, ๐น ) as a dummy variable in T := Cโ 5
4โY ร C 34โY ร Cโ 3
4โY ). Thefact that ใยทใli denes a probability measure on T is immediate by Corollaries 5.4 and 5.7.
Statements (i) and (ii) are immediate by the construction of ใยทใli. The rst part of statement(iii), that is, (1.9), is immediate by Corollary 5.7. For the second part, note that in the case when b issmooth ใยทใ-almost surely, the product ๐ฃ๐2๐ 1๐ฃ makes sense ใยทใ-almost surely and we also have that๐ฃ๐2๐ 1๐ฃ๐ก โ ๐ฃ๐2๐ 1๐ฃ ใยทใ-almost surely. By (5.20) we know that ๐ฃ๐2๐ 1๐ฃ๐ก โ ๐น in Cโ 3
4โY ใยทใ-almostsurely along a subsequence. Hence, we should have that ๐น = ๐ฃ๐2๐ 1๐ฃ ใยทใ-almost surely.
It remains to prove the continuity statement (iv). Assume that {ใยทใโ }โโ0 converges weakly toใยทใ and consider {ใยทใliโ }โโ0 and ใยทใli.
38 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Step 1: We prove that weak convergence of {ใยทใโ }โโ0 to ใยทใ in the Schwartz topology implies weakconvergence in Cโ 5
4โY . Indeed, let ๐บ : Cโ 54โY โ R be bounded and continuous. Then, we can
writeใ๐บ (b)ใโ โ ใ๐บ (b)ใ = (ใ๐บ (b)ใโ โ ใ๐บ (b๐ก )ใโ ) + (ใ๐บ (b๐ก )ใโ โ ใ๐บ (b๐ก )ใ) + (ใ๐บ (b๐ก )ใ โ ใ๐บ (b)ใ).
To treat the rst term, we use (A.16) and (5.6) (which holds uniform in the class of probabilitymeasures satisfying Assumption 1.1) yielding for every 1 โค ๐ < โ,
supโโ(0,1]
ใ[b โ b๐ก ]๐โ 54โY
ใ1๐
โ. ๐ก
Y6 supโโ(0,1]
ใ[b]๐โ 54โ
Y2ใ
1๐
โ. ๐ก
Y6 . (5.22)
For ๐ฟ > 0 which we x below, we writeใ๐บ (b)ใโ โ ใ๐บ (b๐ก )ใโ = ใ(๐บ (b) โ๐บ (b๐ก ))1{ [bโb๐ก ]โ 5
4 โY<๐ฟ }ใโ + ใ(๐บ (b) โ๐บ (b๐ก ))1{ [bโb๐ก ]โ 5
4 โYโฅ๐ฟ }ใโ .
For [ > 0, by the continuity of ๐บ we can choose ๐ฟ suciently small such that
|ใ(๐บ (b) โ๐บ (b๐ก ))1{ [bโb๐ก ]โ 54 โY
<๐ฟ }ใโ | โค[
4uniformly in โ โ (0, 1]. By (5.22), the boundedness of ๐บ , and Chebyshevโs inequality, we canchoose ๐ก โ (0, 1] suciently small such that
|ใ(๐บ (b) โ๐บ (b๐ก ))1{ [bโb๐ก ]โ 54 โY
โค๐ฟ }ใโ | โค โ๐บ โ๐ฟโ
(Cโ 5
4 โY) supโโ(0,1]
ใ1{ [bโb๐ก ]โ 54 โY
โฅ๐ฟ }ใโ โค[
4 .
Hence, we obtain that for ๐ก suciently small
supโโ(0,1]
|ใ๐บ (b)ใโ โ ใ๐บ (b๐ก )ใโ | โค[
2 .
Similarly, we can show that for ๐ก suciently small
|ใ๐บ (b)ใ โ ใ๐บ (b๐ก )ใ| โค[
2 .
Since {ใยทใโ }โโ0 converges to ใยทใ in the Schwartz topology, for every ๐ก โ (0, 1] we know thatใ๐บ (b๐ก )ใโ โ ใ๐บ (b๐ก )ใ as โ โ 0. In total, we have that
lim supโโ0
|ใ๐บ (b)ใโ โ ใ๐บ (b)ใ| โค [,
which proves that ใ๐บ (b)ใโ โ ใ๐บ (b)ใ as โ โ 0 since [ is arbitrary.Step 2: We now prove that {ใยทใliโ }โโ0 converges weakly to ใยทใli in T . The argument is similar inspirit to Step 1. Let ๐บ : T โ R be a bounded continuous function. Then, we write
ใ๐บ (b, ๐ฃ, ๐น )ใliโ โ ใ๐บ (b, ๐ฃ, ๐น )ใli = ใ๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใโ+ ใ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก ) โ๐บ (b, ๐ฃ, ๐น )ใ+ ใ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใโ โ ใ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใ.
To estimate the rst term, for ๐ฟ > 0 to be xed below, we use the decompositionใ๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใโ = ใ(๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก ))1{ [๐นโ๐ฃ๐2๐ 1๐ฃ๐ก ]โ 3
4 โY<๐ฟ }ใโ
+ ใ(๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก ))1{ [๐นโ๐ฃ๐2๐ 1๐ฃ๐ก ]โ 34 โY
โฅ๐ฟ }ใโ .
For [ > 0, by the continuity of ๐บ we can choose ๐ฟ > 0 suciently small such that
|ใ(๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก ))1{ [๐นโ๐ฃ๐2๐ 1๐ฃ๐ก ]โ 34 โY
<๐ฟ }ใโ | โค[
4uniformly in โ โ (0, 1]. By (5.20), the boundedness of ๐บ , and Chebyshevโs inequality, we canchoose ๐ก suciently small such that
supโโ(0,1]
ใ(๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก ))1{ [๐นโ๐ฃ๐2๐ 1๐ฃ๐ก ]โ 34 โY
โฅ๐ฟ }ใโ
VARIATIONAL METHODS FOR A SINGULAR SPDE 39
โค โ๐บ โ๐ฟโ
(Cโ 5
4 โYรC34 โYรCโ 3
4 โY) supโโ(0,1]
ใ1{ [๐นโ๐ฃ๐2๐ 1๐ฃ๐ก ]โ 34 โY
โฅ๐ฟ }ใโ โค[
4 .
Hence, we have proved that for ๐ก suciently small
supโโ(0,1]
ใ๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใโ โค[
2 .
In a similar way we can show that for ๐ก suciently small
ใ๐บ (b, ๐ฃ, ๐น ) โ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใ โค[
2 .
Since ใยทใโ โ ใยทใ weakly as โ โ 0, we have that ใ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใโ โ ใ๐บ (b, ๐ฃ, ๐ฃ๐2๐ 1๐ฃ๐ก )ใ as โ โ 0 forevery ๐ก โ (0, 1]. Altogether, we get that
limโโ0
(ใ๐บ (b, ๐ฃ, ๐น )ใliโ โ ใ๐บ (b, ๐ฃ, ๐น )ใli) โค [,
which in turn implies that ใ๐บ (b, ๐ฃ, ๐น )ใliโ โ ใ๐บ (b, ๐ฃ, ๐น )ใli as โ โ 0 since [ is arbitrary. Thus{ใยทใliโ }โโ0 converges weakly to ใยทใli. ๏ฟฝ
Acknowledgements
The authors would like to thank the Isaac Newton Institute for Mathematical Sciences, Cam-bridge, for support and hospitality during the programme โThe mathematical design of newmaterialsโ where work on this paper was completed. This programme was supported by EPSRCgrant no EP/K032208/1. F.O., T.R., and P.T. also thank the Centre International de Mathรฉmatiqueset dโInformatique de Toulouse (CIMI) and R.I. thanks the Max Planck Institute for Mathematics inthe Sciences for their kind hospitality.
Appendix A. Hรถlder spaces
The following equivalent characterization of Hรถlder norms relies on the โheat kernelโ of theoperator A.
Lemma A.1 ([IO19, Lemma 10, Remark 1]). Let ๐ be a periodic distribution on T2.
(1) For ๐ฝ โ (โ 32 , 0) \ {โ1,โ
12 }, we have
[๐ ]๐ฝ โผ sup๐ โ(0,1]
(๐
13)โ๐ฝ
โ ๐๐ โ๐ฟโ . (A.1)
In the critical cases ๐ฝ โ {โ1,โ 12 } we have
sup๐ โ(0,1]
(๐
13)โ๐ฝ
โ ๐๐ โ๐ฟโ . [๐ ]๐ฝ . (A.2)
(2) For ๐ฝ โ (โ 32 , 0) \ {โ1,โ
12 } and ๐ of vanishing average, we have
[๐ ]๐ฝ โผ sup๐ โ(0,1]
(๐
13)โ๐ฝ
โ๐A ๐๐ โ๐ฟโ . (A.3)
In the critical cases ๐ฝ โ {โ1,โ 12 } we have
28
sup๐ โ(0,1]
(๐
13)โ๐ฝ
โ๐A ๐๐ โ๐ฟโ . [๐ ]๐ฝ . (A.4)
28Indeed, using (A.2) and (1.18) we have
โA ๐๐ โ๐ฟโ = โ ๐๐2โ A๐ ๐
2โ๐ฟโ โค โ ๐๐
2โ๐ฟโ โA๐ ๐
2โ๐ฟ1 . (๐
13 )๐ฝ [๐ ]๐ฝ
1๐.
40 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
(3) For ๐ผ โ (0, 32 ) \ {1} we have
[๐ ]๐ผ โผ sup๐ โ(0,1]
(๐
13)โ๐ผ
โ๐A ๐๐ โ๐ฟโ . (A.5)
In the critical case ๐ผ = 1 we have29
sup๐ โ(0,1]
(๐
13)โ1
โ๐A ๐๐ โ๐ฟโ . [๐ ]1. (A.6)
In the case of periodic distributions ๐ of vanishing average on T2, one can consider the supremum
over all ๐ > 0 in (A.1), (A.2), (A.3), and (A.4), while in (A.5) and (A.6) the suprema over ๐ โ (0, 1)and ๐ > 0 are equivalent even for distributions of nonvanishing average.
We also have the following interpolation inequality.
Lemma A.2. For every โ 32 < ๐ฝ < 0 < ๐พ < ๐ผ < 3
2 there exists a constant ๐ถ > 0 such that the
following interpolation inequality holds for every ๐ : T2 โ R,
[๐ ]๐พ โค ๐ถ [๐ ]_๐ฝ[๐ ]1โ_๐ผ , (A.7)
where _ โ (0, 1) is given by ๐พ = _๐ฝ + (1 โ _)๐ผ . If ๐ has vanishing average in T2, (A.7) also holds for๐พ = 0 with [๐ ]๐พ replaced by โ ๐ โ๐ฟโ .
Proof. By (A.1) and (A.2), we have for every ๐ โ (0, 1] and ๐ฅ,๐ฆ โ T2:
|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | โค โ ๐๐ โ๐ฟโ + โ ๐2๐ โ๐ฟโ . [๐ ]๐ฝ(๐
13
)๐ฝ,
|๐1 ๐2๐ (๐ฅ) โ ๐1 ๐๐ (๐ฅ) | โค (โ ๐ 3๐2โ๐ฟโ + โ ๐๐
2โ๐ฟโ)
โซR2
|๐1๐๐2(๐ง) | d๐ง . [๐ ]๐ฝ
(๐
13
)๐ฝโ1,
|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) | โค 2โ ๐๐ โ๐ฟโ . [๐ ]๐ฝ(๐
13
)๐ฝ,
|๐1 ๐๐ (๐ฆ) (๐ฅ1 โ ๐ฆ1) | โค โ๐1๐๐2โ๐ฟ1 (R2) โ ๐๐2 โ๐ฟโ๐ (๐ฅ,๐ฆ) . [๐ ]๐ฝ
(๐
13
)๐ฝ๐ (๐ฅ,๐ฆ)๐
13,
|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) โ ๐1 ๐๐ (๐ฆ) (๐ฅ1 โ ๐ฆ1) | . [๐ ]๐ฝ(๐
13
)๐ฝmax
(1, ๐ (๐ฅ,๐ฆ)
๐13
),
(A.8)
where we used [IO19, equation (26)]. In the case ๐ผ โ (0, 1], we claim that for every ๐ โ (0, 1] and๐ฅ,๐ฆ โ T2:
|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | . [๐ ]๐ผ(๐
13)๐ผ
and |๐๐ (๐ฅ) โ ๐๐ (๐ฆ) | . [๐ ]๐ผ๐๐ผ (๐ฅ,๐ฆ). (A.9)
Indeed, by [IO19, equation (26)], we deduce
|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) | โคโซR2
|๐๐ (๐ง) | |๐ (๐ฅ โ ๐ง) โ ๐ (๐ฆ โ ๐ง) | d๐ง โค [๐ ]๐ผ๐ (๐ฅ,๐ฆ)๐ผโซR2
|๐๐ (๐ง) | d๐ง
. [๐ ]๐ผ๐๐ผ (๐ฅ,๐ฆ),
|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | โคโซR2
|๐๐ (๐ง) | |๐๐ (๐ฅ โ ๐ง) โ ๐๐ (๐ฅ) | d๐ง . [๐ ]๐ผโซR2
|๐๐ (๐ง) |๐ (๐ง, 0)๐ผ d๐ง
. [๐ ]๐ผ(๐
13)๐ผ.
29Indeed, since A๐๐ has vanishing average, we write A ๐๐ (๐ฅ) =โซR2 A๐๐ (๐ฆ) (๐ (๐ฅ โ ๐ฆ) โ ๐ (๐ฅ)) d๐ฆ and deduce via
Step 2 in the proof of Lemma 10 in [IO19] that
โA ๐๐ โ๐ฟโ โค [๐ ]๐ผโซR2
|A๐๐ (๐ฆ) |๐ (๐ฆ, 0)๐ผ d๐ฆ . [๐ ]๐ผ(๐
13) (โ3+๐ผ)
.
VARIATIONAL METHODS FOR A SINGULAR SPDE 41
In the case ๐ผ โ (1, 32 ), arguing as above, we also have for every ๐ โ (0, 1] and ๐ฅ,๐ฆ โ T2:|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) โ ๐1 ๐๐ (๐ฆ) (๐ฅ1 โ ๐ฆ1) | . [๐ ]๐ผ๐๐ผ (๐ฅ,๐ฆ),|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | โค
โซR2
|๐๐ (๐ง) | |๐๐ (๐ฅ โ ๐ง) โ ๐๐ (๐ฅ) + ๐1 ๐๐ (๐ฅ)๐ง1 | d๐ง . [๐ ]๐ผ(๐
13
)๐ผ,
|๐1 ๐2๐ (๐ฅ) โ ๐1 ๐๐ (๐ฅ) | โคโซR2
|๐1๐๐ /2(๐ง) | |๐3๐ /2(๐ฅ โ ๐ง) โ ๐๐ /2(๐ฅ โ ๐ง) | d๐ง . [๐ ]๐ผ(๐
13
)๐ผโ1,
(A.10)where we used
โซR2๐๐ d๐ง = 1 and
โซR2๐ง1๐๐ (๐ง) d๐ง = 0. To prove (A.7) we distinguish three dierent
cases for ๐พ .Case ๐พ โ (0, 1): First, assume that ๐ผ โ (0, 1]. Interpolating (A.8) and (A.9), we obtain for every๐ โ (0, 1] and ๐ฅ,๐ฆ โ T2:
|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | . [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐
13)๐พ
|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) | . [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐
13)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ .
If ๐0 โ Z is the largest integer such that 2โ๐03 โฅ ๐ (๐ฅ,๐ฆ), then for every ๐ โฅ ๐0
|๐2โ๐ (๐ฅ) โ ๐2โ๐ (๐ฆ) |โค |๐2โ๐ (๐ฅ) โ ๐2โ๐0 (๐ฅ) | + |๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) | + |๐2โ๐ (๐ฆ) โ ๐2โ๐0 (๐ฆ) |
โค๐โ1โ๏ธ๐=๐0
|๐2โ(๐+1) (๐ฅ) โ ๐2โ๐ (๐ฅ) | + |๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) | +๐โ1โ๏ธ๐=๐0
|๐2โ(๐+1) (๐ฆ) โ ๐2โ๐ (๐ฆ) |
. [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐โ1โ๏ธ๐=๐0
(2โ
๐3)๐พ
+(2โ
๐03)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ)
. [๐ ]_๐ฝ[๐ ]1โ_๐ผ
((2โ
๐03)๐พ
+(2โ
๐03)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ). [๐ ]_
๐ฝ[๐ ]1โ_๐ผ ๐ (๐ฅ,๐ฆ)๐พ , (A.11)
which in turn implies (A.7) by letting ๐ โ โ.In the case ๐ผ โ (1, 32 ), rst, one needs to choose ๐0 โ Z such that 2โ
๐03 โฅ ^๐ (๐ฅ,๐ฆ) > 2โ
๐0+13
with a constant ^ > 0, depending only on ๐พ , which we x below. Second, one needs to estimatethe intermediate term |๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) | dierently. For this, we need to use that for every๐ โ (0, 1], by (A.1), (A.2), Denition 1.13, and since ๐พ < 1,
โ๐1 ๐๐ โ๐ฟโ . [๐1 ๐ ]๐พโ1(๐13 )๐พโ1 โค ๐0 [๐ ]๐พ (๐
13 )๐พโ1
where ๐0 > 0 depends only on ๐พ . By interpolating between (A.8) and (A.10), we estimate theintermediate term for a constant ๐ถ > 0 (depending on ๐ผ , ๐ฝ , ๐พ ) by,
|๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) |โค |๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) โ ๐1 ๐2โ๐0 (๐ฆ) (๐ฅ1 โ ๐ฆ1) | + |๐1 ๐2โ๐0 (๐ฆ) (๐ฅ1 โ ๐ฆ1) |
โค ๐ถ [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(2โ
๐03)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ max(1, ๐ (๐ฅ,๐ฆ)
2โ๐03
)_+ ๐0 [๐ ]๐พ (2โ
๐03 )๐พโ1๐ (๐ฅ,๐ฆ)
โค ๐ถ^ [๐ ]_๐ฝ [๐ ]1โ_๐ผ ๐ (๐ฅ,๐ฆ)๐พ + ๐0 [๐ ]๐พ^๐พโ1๐ (๐ฅ,๐ฆ)๐พ .
Choosing ^ > 0 such that ๐0^๐พโ1 = 12 and proceeding as in (A.11) (where now the change of ๐0
aects the implicit constant by a factor depending on ^), after passing to the limit ๐ โ โ weobtain
|๐ (๐ฅ) โ ๐ (๐ฆ) | โค(๐ถ [๐ ]_
๐ฝ[๐ ]1โ_๐ผ + 1
2 [๐ ]๐พ)๐ (๐ฅ,๐ฆ)๐พ .
Dividing by ๐ (๐ฅ,๐ฆ)๐พ and taking the supremum over ๐ฅ โ ๐ฆ we nally obtain (A.7).
42 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Case ๐พ โ (1, 32 ): Since ๐ผ > ๐พ we also have ๐ผ โ (1, 32 ). Interpolating (A.8) and (A.10), we obtain forevery ๐ โ (0, 1] and ๐ฅ,๐ฆ โ T2,
|๐2๐ (๐ฅ) โ ๐๐ (๐ฅ) | . [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐
13)๐พ,
|๐1 ๐2๐ (๐ฅ) โ ๐1 ๐๐ (๐ฅ) | . [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐
13)๐พโ1
,
|๐๐ (๐ฅ) โ ๐๐ (๐ฆ) โ ๐1 ๐๐ (๐ฆ) (๐ฅ1 โ ๐ฆ1) | . [๐ ]_๐ฝ[๐ ]1โ_๐ผ
(๐
13)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ max(1, ๐ (๐ฅ,๐ฆ)
๐13
)_.
If ๐0 โ Z is the largest integer such that 2โ๐03 โฅ ๐ (๐ฅ,๐ฆ), the same argument as in the previous
case yields for ๐ โฅ ๐0,|๐2โ๐ (๐ฅ) โ ๐2โ๐ (๐ฆ) โ ๐1 ๐2โ๐ (๐ฆ) (๐ฅ1 โ ๐ฆ1) |
โค |๐2โ๐0 (๐ฅ) โ ๐2โ๐0 (๐ฆ) โ ๐1 ๐2โ๐0 (๐ฆ) (๐ฅ1 โ ๐ฆ1) | + |๐2โ๐ (๐ฅ) โ ๐2โ๐0 (๐ฅ) |+ |๐2โ๐ (๐ฆ) โ ๐2โ๐0 (๐ฆ) | + |๐1 ๐2โ๐ (๐ฆ) โ ๐1 ๐2โ๐0 (๐ฆ) | |๐ฅ1 โ ๐ฆ1 |
. [๐ ]_๐ฝ[๐ ]1โ_๐ผ
((2โ
๐03)_๐ฝ
๐ (๐ฅ,๐ฆ) (1โ_)๐ผ +๐โ1โ๏ธ๐=๐0
(2โ
๐3)๐พ
+ ๐ (๐ฅ,๐ฆ)๐โ1โ๏ธ๐=๐0
(2โ
๐3)๐พโ1)
. [๐ ]_๐ฝ[๐ ]1โ_๐ผ ๐ (๐ฅ,๐ฆ)๐พ ,
which yields (A.7) by letting ๐ โ โ.Case ๐พ = 1: Take a sequence (๐พ๐) โ (1, 32 ) such that ๐พ๐ โ 1, and consider the correspondingexponents _๐ โ _. Then by [IO19, Remark 2] and the previous case, we have
[๐ ]1 . [๐ ]๐พ๐ . [๐ ]_๐๐ฝ[๐ ]1โ_๐๐ผ ,
with implicit constants independent of ๐. We can therefore perform the limit ๐ โ โ to concludethe estimate for ๐พ = 1.Case ๐พ = 0 and ๐ has vanishing average: If [๐ ]๐ผ = 0, then ๐ โก 0,30 so (A.7) holds trivially. Assumethat [๐ ]๐ผ โ 0. If ๐ผ โ (0, 1], we have for every ๐ > 0,
|๐ (๐ฅ) | โค |๐ (๐ฅ) โ ๐๐ (๐ฅ) | + |๐๐ (๐ฅ) | .โซR2
|๐๐ (๐ง) | |๐ (๐ฅ โ ๐ง) โ ๐ (๐ฅ) | d๐ง +(๐
13)๐ฝ
[๐ ]๐ฝ
.(๐
13)๐ผ
[๐ ]๐ผ +(๐
13)๐ฝ
[๐ ]๐ฝ ,
while if ๐ผ โ (1, 32 ),
|๐ (๐ฅ) | โค |๐ (๐ฅ) โ ๐๐ (๐ฅ) | + |๐๐ (๐ฅ) | .โซR2
|๐๐ (๐ง) | |๐ (๐ฅ โ ๐ง) โ ๐ (๐ฅ) + ๐1 ๐ (๐ฅ)๐ง1 | d๐ง +(๐
13)๐ฝ
[๐ ]๐ฝ
.(๐
13)๐ผ
[๐ ]๐ผ +(๐
13)๐ฝ
[๐ ]๐ฝ ,
where we usedโซR2๐ง1๐๐ (๐ง) d๐ง = 0 and Lemma A.1 in the case of distributions with vanishing
average, as ๐ can be larger than 1. Choosing ๐ 13 =
( [๐ ]๐ฝ[๐ ]๐ผ
) 1๐ผโ๐ฝ leads to the conclusion. ๏ฟฝ
Remark A.3. One can also prove that for โ 12 < ๐ฝ < 1 < ๐ผ < 3
2 the interpolation estimate
โ๐1 ๐ โ๐ฟโ . [๐ ]_๐ฝ[๐ ]1โ_๐ผ (A.12)
holds for _ โ (0, 1) given by 1 = _๐ฝ + (1 โ _)๐ผ . Indeed, by Lemma A.2 (the case ๐พ = 0) we knowthat
โ๐1 ๐ โ๐ฟโ . [๐1 ๐ ]_๐ฝโ1 [๐1 ๐ ]1โ_๐ผโ1.
30This is clear for ๐ผ โ (0, 1) since ๐ has vanishing average. For ๐ผ โ (1, 32 ) notice that by [IO19, Lemma 12],โ๐1 ๐ โ๐ฟโ = 0, hence by Denition 1.12 ๐ is constant, and this constant is 0 since ๐ has vanishing average.
VARIATIONAL METHODS FOR A SINGULAR SPDE 43
By Denition 1.13, we have [๐1 ๐ ]๐ฝโ1 . [๐ ]๐ฝ and by [IO19, Lemma 12], we know [๐1 ๐ ]๐ผโ1 . [๐ ]๐ผ ,so the desired estimate follows.
We also need the following lemma for the Hilbert transform acting on Hรถlder spaces.
Lemma A.4.(1) For ๐ฝ โ (โ 3
2 , 0) and Y > 0 such that ๐ฝ โ Y โ (โ 32 , 0), there exists a constant ๐ถ > 0 such that
for every periodic distribution ๐ ,
[๐ 1 ๐ ]๐ฝโY โค ๐ถ [๐ ]๐ฝ . (A.13)
(2) For ๐ผ โ (0, 32 ) and Y > 0 such that ๐ผ โ Y โ (0, 32 ) there exists a constant ๐ถ > 0 such that for
every ๐ : T2 โ R,[๐ 1 ๐ ]๐ผโY โค ๐ถ [๐ ]๐ผ . (A.14)
Proof. To prove (A.13), we claim that for every Y โ (0, 32 ) and ๐ โ (0, 1], we have that
โ๐ 1 ๐๐ โ๐ฟโ .(๐
13)โY
โ ๐๐2โ๐ฟโ .
Indeed, if we write ฮจ๐ for the periodization of ๐๐ , by the semigroup property and Youngโsinequality for convolution we have for ๐ = 5
2Y > 1,
โ๐ 1 ๐๐ โ๐ฟโ . โ ๐๐2โ๐ฟ๐ โ๐ 1ฮจ๐
2โ๐ฟ
๐๐โ1. โ ๐๐
2โ๐ฟ๐ โฮจ๐
2โ๐ฟ
๐๐โ1. โ ๐๐
2โ๐ฟโ
(๐
13)โ 5
2๐
where we used that the Hilbert transform is bounded31 on ๐ฟ๐
๐โ1 (T2) for ๐
๐โ1 > 1 and the bound
โฮจ๐2โ๐ฟ
๐๐โ1. (๐ 1
3 )โ52๐ , which follows from Remark 1.11. Then (A.13) follows via the characterization
of negative Hรถlder norms (A.1) and (A.2) if ๐ฝ โ ๐ โ โ1,โ 12 . In those cases, consider ๐พ โ (๐ฝ โ ๐, ๐ฝ)
and use the previous case together with [IO19, Remark 2].Equation (A.14) is essentially [IO19, Lemma 7], noting that we can assume that ๐ is of vanishing
average, as ๐ 1 annihilates constants and [๐ โโซT2๐ d๐ฅ]๐ผ โค [๐ ]๐ผ . ๏ฟฝ
Lemma A.5. Let ๐ผ โ (โ 32 ,
32 ) \ {0} and ๐ > 0 such that ๐ผ โ ๐ โ (โ 3
2 ,32 ) \ {โ1,โ
12 , 0, 1}. There exists
a constant ๐ถ > 0 such that for every periodic ๐ โ C๐ผ,
[|๐1 |๐ ๐ ]๐ผโ๐ โค ๐ถ [๐ ]๐ผ .
Proof. Without loss of generality, we may assume that ๐ is of vanishing average because [๐ โโซT2๐ d๐ฅ]๐ผ โค [๐ ]๐ผ and [|๐1 |๐ ๐ ]๐ผโ๐ is invariant by adding a constant to ๐ . Then by the semigroup
property, |๐1 |๐ ๐๐ =(๐2)โ ๐
3 ๐๐2โ (|๐1 |๐ ๐ )๐
2for every๐ โ (0, 1] and since |๐1 |๐ ๐ โ ๐ฟ1(R2), we deduce
โ๐A|๐1 |๐ ๐๐ โ๐ฟโ .(๐
13
)โ๐ โ๐A ๐๐
2โ๐ฟโ . Hence, we obtain that(
๐13)โ(๐ผโ๐ )
โ๐A|๐1 |๐ ๐๐ โ๐ฟโ .(๐
13)โ๐ผ
โ๐A ๐๐2โ๐ฟโ,
and the conclusion follows by Lemma A.1. ๏ฟฝ
Lemma A.6. Let ๐ผ โ (โ 32 ,
32 ) \ {0}. For every sequence {๐๐}๐โฅ1 โ C๐ผ
with sup๐โฅ1 [๐๐]๐ผ < โ, there
exists ๐ โ C๐ผwith
[๐ ]๐ผ โค lim inf๐โโ
[๐๐]๐ผ ,
such that ๐๐ โ ๐ in C๐ผโYfor every Y > 0 along a subsequence. In particular, the embedding
C๐ผ โฉโ C๐ผโYis compact.
31This follows from the fact that the Hilbert transform ๐ 1 is bounded on ๐ฟ๐ (R2) for any ๐ โ (1,โ) and thetransference of multipliers method [Gra14, Theorem 4.3.7].
44 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Proof. First, assume that ๐ผ โ Y โ โ1,โ 12 , 0, 1. Let {๐๐}๐โฅ1 โ C๐ผ such that๐พ := sup
๐โฅ1[๐๐]๐ผ < โ,
and, if ๐ผ โ (0, 32 ), we assume in addition that {โ ๐๐ โ๐ฟโ}๐โฅ1 is uniformly bounded (hence, up tosubtraction, we may assume that ๐๐ has zero average for any ๐ โ N).
By [IO19, Lemma 13] there exists ๐ โ C๐ผ such that ๐๐ โ ๐ (along a subsequence) in the senseof distributions and
[๐ ]๐ผ โค lim inf๐โโ
[๐๐]๐ผ โค ๐พ.
For ๐, ๐ก > 0 we have thatโ(A ๐ โ A ๐๐)๐ โ๐ฟโ โค โ(A ๐ โ A ๐๐ก )๐ โ๐ฟโ + โ(A ๐ โ A ๐๐)๐ก+๐ โ๐ฟโ
+ โ((A ๐๐)๐ก โ A ๐๐)๐ โ๐ฟโ . (A.15)By (A.3), (A.5), and (A.16) below the following estimates hold
โ(A ๐ โ A ๐๐ก )๐ โ๐ฟโ .(๐
13)๐ผโYโ3
[๐ โ ๐๐ก ]๐ผโY . ๐พ(๐
13)๐ผโYโ3 (
๐ก13)Y,
โ((A ๐๐)๐ก โ A ๐๐)๐ โ๐ฟโ .(๐
13)๐ผโYโ3
[(๐๐)๐ก โ ๐๐]๐ผโY . ๐พ(๐
13)๐ผโYโ3 (
๐ก13)Y.
By Youngโs inequality for convolution and (1.18) we further have that
โ(A ๐ โ A ๐๐)๐ก+๐ โ๐ฟโ .(๐
13)๐ผโYโ3
โ(A ๐ โ A ๐๐)๐ก โ๐ฟ
52(3โ๐ผ+Y )
.
Since ๐๐ โ ๐ in the sense of distributions, (A ๐ โ A ๐๐)๐ก โ 0 as ๐ โ โ pointwise for every๐ก โ (0, 1], and by (A.3) and (A.5) we know that
โ(A ๐ โ A ๐๐)๐ก โ๐ฟโ .(๐ก13)๐ผโ3
[๐ โ ๐๐]๐ผ . ๐พ(๐ก13)๐ผโ3
.
Hence, by dominated convergence theorem, โ(A ๐ โ A ๐๐)๐ก โ๐ฟ
52(3โ๐ผ+Y )
โ 0 as ๐ โ โ for every๐ก โ (0, 1]. Taking ๐ โ โ in (A.15) and using again (A.3) and (A.5) we obtain that
lim sup๐โโ
[๐ โ ๐๐]๐ผโY . ๐พ(๐ก13)Y,
which completes the proof if we let ๐ก โ 0.If ๐ผ โ Y โ {โ1,โ 1
2 , 0, 1}, consider ๐พ โ (๐ผ โ Y, ๐ผ); in view of [IO19, Remark 2] and the aboveresult we then have [๐ โ ๐๐]๐ผโY . [๐ โ ๐๐]๐พ โ 0 as ๐ โ โ. ๏ฟฝ
Proposition A.7. For every ๐ผ โ (โ 32 ,
32 ) \ {0} and Y > 0 such that ๐ผ โ Y โ (โ 3
2 ,32 ) \ {โ1,โ
12 , 0, 1}
the following estimate holds:
[๐ โ ๐๐ก ]๐ผโY .(๐ก13)Y
[๐ ]๐ผ . (A.16)
Proof. To prove (A.16) we use the denition of ๐๐ก and the semigroup property to estimate for๐ก,๐ โ (0, 1]
โA (๐ โ ๐๐ก )๐ โ๐ฟโ โคโซ ๐ก+๐
๐
โA๐๐ ๐๐ โ๐ฟโ d๐ =โซ ๐ก+๐
๐
โA2 ๐๐ โ๐ฟโ d๐
=
โซ ๐ก+๐
๐
โA๐ ๐ 2โ A ๐ ๐
2โ๐ฟโ d๐ โค
โซ ๐ก+๐
๐
โA๐ ๐ 2โ๐ฟ1 โA ๐ ๐
2โ๐ฟโ d๐ .
Since โA๐ ๐ 2โ๐ฟ1 . ๐ โ1, (A.3) and (A.5) imply that
โA (๐ โ ๐๐ก )๐ โ๐ฟโ . [๐ ]๐ผโซ ๐ก+๐
๐
(๐ 13 )โ3+๐ผ d๐
๐ . [๐ ]๐ผ
(๐
13)โ3+๐ผโY โซ ๐ก+๐
๐
(๐ 13 )Y d๐
๐
. [๐ ]๐ผ(๐
13)โ3+๐ผโY (
๐ก13)Y,
VARIATIONAL METHODS FOR A SINGULAR SPDE 45
so that (A.16) follows from (A.3) and (A.5). ๏ฟฝ
Appendix B. Besov spaces
In the next lemma we summarize some useful properties of the Besov seminorms that we oftenuse in this article.
Lemma B.1. Let 0 < ๐ < ๐ โฒ โค 1, 1 โค ๐ โค ๐ < โ, and ๐ โ {1, 2}. The following estimates hold
โ ๐ โ ยคB๐ โฒ๐ ;1
โค [๐ ]๐ โฒ , (B.1)
โ ๐ โ ยคB๐ ๐ ;2
โค [๐ ] 32๐ , (B.2)
โ ๐ โ ยคB๐ ๐ ;๐
โค โ ๐ โ ยคB๐ โฒ๐ ;๐
and โ ๐ โ ยคB๐ โฒ๐ ;๐
โค โ ๐ โ ยคB๐ โฒ๐;๐, (B.3)
โ|๐๐ |๐ ๐ โ๐ฟ๐ โค ๐ถ (๐ , ๐ โฒ)โ ๐ โ ยคB๐ โฒ๐ ;๐, (B.4)
for every function ๐ : T2 โ R, where the constant ๐ถ (๐ , ๐ โฒ) > 0 depends only on ๐ and ๐ โฒ.
Proof. Estimates (B.1) and (B.2) are immediate from Denitions 1.12 and 2.1. Both estimates in (B.3)follow from Denition 2.1 and Jensenโs inequality. To prove (B.4) we rst notice that by a simplecalculation of the Fourier coecients we have the identity
|๐๐ |๐ ๐ (๐ฅ) = ๐๐ โซR
๐โ๐ ๐ (๐ฅ)|โ |๐ +1 dโ, ๐ฅ โ T2,
for some constant ๐๐ > 0 which depends only on ๐ , where we interpret the integral as a principlevalue. Then by Minkowskiโs inequality we get
โ|๐๐ |๐ ๐ โ๐ฟ๐ โค ๐๐ โซR
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
|โ | (๐ +1)๐d๐ฅ
) 1๐
dโ
โค ๐๐ โซ|โ | โค1
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
|โ | (๐ +1)๐d๐ฅ
) 1๐
dโ + ๐๐ โซ|โ | โฅ1
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
|โ | (๐ +1)๐d๐ฅ
) 1๐
dโ.
The rst term in the last inequality is estimated byโซ|โ | โค1
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
|โ | (๐ +1)๐d๐ฅ
) 1๐
dโ = 2โซ 1
0
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
โ (๐ +1)๐d๐ฅ
) 1๐
dโ
โค 2โซ 1
0
โ๐ โฒโ๐
โdโ โ ๐ โ ยคB๐ โฒ
๐ ;๐=
2๐ โฒ โ ๐ โ ๐ โ ยคB๐ โฒ
๐ ;๐,
where we also used translation invariance of the torus and that ๐ โฒ > ๐ . The second term isestimated by Minkowskiโs inequalityโซ
|โ | โฅ1
(โซT2
|๐โ๐ ๐ (๐ฅ) |๐
|โ | (๐ +1)๐d๐ฅ
) 1๐
dโ โค 4โซ โ
1
1โ๐ +1
dโ โ ๐ โ๐ฟ๐ =4๐ โ ๐ โ๐ฟ๐ ,
where we used again translation invariance of the torus. If ๐ has vanishing average in ๐ฅ ๐ , thenโ ๐ โ๐ฟ๐ โค โ ๐ โ ยคB๐ โฒ
๐ ;๐. Otherwise โ ๐ โ
โซ 10 ๐ d๐ฅ ๐ โ๐ฟ๐ โค โ ๐ โ ยคB๐ โฒ
๐ ;๐and we can replace ๐ by ๐ โ
โซ 10 ๐ d๐ฅ ๐ .
This completes the proof. ๏ฟฝ
Lemma B.2.(i) For every ๐ โ (0, 1), ๐ โฅ 1 and ๐ , ๐ : T2 โ R we have
โ ๐ ๐โ ยคB๐ ๐ ;1
โค โ ๐ โ ยคB๐ ๐ ;1โ๐โ๐ฟโ + โ ๐ โ๐ฟ๐ [๐]๐ ,
โ ๐ ๐โ ยคB๐ ๐ ;2
โค โ ๐ โ ยคB๐ ๐ ;2โ๐โ๐ฟโ + โ ๐ โ๐ฟ๐ [๐] 3
2๐ .
46 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
(ii) For every ๐ โ (0, 1), there exists a constant ๐ถ (๐ ) > 0 depending only on ๐ such that for every
Y โ (0, 1 โ ๐ ) and ๐ , ๐ : T2 โ R we have
โ|๐1 |๐ (๐ ๐)โ๐ฟ2 โค 2โ|๐1 |๐ ๐ โ๐ฟ2 โ๐โ๐ฟโ + ๐ถ (๐ )โYโ ๐ โ๐ฟ2 [๐]๐ +Y,
โ|๐2 |๐ (๐ ๐)โ๐ฟ2 โค 2โ|๐2 |๐ ๐ โ๐ฟ2 โ๐โ๐ฟโ + ๐ถ (๐ )โYโ ๐ โ๐ฟ2 [๐] 3
2 (๐ +Y).
Proof. (i) For ๐ โ {1, 2} we have that
๐โ๐ (๐ ๐) (๐ฅ) = (๐โ๐ ๐ ) (๐ฅ)๐(๐ฅ + โ๐ ๐ ) + ๐ (๐ฅ) (๐โ๐ ๐) (๐ฅ),
hence by Minkowskiโs inequality, โ๐โ๐ (๐ ๐)โ๐ฟ๐ โค โ(๐โ๐ ๐ )๐(ยท + โ๐ ๐ )โ๐ฟ๐ + โ ๐ (๐โ๐ ๐)โ๐ฟ๐ . Itfollows that โ ๐ ๐โ ยคB๐
๐ ;๐โค โ ๐ โ ยคB๐
๐ ;๐โ๐โ๐ฟโ + โ ๐ โ๐ฟ๐ [๐]๐ ๐ with ๐ 1 = ๐ and ๐ 2 = 3
2๐ .(ii) By (2.2) we know that
โ|๐๐ |2(๐ ๐)โ2๐ฟ2 = ๐๐ โซR
1|โ |2๐
โซT2
|๐โ๐ (๐ ๐) (๐ฅ) |2 d๐ฅdโ|โ | .
Similarly to (i) we can prove that
๐๐
โซR
1|โ |2๐
โซT2
|๐โ๐ (๐ ๐) (๐ฅ) |2 d๐ฅdโ|โ |
โค 2๐๐ โซR
1|โ |2๐
โซT2
|๐โ๐ ๐ (๐ฅ) |2 d๐ฅdโ|โ | โ๐โ
2๐ฟโ + 2๐๐ โ ๐ โ2๐ฟ2
โซR
1|โ |2๐ sup
๐ฅ โT2|๐โ๐ ๐(๐ฅ) |2
dโ|โ |
= 2โ|๐๐ |๐ ๐ โ2๐ฟ2 โ๐โ2๐ฟโ + 2๐๐ โ ๐ โ2๐ฟ2
โซR
1|โ |2๐ sup
๐ฅ โT2|๐โ๐ ๐(๐ฅ) |2
dโ|โ | ,
where in the last step we used again (2.2). Using the periodicity of ๐ and the fact thatfor โ > 1 we can write โ = โfr + โint with โfr โ (0, 1] and โint โ Z, we notice that|๐โ๐ ๐(๐ฅ) | = |๐โfr
๐๐(๐ฅ) | . [๐]๐ ๐โ
๐ ๐
fr . [๐]๐ ๐ with ๐ ๐ โ {๐ + Y, 32 (๐ + Y)}. Then the result followsfrom (โซ 1
0+โซ โ
1
)1โ2๐
sup๐ฅ โT2
|๐โ๐ ๐(๐ฅ) |2dโโ.
(1Y+
โซ โ
1
dโโ1+2๐
)[๐]2๐ ๐ .
๏ฟฝ
Lemma B.3. For every ๐ โ (0, 1) and ๐พ โ (๐ , 1], there exists a constant ๐ถ (๐ ,๐พ) > 0 depending onlyon ๐ and ๐พ such that the following duality estimate holds for every ๐ , ๐ : T2 โ R,๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2๐ ๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค ๐ถ (๐ ,๐พ) (โ|๐1 |๐พ ๐ โ๐ฟ1 + โ|๐2 |
23๐พ ๐ โ๐ฟ1 + โ ๐ โ๐ฟ1
)[๐]โ๐ .
Proof. By the mean value theorem and the denition of the kernel๐๐ we have thatโซT2๐ (๐ โ ๐1) d๐ฅ =
โซ 12
0
โซT2๐ ๐๐๐2๐ d๐ฅ d๐ =
โซ 12
0
โซT2๐
(|๐1 |3 โ ๐22
)๐2๐ d๐ฅ d๐ .
VARIATIONAL METHODS FOR A SINGULAR SPDE 47
Let๐ (1) = |๐1 |3โ๐พ๐ and๐ (2) = |๐2 |2โ23๐พ๐ . Recalling that |๐1 |๐ผ๐, |๐2 |๐ผ๐ โ ๐ฟ1(R2) for every ๐ผ โฅ 0,32
integrating by parts and using the semigroup property we obtain by (A.1) and Remark 1.11,๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ 12
0
โซT2๐
(|๐1 |3 โ ๐22
)๐2๐ d๐ฅ d๐
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ =๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ 1
2
0
โซT2
(|๐1 |3 โ ๐22
)๐๐ ๐๐ d๐ฅ d๐
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ.๐
โซ 12
0
โซT2๐ โ 3โ๐พ
3
๏ฟฝ๏ฟฝ๏ฟฝ|๐1 |๐พ ๐ โ๐ (1)๐
๏ฟฝ๏ฟฝ๏ฟฝ [๐]โ๐ ๐ โ ๐ 3 d๐ฅ d๐
+โซ 1
2
0
โซT2๐ โ 3โ๐พ
3
๏ฟฝ๏ฟฝ๏ฟฝ|๐2 | 23๐พ ๐ โ๐ (2)๐
๏ฟฝ๏ฟฝ๏ฟฝ [๐]โ๐ ๐ โ ๐ 3 d๐ฅ d๐
.๐ (โ|๐1 |๐พ ๐ โ๐ฟ1 + โ|๐2 |
23๐พ ๐ โ๐ฟ1
)[๐]โ๐
โซ 12
0๐ โ 3โ๐พ+๐
3 d๐ .
The proof is complete since the last integral is nite for ๐พ > ๐ and by (A.1) we also have theestimate ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2๐ ๐1d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ ๐ โ๐ฟ1 โ๐1โ๐ฟโ .๐ โ ๐ โ๐ฟ1 [๐]โ๐ .
๏ฟฝ
The following Lemma establishes an optimal Sobolev embedding with respect to our anisotropicmetric. Recall that in our context the (scaling) dimension of the space is dim = 5
2 , and ๐2 costs asmuch as 3
2 of ๐1. Therefore, the critical exponent of the embedding ๐ป 1anisotropic โ ๐ฟ2
โ is given by2โ = 2 dim
dimโ2 = 10.
Lemma B.4. There exists a constant ๐ถ > 0 such that for any function ๐ : T2 โ R of vanishing
average in ๐ฅ1,
โ ๐ โ๐ฟ10 โค ๐ถ(โ๐1 ๐ โ๐ฟ2 + โ|๐2 |
23 ๐ โ๐ฟ2
), (B.5)
โ ๐ โ๐ฟ103โค ๐ถ
(โ|๐1 |
12 ๐ โ๐ฟ2 + โ|๐2 |
13 ๐ โ๐ฟ2
), (B.6)
โ ๐ โ๐ฟ
51โ2Y
โค ๐ถ(โ|๐1 |
34+๐ ๐ โ๐ฟ2 + โ|๐2 |
23 (
34+๐) ๐ โ๐ฟ2
), Y โ [0, 14 ) . (B.7)
Proof. We rst prove (B.5). For that, by the one-dimensional Gagliardo-Nirenberg-Sobolev in-equalities, using that ๐ (ยท, ๐ฅ2) has vanishing average, we have that for every ๐ฅ1, ๐ฅ2 โ [0, 1),
โ ๐ (ยท, ๐ฅ2)โ๐ฟโ๐ฅ1 . โ๐1 ๐ (ยท, ๐ฅ2)โ16๐ฟ2๐ฅ1
โ ๐ (ยท, ๐ฅ2)โ56๐ฟ10๐ฅ1,
โ ๐ (๐ฅ1, ยท)โ๐ฟโ๐ฅ2 . โ|๐2 |23 ๐ (๐ฅ1, ยท)โ
38๐ฟ2๐ฅ2
โ ๐ (๐ฅ1, ยท)โ58๐ฟ10๐ฅ2
+ โ ๐ (๐ฅ1, ยท)โ๐ฟ1๐ฅ2 .
Hence, Hรถlderโs inequality implies โ ๐ โ๐ฟโ๐ฅ1 ๐ฟ6๐ฅ2 . โ๐1 ๐ โ16๐ฟ2โ ๐ โ
56๐ฟ10, โ ๐ โ๐ฟโ๐ฅ2 ๐ฟ4๐ฅ1 . โ|๐2 |
23 ๐ โ
38๐ฟ2โ ๐ โ
58๐ฟ10
+ โ ๐ โ๐ฟ4 . โ|๐2 |23 ๐ โ
38๐ฟ2โ ๐ โ
58๐ฟ10
+ โ ๐ โ๐ฟ10 .
Therefore, we obtain
โ ๐ โ๐ฟ10 โค โ ๐ โ๐ฟโ๐ฅ1 3
5
๐ฟ6๐ฅ2
โ ๐ โ๐ฟโ๐ฅ2 25
๐ฟ4๐ฅ1
. โ๐1 ๐ โ110๐ฟ2โ|๐2 |
23 ๐ โ
320๐ฟ2โ ๐ โ
34๐ฟ10
+ โ๐1 ๐ โ110๐ฟ2โ ๐ โ
910๐ฟ10.
32As explained in [IO19, Proof of Lemma 10], the kernel๐ factorizes into a Gaussian in ๐ฅ2 and a kernel ๐ (๐ฅ1) thatis smooth and |๐ฅ1 |3๐๐1๐ โ ๐ฟโ (R) for every ๐ โฅ 0 because in Fourier space b๐1 ๐
โ|b1 |3 has integrable derivatives up toorder 3.
48 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
It follows by Youngโs inequality that for any Y โ (0, 1) there exists a constant ๐ถ (Y) > 0 such that
โ ๐ โ๐ฟ10 โค Yโ ๐ โ๐ฟ10 +๐ถ (Y)(โ๐1 ๐ โ๐ฟ2 + โ|๐2 |
23 ๐ โ๐ฟ2
),
from which (B.5) follows.For the second inequality observe that 3
10 = 12 ยท
110 +
12 ยท
12 , so that (B.6) follows from complex
interpolation (with change of measure). Indeed, by inequality (B.5) in the form
โ ๐ โ2๐ฟ10 .
โ๏ธ๐โ(2๐Z)2
( |๐1 |2 + |๐2 |43 ) |๐ (๐) |2,
it follows that Id : ๐ฟ2((2๐Z)2,๐ค d๐) โ ๐ฟ10(T2, d๐ฅ) is bounded, where ๐ค (๐) := |๐1 |2 + |๐2 |43
and ๐ is the counting measure, while Parsevalโs identity โ ๐ โ2๐ฟ2
=โ
๐โ(2๐Z)2 |๐ (๐) |2 shows thatId : ๐ฟ2((2๐Z)2, d๐) โ ๐ฟ2(T2, d๐ฅ) is bounded. Hence, by interpolation (see [BL76, Corollary5.5.4]), it follows that Id : ๐ฟ2((2๐Z)2,๐ค 1
2 d๐) โ ๐ฟ103 (T2, d๐ฅ) is bounded, which implies (B.6). The
bound (B.7) follows similarly by interpolation. ๏ฟฝ
Lemma B.5. There exists a constant ๐ถ > 0 such that for every ๐ 1 โ [0, 1] and ๐ 2 โ [0, 23 ] with๐ 1 + 3
2๐ 2 โค 1 and every periodic function ๐ : T2 โ R of vanishing average in ๐ฅ1 the following holds
โ|๐1 |๐ 1 |๐2 |๐ 2 ๐ โ2๐ฟ2 โค ๐ถH(๐ ).In particular, any sublevel set of E (respectivelyH ) overW is relatively compact in ๐ฟ2.
Proof. The desired estimate is immediate by Hรถlderโs inequality in Fourier space and (2.15). Toprove that the sublevel sets of E (respectively H ) over W are relatively compact, we notice thatH(๐ ) controls โ|๐1 |
12 ๐ โ๐ฟ2 and โ|๐2 |
12 ๐ โ๐ฟ2 , hence also โ ๐ โ๐ฟ2 since ๐ has vanishing average. By the
compact embedding ๐ป 12 โ ๐ฟ2 and (2.14), we deduce that any sublevel set of E (respectively H )
overW is relatively compact in ๐ฟ2. ๏ฟฝ
Below we use the following notation for ๐ > 0 and a periodic function ๐ : T2 โ R withvanishing average in ๐ฅ1,
โ|๐ โ|2๐ :=โซT2
( |๐1 |๐ ๐ )2 d๐ฅ +โซT2
(|๐1 |โ
๐ 2 |๐2 |๐ ๐
)2d๐ฅ . (B.8)
Lemma B.6. Let ๐ > 0. There exists a constant๐ถ > 0 such that for any periodic function ๐ : T2 โ Rwith vanishing average in ๐ฅ1 there holds
โ|๐1 |๐ ๐ โ๐ฟ2 + โ|๐2 |23๐ ๐ โ๐ฟ2 โค ๐ถ โ|๐ โ|๐ . (B.9)
Proof. Note that by the denition of โ|๐ โ|๐ we only have to bound โ|๐2 |23๐ ๐ โ๐ฟ2 . โ|๐ โ|๐ . This
follows easily by an application of Hรถlderโs inequality in Fourier space. Indeed, by (2.2) we havethat33 โซ
T2| |๐2 |
23๐ ๐ |2d๐ฅ =
โ๏ธ๐โ(2๐Z)2
|๐2 |43๐ |๐ (๐) |2 =
โ๏ธ๐โ(2๐Z)2
|๐1 |โ23๐ |๐2 |
43๐ |๐ (๐) | 43 |๐1 |
23๐ |๐ (๐) | 23
โค ยฉยญยซโ๏ธ
๐โ(2๐Z)2|๐1 |โ๐ |๐2 |2๐ |๐ (๐) |2
ยชยฎยฌ23 ยฉยญยซ
โ๏ธ๐โ(2๐Z)2
|๐1 |2๐ |๐ (๐) |2ยชยฎยฌ
13
=
(โซT2
| |๐1 |โ๐ 2 |๐2 |๐ ๐ |2d๐ฅ
) 23(โซT2
|๐1 ๐ |๐ d๐ฅ) 1
3
โค 23
โซT2
| |๐1 |โ๐ 2 |๐2 |๐ ๐ |2d๐ฅ + 1
3
โซT2
| |๐1 |๐ ๐ |2 d๐ฅ โค 23 โ|๐ โ|
2๐ .
๏ฟฝ
33Recall that ๐ has vanishing average in ๐ฅ1, in particular ๐ (0, ๐2) = 0 for all ๐2 โ 2๐Z.
VARIATIONAL METHODS FOR A SINGULAR SPDE 49
Lemma B.7. Let ๐ โ (0, 14 ]. There exists a constant ๐ถ > 0 such that for any ๐ , ๐ : T2 โ R with
vanishing average in ๐ฅ1 there holds |๐1 | 12 (๐ ๐) ๐ฟ2
โค ๐ถ โ|๐ โ|1โ|๐โ| 34+๐ .
In particular, we have that โ|๐1 |12 (๐ ๐)โ๐ฟ2 โค ๐ถH(๐ ) 1
2H(๐) 12 .
Proof. By (2.2), writing ๐โ := ๐(ยท + โ), we have |๐1 | 12 (๐ ๐) 2๐ฟ2
=
โซR
โซT2
|๐โ1 (๐ ๐) |2 d๐ฅdโ|โ |2
.
โซR
โซT2
|๐โ1 ๐ |2 |๐โ |2 d๐ฅdโ|โ |2 +
โซR
โซT2
|๐โ1๐|2 |๐ |2 d๐ฅdโ|โ |2 . (B.10)
To estimate the rst term on the right-hand side of (B.10) we use Lemma B.4. We x ๐ โ (0, 14 ] andlet ๐ โฒ๐ =
5+^๐2 with ^๐ = 10๐
1โ2๐ , and ๐๐ =5+^๐3+^๐ > 1. Then 1
๐๐+ 1
๐โฒ๐= 1, so that by Hรถlderโs inequality,โซ
R
โซT2
|๐โ1 ๐ |2 |๐โ |2 d๐ฅdโ|โ |2 โค
โซR
(โซT2
|๐โ1 ๐ |2๐๐ d๐ฅ) 1๐๐
(โซT2
|๐โ |5+^๐ d๐ฅ) 2
5+^๐ dโ|โ |2
= โ๐โ2๐ฟ5+^๐
โซR
(โซT2
|๐โ1 ๐ |2๐๐ d๐ฅ) 1๐๐ dโ
|โ |2 ,
where in the last step we also used translation invariance. Note that the exponent 2๐๐ โ (2, 10),so that we may interpolateโซ
R
(โซT2
|๐โ1 ๐ |2๐๐ d๐ฅ) 1๐๐ dโ
|โ |2 =
โซR
(โซT2
|๐โ1 ๐ |2 d๐ฅ)\๐ (โซ
T2|๐โ1 ๐ |10 d๐ฅ
) 1โ\๐5 dโ
|โ |2
. โ ๐ โ2(1โ\๐ )๐ฟ10
โซR
(โซT2
|๐โ1 ๐ |2 d๐ฅ)\๐ dโ
|โ |2 ,
with \๐ = 12 + ๐ . By Jensenโs inequality, the mean-value theorem, and Poincarรฉโs inequality for
functions with zero average in ๐ฅ1, it then follows thatโซR
(โซT2
|๐โ1 ๐ |2 d๐ฅ)\๐ dโ
|โ |2 . โ ๐ โ1+2๐๐ฟ2
(โซ|โ | โฅ1
dโ|โ |2
)\๐+ โ๐1 ๐ โ1+2๐๐ฟ2
(โซ|โ |<1
dโ|โ |1โ2๐
)\๐. โ๐1 ๐ โ1+2๐๐ฟ2 .
By Lemmata B.4 and B.6 we can estimate โ ๐ โ๐ฟ10 . โ|๐ โ|1 and โ๐โ๐ฟ5+^๐ . โ|๐โ| 34+๐
, henceโซR
โซT2
|๐โ1 ๐ |2 |๐โ |2 d๐ฅdโ|โ |2 . โ|๐ โ|21โ|๐โ|23
4+๐.
It remains to bound the second term on the right-hand side of (B.10). Similar to the st term, weget by Hรถlderโs inequality and interpolation thatโซ
R
โซT2
|๐โ1๐|2 |๐ |2 d๐ฅdโ|โ |2 โค
โซR
(โซT2
|๐โ1๐|52 d๐ฅ
) 45(โซT2
|๐ |10 d๐ฅ) 1
5 dโ|โ |2
โค โ ๐ โ2๐ฟ10
โซR
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3(โซT2
|๐โ1๐|5 d๐ฅ) 2
15 dโ|โ |2
. โ ๐ โ2๐ฟ10 โ๐โ
23๐ฟ5
โซR
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3 dโ|โ |2 .
50 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
If Y < 14 , splitting the integral in โ, it follows with Jensenโs inequality thatโซR
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3 dโ|โ |2 =
โซ|โ | โฅ1
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3 dโ|โ |2 +
โซ|โ |<1
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3 dโ|โ |2
. โ๐โ43๐ฟ2
(โซ|โ | โฅ1
dโ|โ |2
) 23+
โซ|โ |<1
(โซT2
|๐โ1๐|2
|โ | 32+6๐d๐ฅ
) 23 dโ|โ |1โ4๐
. โ๐โ43๐ฟ2
+(โซ
|โ |<1
โซT2
|๐โ1๐|2
|โ | 32+2๐d๐ฅ dโ|โ |
) 23
. โ๐โ43๐ฟ2
+ โ|๐1 |34+๐๐โ
43๐ฟ2.
Using again Lemmata B.4 and B.6, we may bound โ ๐ โ๐ฟ10 . โ|๐ โ|1 and โ๐โ๐ฟ5 . โ|๐โ| 34+๐
, theconclusion follows with โ๐โ๐ฟ2 โค โ|๐โ| 3
4+๐. If Y = 1
4 , we use instead the estimateโซ|โ |<1
(โซT2
|๐โ1๐|2 d๐ฅ) 2
3 dโ|โ |2 โค โ๐1๐โ
43๐ฟ2
โซ|โ |<1
dโ|โ | 23. โ|๐โ|
431 .
๏ฟฝ
As for the Sobolev embedding in Lemma B.4, we next prove the embedding ๐ป 1anistropic โ C๐ผ ,
which is optimal and the critical exponent is given by ๐ผ = 1 โ dim2 = โ 1
4 .
Lemma B.8 (Besov embedding into Hรถlder spaces). There exists a constant ๐ถ > 0 such that for
any periodic distribution ๐ : T2 โ R of vanishing average, and ๐ โ (0, 114 ) \ {14 ,
34 ,
54 ,
94 }, there holds
[๐ ]โ 54+๐
โค ๐ถ (โ |๐1 |๐ ๐ โ๐ฟ2 + โ|๐2 |23๐ ๐ โ๐ฟ2), (B.11)
In particular, [๐ค]โ 14โค ๐ถH(๐ค) 1
2 for every๐ค โ W.
Proof. Since ๐ is of vanishing average, by (A.3) and (A.5) we know that for ๐ โ (0, 114 ) \ {14 ,
34 ,
54 ,
94 },
[๐ ]โ 54+๐
โผ sup๐ โ(0,1]
(๐
13) 54โ๐ โ๐A ๐๐ โ๐ฟโ .
Writing |๐1 |3 ๐๐ = |๐1 |๐ ๐ โ |๐1 |3โ๐ ๐๐ and ๐22 ๐๐ = |๐2 |23๐ ๐ โ |๐2 |2โ
23๐ ๐๐ , and using that |๐๐ |๐ผ๐ โ ๐ฟ2(R2)
for every ๐ผ โฅ 0 and ๐ = 1, 2, we deduce with Youngโs inequality for convolution of functions (asin Remark 1.11) that
โA ๐๐ โ๐ฟโ โค โ|๐1 |๐ ๐ โ๐ฟ2 โ|๐1 |3โ๐ ๐๐ โ๐ฟ2 + โ|๐2 |23๐ ๐ โ๐ฟ2 โ|๐2 |2โ
23๐ ๐๐ โ๐ฟ2
.(๐
13)โ3+๐ โ 5
4(โ|๐1 |๐ ๐ โ๐ฟ2 + โ|๐2 |
23๐ ๐ โ๐ฟ2
).
This implies that
[๐ ]โ 54+๐
โผ sup๐ โ(0,1]
(๐
13) 54โ๐ โ๐A ๐๐ โ๐ฟโ . โ|๐1 |๐ ๐ โ๐ฟ2 + โ|๐2 |
23๐ ๐ โ๐ฟ2 .
Combining (B.11) for ๐ = 1 and (2.15), we conclude that [๐ค]โ 14. H(๐ค) 1
2 for every๐ค โ W. ๏ฟฝ
The next proposition is the classical 1-dimensional embedding of Besov spaces into ๐ฟ๐ spacesin the periodic setting. 34
34The nonperiodic version of the statement is essentially a combination of [BCD11, Proposition 2.20 and Theorem2.36].
VARIATIONAL METHODS FOR A SINGULAR SPDE 51
Proposition B.9. For every ๐ โ (1,โ] and ๐ โ [1, ๐] with (๐, ๐) โ (โ, 1), there exists a constant๐ถ (๐, ๐) > 0 such that for every periodic ๐ : [0, 1) โ R with vanishing average(โซ 1
0|๐ (๐ง) |๐ d๐ง
) 1๐
โค ๐ถ (๐, ๐)โซ 1
0
1
โ1๐โ 1
๐
(โซ 1
0|๐โ1 ๐ (๐ง) |๐ d๐ง
) 1๐ dโโ, (B.12)
with the usual interpretation for ๐ = โ or ๐ = โ.
Proof. We prove the statement for ๐ โ (1,โ) (the case ๐ = โ follows similarly). For ๐ โ (0, 1] let๐๐ (โ) = 1โ
4๐๐eโโ2
4๐ , โ โ R, be the heat semigroup, and denote its periodization by
ฮฆ๐ (โ) =1
โ4๐๐
โ๏ธ๐โZ
eโ(โโ๐ )2
4๐ =โ๏ธ๐โZ
eโ4๐2๐2๐ e2๐๐๐โ, โ โ [0, 1).
Note that ฮฆ๐ is smooth, ฮฆ๐ โฅ 0, โฮฆ๐ โ๐ฟ1 =โซ 10 ฮฆ๐ dโ = 1, and for every ๐ โ (0, 1]
โฮฆ๐ โ๐ฟโ โค 1 +โ๏ธ
๐โZ\{0}eโ4๐2๐2๐ . 1 +
โซR๐๐ (b) db . 1 + ๐๐ (0) .
1โ๐.
Therefore, by interpolation, for every ๐ โ [1,โ] and ๐ โ (0, 1] we have
โฮฆ๐ โ๐ฟ๐ .โ๐โ(1โ 1
๐). (B.13)
We also claim that for every ๐ โ (0, 1]
sup|โ | โค 1
2
โ2โ๐ฮฆ๐ (โ) . 1. (B.14)
Indeed, using that for every ๐ โ Z \ {0}, |โ | โค 12 , and ๐ โ (0, 1], (โโ๐)2
4๐ โฅ ( |๐ |โ 12 )2
4๐ โฅ 116 , we
obtain35 eโ(โโ๐ )2
4๐ . 4๐(โโ๐)2 .
๐๐2 . It then follows that
โ4๐โ2โ๐
ฮฆ๐ (โ) =โ2
๐eโ
โ24๐ +
โ๏ธ๐โZ\{0}
โ2
๐eโ
(โโ๐ )24๐ . sup
๐งโR๐ง2eโ
๐ง24 + โ2
โ๏ธ๐โZ\{0}
1๐2. 1.
By the semigroup property and the periodicity of ๐ we know that for ๐ง โ (โ 12 ,
12 ),
๐ โ ฮฆ2๐ (๐ง) โ ๐ โ ฮฆ๐ (๐ง) =โซ 1
2
โ 12
(๐โโ1 ๐ โ ฮฆ๐ (๐ง)
)ฮฆ๐ (โ) dโ.
Using Minkowskiโs inequality and Youngโs inequality for convolution with exponents 1+ 1๐= 1
๐+ 1๐
with ๐ โ [1,โ) we deduce by (B.13),(โซ 12
โ 12
|๐ โ ฮฆ2๐ (๐ง) โ ๐ โ ฮฆ๐ (๐ง) |๐ d๐ง) 1
๐
.
โซ 12
โ 12
ฮฆ๐ (โ)(โซ 1
2
โ 12
|๐โโ1 ๐ โ ฮฆ๐ (๐ง) |๐ d๐ง) 1
๐
dโ
.
(โซ 12
โ 12
|ฮฆ๐ (๐ง) |๐ d๐ง) 1๐ โซ 1
2
โ 12
ฮฆ๐ (โ)(โซ 1
2
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ
.1
โ๐
(1๐โ 1
๐
) โซ 12
โ 12
ฮฆ๐ (โ)(โซ 1
2
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ, (B.15)
where we also used a change of variables and periodicity to replace โโ by โ.
35Recall that eโ๐ฅ . 1๐ฅ for ๐ฅ โฅ 1
16 .
52 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
To prove (B.12) we now write
๐ (๐ง) =โโ๏ธ๐=1
(๐ โ ฮฆ2ยท2โ๐ (๐ง) โ ๐ โ ฮฆ2โ๐ (๐ง)) โ ๐ โ ฮฆ1(๐ง),
and obtain by (B.15) that(โซ 1
0|๐ (๐ง) |๐ d๐ง
) 1๐
=
(โซ 12
โ 12
|๐ (๐ง) |๐ d๐ง) 1
๐
. ฮฃ(1) + ฮฃ(2) +(โซ 1
2
โ 12
|๐ โ ฮฆ1(๐ง) |๐ d๐ง) 1
๐
, (B.16)
where
ฮฃ(1) =โโ๏ธ๐=1
โ2๐
(1๐โ 1
๐
) โซ{ |โ | โค 1
2 : |โ |โ2๐ โค1}
ฮฆ2โ๐ (โ)(โซ 1
2
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ,
ฮฃ(2) =โโ๏ธ๐=1
โ2๐
(1๐โ 1
๐
) โซ{ |โ | โค 1
2 : |โ |โ2๐>1}
ฮฆ2โ๐ (โ)(โซ 1
2
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ.
Using that by (B.13), sup |โ | โค 12|ฮฆ2โ๐ (โ) | .
โ2๐ , we can estimate ฮฃ(1) as follows:
ฮฃ(1) .
โซ 12
โ 12
โ๏ธ{๐โฅ1: |โ |
โ2๐ โค1}
โ2๐
(1๐โ 1
๐+1
) (โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ
.
โซ 12
โ 12
1
|โ |1๐โ 1
๐
(โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐ dโ
|โ | .
For ฮฃ(2) , by (B.14) and the fact that 1๐โ 1
๐โ 1 < 0 (since (๐, ๐) โ (โ, 1)), we have
ฮฃ(2) .โโ๏ธ๐=1
โ2๐
(1๐โ 1
๐โ1
) โซ{ |โ | โค 1
2 : |โ |โ2๐>1}
1|โ |
(โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐ dโ
|โ |
. 1๐โ 1
๐
โซ 12
โ 12
1
|โ |1๐โ 1
๐
(โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐ dโ
|โ | .
For the last term in (B.16) we use that ๐ has vanishing average and periodicity, which implies thatโซ 12
โ 12๐ โ ฮฆ1(๐ง + โ) dโ = 0 for every ๐ง โ (โ 1
2 ,12 ), to obtain the bound(โซ 1
2
โ 12
|๐ โ ฮฆ1(๐ง) |๐ d๐ง) 1
๐
=
(โซ 12
โ 12
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๐ โ ฮฆ1(๐ง) โโซ 1
2
โ 12
๐ โ ฮฆ1(๐ง + โ) dโ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๐ d๐ง
) 1๐
โคโซ 1
2
โ 12
(โซ 12
โ 12
|๐โ1 ๐ โ ฮฆ1(๐ง) |๐ d๐ง) 1
๐
dโ .โซ 1
2
โ 12
(โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐
dโ
.
โซ 12
โ 12
1
|โ |1๐โ 1
๐
(โซ 12
โ 12
|๐โ1 ๐ (๐ง) |๐ d๐ง) 1๐ dโ|โ | , (B.17)
where we also used Minkowskiโs inequality, Youngโs inequality for convolution and the fact that1๐โ 1
๐+ 1 > 0. The right hand side of (B.17) is estimated by twice the right hand side of (B.12), so
the conclusion follows. ๏ฟฝ
The next lemma allows us to connect the estimate (2.4) with regularity in Besov spaces.
VARIATIONAL METHODS FOR A SINGULAR SPDE 53
Lemma B.10. There exists a constant ๐ถ > 0 such that for every ๐ โ (0, 1), ๐ โ [1,โ) and everyperiodic function ๐ : [0, 1) โ R the following estimate holds:
supโโ(0,1]
1โ๐
(โซ 1
0|๐โ1 ๐ (๐ง) |๐ d๐ง
) 1๐
โค ๐ถ supโโ(0,1]
1โ๐
(1โ
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ (๐ง) |๐ d๐ง dโโฒ
) 1๐
. (B.18)
Proof. Let โ โ (0, 1]. Then for โโฒ โ (0, โ] we have thatโซ 1
0|๐โ1 ๐ (๐ง) |๐ d๐ง โค 2๐โ1
โซ 1
0|๐โโฒ1 ๐ (๐ง) |๐ d๐ง + 2๐โ1
โซ 1
0|๐โโโโฒ1 ๐ (๐ง + โโฒ) |๐ d๐ง.
Integrating over โโฒ โ [โ2 , โ] we obtain that
โ
โซ 1
0|๐โ1 ๐ (๐ง) |๐ d๐ง โค 2๐
โซ โ
โ2
โซ 1
0|๐โโฒ1 ๐ (๐ง) |๐ d๐ง dโโฒ + 2๐
โซ โ
โ2
โซ 1
0|๐โโโโฒ1 ๐ (๐ง + โโฒ) |๐ d๐ง dโโฒ.
By the change of variables โโฒโฒ = โ โ โโฒ and ๐ง โฒ = ๐ง + โ โ โโฒโฒ, upon relabelling, we see thatโซ โ
โ2
โซ 1
0|๐โโโโฒ1 ๐ (๐ง + โโฒ) |๐ d๐ง dโโฒ =
โซ โ2
0
โซ 1
0|๐โโฒ1 ๐ (๐ง) |๐ d๐ง dโโฒ,
where we also used periodicity in ๐ง. Hence we have proved thatโซ 1
0|๐โ1 ๐ (๐ง) |๐ d๐ง โค 2๐
โ
โซ โ
0
โซ 1
0|๐โโฒ1 ๐ (๐ง) |๐ d๐ง dโโฒ,
which in turn implies (B.18). ๏ฟฝ
Appendix C. Stochastic estimates
We show that solutions of the linearized equationL๐ฃ = ๐b (C.1)
almost surely have (negative) innite total energy (see (1.1) for the denition) under the law ofwhite noise.
Proposition C.1. Assume that ใยทใ is the law of white noise. If ๐ฃ is the solution of vanishing average
in ๐ฅ1-direction to L๐ฃ = ๐b , then ๐ธ๐ก๐๐ก (๐ฃ) = โโ ใยทใ-almost surely.
Proof. Recall that in Fourier space we have an explicit representation of the solution to (C.1) as
๏ฟฝฬ๏ฟฝ (๐) = bฬ (๐)๐21 + |๐1 |โ1๐22
for ๐1 โ 0 and ๏ฟฝฬ๏ฟฝ (0, ๐2) = 0 for all ๐2 โ 2๐Z.
A short calculation shows that the harmonic part of the energy is
H(๐ฃ) =โซT2b๐ฃ d๐ฅ,
so that
๐ธ๐ก๐๐ก (๐ฃ) = โH(๐ฃ) +โซT2
(|๐1 |โ
12 ๐1
๐ฃ2
2
)2d๐ฅ โ 2
โซT2
(|๐1 |โ
12 ๐1
๐ฃ2
2
) (|๐1 |โ
12 ๐2๐ฃ
)d๐ฅ .
By Youngโs inequality, we have
๐ธ๐ก๐๐ก (๐ฃ) โค โ12H(๐ฃ) + 3โซT2
(|๐1 |โ
12 ๐1
๐ฃ2
2
)2d๐ฅ . (C.2)
By (B.1), (B.4) and [IO19, Lemma 12], we may estimateโซT2
(|๐1 |โ
12 ๐1
๐ฃ2
2
)2d๐ฅ =
โซT2
(๐ 1 |๐1 |
12๐ฃ2
2
)2d๐ฅ =
โซT2
(|๐1 |
12๐ฃ2
2
)2d๐ฅ . [๐ฃ2]21
2+Y. [๐ฃ]43
4โY,
where [๐ฃ] 34โY
is nite ใยทใ-almost surely by (5.7)
54 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
We next show that
H(๐ฃ) =โ๏ธ๐1โ 0
|bฬ (๐) |2
๐21 + |๐1 |โ1๐22
diverges ใยทใ-almost surely. Since bฬ (โ๐) = โbฬ (๐), we have that
H(๐ฃ) = 2โ๏ธ
๐โ2๐Z2\{๐1โค0}
|bฬ (๐) |2
๐21 + |๐1 |โ1๐22=: 2
โ๏ธ๐โ2๐Z2\{๐1โค0}
๐๐ |bฬ (๐) |2.
By the independence of {|bฬ (๐) |}๐โ2๐Z2\{๐1โค0} and Kolmogorovโs 0-1 law, we know that the probabil-ity of the event {H (๐ฃ) = +โ} is either 1 or 0. Hence, it is enough to show that ใ{H (๐ฃ) = +โ}ใ > 0.We rst notice thatโ๏ธ
๐โ2๐Z2\{๐1โค0}๐๐ |bฬ (๐) |2 โฅ
โ๏ธ๐โ2๐Z2\{๐1โค0}
๐๐1{ |bฬ (๐) |2โฅ1} =:โ๏ธ
๐โ2๐Z2\{๐1โค0}๐๐๐๐
and since the random variables b (๐) are identically distributed, there exists ๐ โ (0, 1) suchthat ใ๐๐ใ = ๐ for every ๐ โ 2๐Z2 \ {๐1 โค 0}. Given ๐ โฅ 1, there exists a nite subset๐ฝ โ 2๐Z2 \ {๐1 โค 0} such that ๐
2โ
๐โ๐ฝ ๐๐ โฅ ๐ and the following estimate holds
๐โ๏ธ๐โ๐ฝ
๐๐ =
โจโ๏ธ๐โ๐ฝ
๐๐๐๐
โฉ
โค ๐
2โ๏ธ๐โ๐ฝ
๐๐ยฉยญยซ1 โ
โจ{โ๏ธ๐โ๐ฝ
๐๐๐๐ โฅ ๐
}โฉยชยฎยฌ +โ๏ธ๐โ๐ฝ
๐๐
โจ{โ๏ธ๐โ๐ฝ
๐๐๐๐ โฅ ๐
}โฉ.
Then, it is easy to see that โจ{โ๏ธ๐โ๐ฝ
๐๐๐๐ โฅ ๐
}โฉโฅ ๐
2 โ ๐ > 0,
which in turn impliesโจ{ โ๏ธ๐โ2๐Z2\{๐1โค0}
๐๐๐๐ = +โ}โฉ
= lim๐โ+โ
โจ{ โ๏ธ๐โ2๐Z2\{๐1โค0}
๐๐๐๐ โฅ ๐
}โฉโฅ ๐
2 โ ๐ > 0.
Thus, we obtain that
ใ{H (๐ฃ) = +โ}ใ โฅโจ{ โ๏ธ
๐โ2๐Z2\{๐1โค0}๐๐๐๐ = +โ
}โฉ> 0,
which proves the desired claim. ๏ฟฝ
The next lemma is a Kolmogorov-type criterion for periodic random elds.
Lemma C.2. Let {๐(๐ฅ)}๐ฅ โT2 be a random eld and assume that for some ๐ผ โ (0, 32 ) and every
1 โค ๐ < โ
sup๐ โ(0,1]
(๐
13)๐ผ
sup๐ฅ โT2
ใ|๐๐ (๐ฅ) |๐ใ1๐ < โ.
Then, for every Y โ (0, 32 โ ๐ผ), ๐ โ Cโ๐ผโYalmost surely and for every 1 โค ๐ < โ there exists
๐ถ (Y, ๐) > 0 such that โจ[๐]๐โ๐ผโY
โฉ 1๐ โค ๐ถ (Y, ๐) .
VARIATIONAL METHODS FOR A SINGULAR SPDE 55
Proof. First assume that ๐ผ + Y โ 1, 12 . Let ๐Y >52Y . We rst claim that
[๐]โ๐ผโY .โ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
) (2
13)โ๐๐ผ
โ๐2โ๐ โ๐ฟ๐Y .
Indeed, for every ๐ โ (0, 1] we can nd ๐ โฅ 1 such that 2โ๐ < ๐ โค 2โ๐+1 and by the semigroupproperty and Remark 1.11, we obtain(
๐13)๐ผ+Y
โ๐๐ โ๐ฟโ .(2
13)โ๐ (๐ผ+Y)
โ(๐2โ๐ )๐โ2โ๐ โ๐ฟโ .(2
13)โ๐ (๐ผ+Y)
โ๐2โ๐ โ๐ฟโ
.(2
13)โ๐ (๐ผ+Y) (
213) (๐+1) 5
2๐Y โ๐2โ๐โ1 โ๐ฟ๐Y
.โ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
) (2
13)โ๐๐ผ
โ๐2โ๐ โ๐ฟ๐Y
and, taking the supremum over all ๐ โ (0, 1], we conclude the above claim via (A.1).Then, for every ๐ โฅ ๐Y , Minkowskiโs and Jensenโs inequality imply
โจ[๐]๐โ๐ผโY
โฉ 1๐ .
โจ(โ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
) (2
13)โ๐๐ผ
โ๐2โ๐ โ๐ฟ๐Y)๐โฉ 1
๐
โคโ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
) (2
13)โ๐๐ผ โจ
โ๐2โ๐ โ๐๐ฟ๐Yโฉ 1๐
โคโ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
) (2
13)โ๐๐ผ โจ
โ๐2โ๐ โ๐๐ฟ๐โฉ 1๐
.โ๏ธ๐โฅ1
(2
13)โ๐ (
Yโ 52๐Y
)sup
๐ โ(0,1]
(๐
13)๐ผ
sup๐ฅ โT2
ใ|๐๐ (๐ฅ) |๐ใ1๐ ,
where in the nal step we used the estimateโจโ๐๐ โ๐๐ฟ๐
โฉ 1๐ โค sup๐ฅ โT2 ใ|๐๐ (๐ฅ) |๐ใ
1๐ . As Y > 5
2๐Y , ourhypothesis yields the conclusion. For ๐ โ [1, ๐Y), one concludes via Jensenโs inequality.
In the critical case ๐ผ + Y = 1, 12 , one considers ๐พ < ๐ผ + Y and applies the above to conclude๐ โ Cโ๐พ , which together with [IO19, Remark 2] gives ๐ โ Cโ๐ผโY . ๏ฟฝ
Appendix D. Some estimates for the linear eqation
Lemma D.1. There exists ๐ถ > 0 such that for every Y โ (0, 18 ) and every b โ Cโ 54โY , the solution ๐ฃ
of vanishing average in ๐ฅ1 to the equation L๐ฃ = ๐b satises |๐1 |โ1๐2๐ฃ โ C 14โY with[
|๐1 |โ1๐2๐ฃ]14โY
โค ๐ถ [b]โ 54โY.
Proof. Recalling our notation A = |๐1 |L, we have that
๐b๐ = L๐ฃ๐ = |๐1 |โ1A๐ฃ๐ .
For ๐ = |๐1 |โ1๐2๐ฃ , this yields
A๐๐ = A|๐1 |โ1๐2๐ฃ๐ = ๐2๐b๐ .
Hence, for ๐ โ (0, 1] we have that
โ๐A๐๐ โ๐ฟโ = ๐ โ๐2๐b๐ โ๐ฟโ = ๐ โ๐b ๐2โ ๐2๐๐
2โ๐ฟโ = 2
12(๐
13)3โ 3
2 โ๐b ๐2โ (๐2๐ )๐
2โ๐ฟโ
.(๐
13) 32 โ๐b ๐
2โ๐ฟโ .
(๐
13) 14โY [๐b]โ 5
4โY,
56 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
where we used the characterisation of negative Hรถlder spaces from Lemma A.1. Note that theimplicit constant is universal for Y small, in particular for Y โ (0, 18 ). Hence, we obtain that[
|๐1 |โ1๐2๐ฃ]14โY
= [๐] 14โY. sup
๐ โ(0,1]
(๐
13)โ 1
4+Y โ๐A๐๐ โ๐ฟโ . [b]โ 54โY.
๏ฟฝ
Proposition D.2. There exists a constant ๐ถ > 0 such that for every ๐ฟb โ ๐ฟ2(T2), the solution ๐ฟ๐ฃ ofvanishing average in ๐ฅ1 to L๐ฟ๐ฃ = ๐๐ฟb satises the following estimates:
[๐ฟ๐ฃ] 34โค ๐ถ โ๐ฟb โ๐ฟ2, (D.1)
โ๐1๐ฟ๐ฃ โ๐ฟ10 โค ๐ถ โ๐ฟb โ๐ฟ2, (D.2)โ๐2๐ฟ๐ฃ โ
๐ฟ103โค ๐ถ โ๐ฟb โ๐ฟ2 . (D.3)
Proof. Writing ๐21๐ฟ๐ฃ and |๐2 |43๐ฟ๐ฃ as Fourier series and using Youngโs inequality in the form |๐2 |
83 .
๐41 +๐42๐21
for every ๐1, ๐2 โ 2๐Z, we obtain that
โ๐21๐ฟ๐ฃ โ2๐ฟ2 + โ|๐2 |43๐ฟ๐ฃ โ2
๐ฟ2 . โL๐ฟ๐ฃ โ2๐ฟ2 . โ๐๐ฟb โ2
๐ฟ2 . โ๐ฟb โ2๐ฟ2,
which leads to (D.1) via (B.11) for ๐ = 2. Using the same argument, we also obtain that
โ๐21๐ฟ๐ฃ โ2๐ฟ2 + โ|๐2 |23 ๐1๐ฟ๐ฃ โ2๐ฟ2 . โ๐ฟb โ2
๐ฟ2, (D.4)
โ๐1 |๐2 |23๐ฟ๐ฃ โ2
๐ฟ2 + โ|๐2 |43๐ฟ๐ฃ โ2
๐ฟ2 . โ๐ฟb โ2๐ฟ2, (D.5)
โ|๐1 |12 ๐2๐ฟ๐ฃ โ2๐ฟ2 + โ|๐2 |
13 ๐2๐ฟ๐ฃ โ2๐ฟ2 . โ๐ฟb โ2
๐ฟ2 . (D.6)By the embedding result in Lemma B.4 we know that
โ๐1๐ฟ๐ฃ โ๐ฟ10 . โ๐21๐ฟ๐ฃ โ๐ฟ2 + โ|๐2 |23 ๐1๐ฟ๐ฃ โ๐ฟ2, (D.7)
โ๐โ2๐ฟ๐ฃ โ๐ฟ10 . โ๐1๐โ2๐ฟ๐ฃ โ๐ฟ2 + โ|๐2 |23 ๐โ2๐ฟ๐ฃ โ๐ฟ2, (D.8)
โ๐2๐ฟ๐ฃ โ๐ฟ103. โ|๐1 |
12 ๐2๐ฟ๐ฃ โ๐ฟ2 + โ|๐2 |
13 ๐2๐ฟ๐ฃ โ๐ฟ2 . (D.9)
Combining (D.4) with (D.7) and (D.6) with (D.9) we obtain (D.2) and (D.3). ๏ฟฝ
Lemma D.3. Let b be smooth. Then the solution ๐ฃ of L๐ฃ = ๐b with vanishing average in ๐ฅ1 issmooth.
Proof. If b is smooth, then ๐๐1 ๐๐2 b โ ๐ฟ2(T2) for all๐,๐ โ N0. It follows by a simple calculation inFourier space that
โ๐๐1 ๐๐2 ๐ฃ โ2๐ฟ2 =โ๏ธ๐
|๐1 |2๐ |๐2 |2๐ |๏ฟฝฬ๏ฟฝ (๐) |2 =โ๏ธ๐1โ 0
|๐1 |2๐ |๐2 |2๐|๐1 |2 |bฬ (๐) |2|๐1 |3 + |๐2 |2
โคโ๏ธ๐1โ 0
|๐1 |2๐+2 |๐2 |2๐ |bฬ (๐) |2 = โ๐๐+11 ๐๐2 b โ2๐ฟ2 < โ
for all๐,๐ โ N0, in particular, ๐ฃ is smooth by Sobolev embedding. ๏ฟฝ
Appendix E. Regularity of finite-energy solutions for smooth data
In this section we develop an ๐ฟ2-based regularity theory for weak solutions ๐ข with nite energyH(๐ข) < โ of the EulerโLagrange equation
L๐ข = โ๐(๐ข๐ 1๐2๐ข โ 1
2๐ข๐ 1๐1๐ข2)โ 12๐ 1๐2๐ข
2 + ๐b . (E.1)
For โ โ (0, 1], dene the dierence quotients
๐ทโ๐ ๐ข = |โ |โ๐ผ๐ ๐โ๐ ๐ข, ๐ผ1 = 1, ๐ผ2 =
23 . (E.2)
VARIATIONAL METHODS FOR A SINGULAR SPDE 57
Proposition E.1 (๐ป 2โ estimate). Assume that b โ ๐ฟ2. There exists a constant ๐ถ > 0 such that for
any solution ๐ข of the EulerโLagrange equation (E.1) withH(๐ข) < โ we have
supโโ(0,1]
H(๐ทโ๐ ๐ข) โค ๐ถ
(1 + โb โ2
๐ฟ2 + H (๐ข)12).
In particular, for any ๐ โ [0, 2) we have that โ|๐1 |๐ ๐ขโ๐ฟ2 + โ|๐2 |23๐ ๐ขโ๐ฟ2 < โ.
Proposition E.2 (๐ป 3โ estimate). Assume that b satises H(b) < โ. There exists a constant ๐ถ > 0such that for any solution ๐ข of the EulerโLagrange equation (E.1) withH(๐ข) < โ we have
supโ,โโฒโ(0,1]
H(๐ทโ๐ ๐ท
โโฒ๐ ๐ข) โค ๐ถ
(1 + H (b)22 + H (๐ข)132
).
In particular, for any ๐ โ [0, 3) we have that โ|๐1 |๐ ๐ขโ๐ฟ2 + โ|๐2 |23๐ ๐ขโ๐ฟ2 < โ.
For the proof of Propositions E.1 and E.2 it is convenient to work with the scale of norms
โ|๐ โ|2๐ =โซT2
( |๐1 |๐ ๐ )2 d๐ฅ +โซT2
(|๐1 |โ
๐ 2 |๐2 |๐ ๐
)2d๐ฅ,
for ๐ > 0 and periodic functions ๐ : T2 โ R with vanishing average in ๐ฅ1, as dened in (B.8).These norms are adapted to the harmonic energy H , in particular, we have that โ|๐ โ|1 = H(๐ ) 1
2 ,and one may think of the norms โ| ยท โ|๐ dening a scale of (anisotropic) Sobolev spaces. Indeed, asshown in Lemma B.6 the norms โ| ยท โ|๐ control an anisotropic fractional gradient in ๐ฟ2.Lemma E.3. There exists a constant ๐ถ > 0 such that for any ๐ข โ W there holds
supโโ(0,1]
โ๐ทโ๐ ๐ขโ๐ฟ2 โค ๐ถ โ|๐ขโ|1, ๐ = 1, 2.
Proof. We treat the two directions ๐ = 1, 2 separately. For ๐ = 1, the claim follows easily by themean-value theorem, which implies that
supโโ(0,1]
โ๐ทโ1๐ขโ๐ฟ2 โค โ๐1๐ขโ๐ฟ2 .
For ๐ = 2 we appeal to Lemma B.10 (or rather its analogue for functions on T2) to estimate
supโโ(0,1]
โ๐ทโ2๐ขโ2๐ฟ2 = sup
โโ(0,1]
1โ
43
โซT2
|๐โ2๐ข |2 d๐ฅ . supโโ(0,1]
1โ
43
1โ
โซ โ
0
โซT2
|๐โโฒ2 ๐ข |2 d๐ฅ dโโฒ
. supโโ(0,1]
โซ โ
0
โซT2
|๐โโฒ2 ๐ข |2
โโฒ43
d๐ฅ dโโฒ
โโฒ.
โซR
โซT2
|๐โ2๐ข |2
|โ | 43d๐ฅ dโ|โ |
(2.2). โ|๐2 |
23๐ขโ2
๐ฟ2 .
The conclusion then follows from Lemma B.6. ๏ฟฝ
The proof of Propositions E.1 and E.2 mainly relies on the following two lemmata:Lemma E.4. Let ๐ โ (0, 14 ). There exists a constant ๐ถ๐ > 0 such that for all periodic functions
๐ , ๐, ๐ : T2 โ R of vanishing average in ๐ฅ1 we have๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ (๐2๐)๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค ๐ถ๐ โ|๐ โ|1โ|๐โ|1โ|๐ โ| 34+๐ .
Proof. This follows easily from the denition of โ| ยท โ|1 and Lemma B.7. Indeed, we have๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ (๐2๐)๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2
|๐1 |โ12 ๐2๐ |๐1 |
12 (๐ ๐) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐โ|1โ|๐1 |12 (๐ ๐)โ๐ฟ2 . โ|๐โ|1โ|๐ โ|1โ|๐ โ| 34+๐ .
๏ฟฝ
Lemma E.5. There exists a constant ๐ถ > 0 such that for all periodic functions ๐ , ๐, โ, ๐ : T2 โ R of
vanishing average in ๐ฅ1 we have๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ ๐ 1(๐๐1โ)๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค ๐ถ โ|๐ โ|1โ|๐โ|1โ|โโ|1โ|๐ โ| 12 .
58 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Proof. We rst use CauchyโSchwarz to bound๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ ๐ 1(๐๐1โ)๐ d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2(๐1โ)๐๐ 1(๐ ๐) d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ๐1โโ๐ฟ2 โ๐๐ 1(๐ ๐)โ๐ฟ2 โค โ|โโ|1โ๐๐ 1(๐ ๐)โ๐ฟ2 .
By Hรถlderโs inequality and the boundedness of ๐ 1 on ๐ฟ52 (T2) (A.4) , we may further estimate
โ๐๐ 1(๐ ๐)โ๐ฟ2 โค โ๐โ๐ฟ10 โ๐ 1(๐ ๐)โ๐ฟ52. โ๐โ๐ฟ10 โ ๐ ๐ โ
๐ฟ52. โ๐โ๐ฟ10 โ ๐ โ๐ฟ10 โ๐ โ
๐ฟ103,
from which the claim follows with the Sobolev-type embeddings
โ๐โ๐ฟ10(B.5). โ๐1๐โ๐ฟ2 + โ๐2 |
23๐โ๐ฟ2
(B.9). โ|๐โ|1,
โ๐ โ๐ฟ103
(B.6). โ|๐1 |
12๐ โ๐ฟ2 + โ๐2 |
13๐ โ๐ฟ2
(B.9). โ|๐ โ| 1
2.
๏ฟฝ
Proof of Proposition E.1. Since โ|๐ขโ|21 = H(๐ข) < โ, we can test the EulerโLagrange equation (E.1)with ๐ = ๐ทโโ
๐ ๐ทโ๐ ๐ข, where ๐ทโ
๐ denotes the dierence quotient introduced in (E.2) for โ โ (0, 1].Then the left-hand side of (E.1) turns intoโซ
T2L๐ข๐ทโโ
๐ ๐ทโ๐ ๐ข d๐ฅ = H(๐ทโ
๐ ๐ข) = โ|๐ทโ๐ ๐ขโ|21.
We continue with estimating the terms on the right-hand side of the EulerโLagrange equation:Term 1 (๐ข๐ 1๐2๐ข). By a discrete integration by parts, we can writeโซ
T2๐ข๐ 1๐2๐ข๐ท
โโ๐ ๐ทโ
๐ ๐ข d๐ฅ =
โซT2๐ทโ๐ ๐ข (๐2๐ 1๐ข)๐ทโ
๐ ๐ข d๐ฅ +โซT2๐ขโ๐2(๐ทโ
๐ ๐ 1๐ข)๐ทโ๐ ๐ข d๐ฅ,
where ๐ขโ = ๐ข (ยท + โ). Applying Lemma E.4 to each of these two terms, together with
โ|๐ 1๐ขโ|1 = โ|๐ขโ|1 and โ|๐ขโ โ|1 = โ|๐ขโ|1, (E.3)
then yields๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ทโ๐ ๐ข (๐2๐ 1๐ข)๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ทโ
๐ ๐ขโ|1โ|๐ 1๐ขโ|1โ|๐ทโ๐ ๐ขโ| 45 . โ|๐ทโ
๐ ๐ขโ|1โ|๐ขโ|1โ|๐ทโ๐ ๐ขโ| 45 ,๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2๐ขโ๐2(๐ทโ
๐ ๐ 1๐ข)๐ทโ๐ ๐ข d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ขโ โ|1โ|๐ 1๐ทโ๐ ๐ขโ|1โ|๐ทโ
๐ ๐ขโ| 45 . โ|๐ขโ|1โ|๐ทโ๐ ๐ขโ|1โ|๐ทโ
๐ ๐ขโ| 45 .
Note that by interpolation (which is easily seen in Fourier space) and Lemma E.3, there holds
โ|๐ทโ๐ ๐ขโ| 45 โค โ๐ทโ
๐ ๐ขโ15๐ฟ2โ|๐ทโ
๐ ๐ขโ|451 . โ|๐ขโ|
151 โ|๐ท
โ๐ ๐ขโ|
451 , (E.4)
hence ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ข๐ 1๐2๐ข๐ท
โโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ขโ|
651 โ|๐ท
โ๐ ๐ขโ|
951 .
Term 2 (๐ 1๐2๐ข2). As for the rst term, after a discrete integration by partsโซT2๐ 1๐2๐ข
2๐ทโโ๐ ๐ทโ
๐ ๐ข d๐ฅ =
โซT2๐ทโ๐ (๐ข๐2๐ข)๐ 1๐ทโ
๐ ๐ข d๐ฅ
=
โซT2(๐ทโ
๐ ๐ข)๐2๐ข๐ 1๐ทโ๐ ๐ข d๐ฅ +
โซT2๐ขโ๐ทโ
๐ ๐2๐ข๐ 1๐ทโ๐ ๐ข d๐ฅ,
an application of Lemma E.4, the interpolation (E.4), and Lemma E.3 implies๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ 1๐2๐ข
2๐ทโโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ทโ
๐ ๐ขโ|1โ|๐ขโ|1โ|๐ทโ๐ ๐ขโ| 45 . โ|๐ขโ|
651 โ|๐ท
โ๐ ๐ขโ|
951 .
VARIATIONAL METHODS FOR A SINGULAR SPDE 59
Term 3 (๐ข๐1๐ 1๐ข2). For the cubic term in ๐ข we haveโซT2๐ข๐1๐ 1๐ข
2๐ทโโ๐ ๐ทโ
๐ ๐ข d๐ฅ =
โซT2(๐ทโ
๐ ๐ข)๐ 1(๐ข๐1๐ข)๐ทโ๐ ๐ข d๐ฅ +
โซT2๐ขโ๐ 1(๐ทโ
๐ ๐ข๐1๐ข)๐ทโ๐ ๐ข d๐ฅ
+โซT2๐ขโ๐ 1(๐ขโ๐1๐ทโ
๐ ๐ข)๐ทโ๐ ๐ข d๐ฅ .
By Lemma E.5 we may estimate the rst term byโซT2(๐ทโ
๐ ๐ข)๐ 1(๐ข๐1๐ข)๐ทโ๐ ๐ข d๐ฅ . โ|๐ทโ
๐ ๐ขโ|1โ|๐ขโ|1โ|๐ขโ|1โ|๐ทโ๐ ๐ขโ| 12 ,
and similarly for the other two terms, so that, together with (E.3),๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ข๐1๐ 1๐ข
2๐ทโโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ขโ|21โ|๐ทโ
๐ ๐ขโ|1โ|๐ทโ๐ ๐ขโ| 12 .
Interpolation and Lemma E.3 then yield
โ|๐ทโ๐ ๐ขโ| 12 โค โ๐ทโ
๐ ๐ขโ12๐ฟ2โ|๐ทโ
๐ ๐ขโ|121 . โ|๐ขโ|
121 โ|๐ท
โ๐ ๐ขโ|
121 ,
hence ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐ข๐1๐ 1๐ข
2๐ทโโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ . โ|๐ขโ|
521 โ|๐ท
โ๐ ๐ขโ|
321 .
Term 4 (๐b). Note that by assumption b โ ๐ฟ2, so that CauchyโSchwarz and Lemma E.3 imply๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซT2๐b๐ทโโ
๐ ๐ทโ๐ ๐ข d๐ฅ
๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ๐b โ๐ฟ2 โ๐ทโโ๐ ๐ทโ
๐ ๐ขโ๐ฟ2 . โ๐b โ๐ฟ2 โ|๐ทโ๐ ๐ขโ|1.
With the above estimates on the three superlinear on the right-hand side of the EulerโLagrangeequation, we have therefore shown that
โ|๐ทโ๐ ๐ขโ|21 . โ|๐ขโ|
651 โ|๐ท
โ๐ ๐ขโ|
951 + โ|๐ขโ|
521 โ|๐ท
โ๐ ๐ขโ|
321 + โb โ๐ฟ2 โ|๐ทโ
๐ ๐ขโ|1,which by Youngโs inequality implies that
โ|๐ทโ๐ ๐ขโ|21 . โ|๐ขโ|121 + โ|๐ขโ|101 + โ๐b โ2
๐ฟ2 . 1 + โ|๐ขโ|121 + โ๐b โ2๐ฟ2,
with an implicit constant that does not depend onโ. Finally, we notice that a bound on the quantitysupโโ(0,1] โ|๐ทโ
๐ ๐ขโ|1 implies a bound on โ|๐1 |๐ ๐ขโ๐ฟ2 + โ|๐2 |23๐ ๐ขโ๐ฟ2 for ๐ โ [0, 1) by Lemma B.6 and
(2.2). ๏ฟฝ
Proof of Proposition E.2. The proof is very similar to the proof of Proposition E.1. Under theassumptions of Proposition E.2, Proposition E.1 implies that
supโโ(0,1]
โ|๐ทโ๐ ๐ขโ|1 . 1 + โ|๐ขโ|61 + โ๐b โ๐ฟ2 . 1 + โ|๐ขโ|61 + โ|b โ|1, (E.5)
so that we may test the EulerโLagrange equation (E.1) with ๐ = ๐ทโโโฒ๐ ๐ทโโฒ
๐ ๐ทโโ๐ ๐ทโ
๐ ๐ข. Then theleft-hand side of (E.1) turns intoโซ
T2L๐ข ๐ทโโโฒ
๐ ๐ทโโฒ๐ ๐ท
โโ๐ ๐ทโ
๐ ๐ข d๐ฅ = โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ|21.
We proceed by estimating each term on the right-hand side of (E.1).Term 1 (๐ข๐ 1๐2๐ข). Integrating by parts twice (with respect to ๐ทโโโฒ
๐ and ๐ทโโ๐ , we obtain four terms,
all of which can be estimated by eitherโ|๐ขโ|1โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ|1โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ| 45 , or โ|๐ทโโฒ
๐ ๐ขโ|1โ|๐ทโ๐ ๐ขโ|1โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ| 45 . (E.6)
By interpolation, see (E.4), and Lemma E.3, there holds
โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ| 45 โค โ๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ
15๐ฟ2โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ|
451 . โ|๐ทโ
๐ ๐ขโ|151 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
451
Term 2 (๐ 1๐2๐ข2). This term is treated like the previous one, with the same bounds (E.6).
60 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Term 3 (๐ข๐1๐ 1๐ข2). For this term we again integrate by parts twice to obtain nine terms, all ofwhich can be bounded by one of the expressions
โ|๐ขโ|1โ|๐ทโโฒ๐ ๐ขโ|1โ|๐ทโ
๐ ๐ขโ|1โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ| 12 , or โ|๐ขโ|21โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ|1โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ| 12 ,
where by interpolation and Lemma E.3
โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ| 12 โค โ๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ
12๐ฟ2โ|๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ|
121 . โ|๐ทโ
๐ ๐ขโ|121 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
121 .
Term 4 (๐b). Under the regularity assumption โ|b โ|1 < โ on b we can also estimate with CauchyโSchwarz and Lemma E.3๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2๐b๐ทโโโฒ
๐ ๐ทโโฒ๐ ๐ท
โโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ = ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝโซ
T2๐ทโโฒ๐ ๐b๐ท
โโฒ๐ ๐ท
โโ๐ ๐ทโ
๐ ๐ข d๐ฅ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค โ๐ทโโฒ
๐ b โ๐ฟ2 โ๐ทโโ๐ ๐ทโโฒ
๐ ๐ทโ๐ ๐ขโ๐ฟ2
โค โ|b โ|1โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ|1.
In total, we can therefore bound
โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ|21 . โ|๐ขโ|1โ|๐ทโ
๐ ๐ขโ|151 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
951 + โ|๐ทโโฒ
๐ ๐ขโ|1โ|๐ทโ๐ ๐ขโ|
651 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
951
+ โ|๐ขโ|1โ|๐ทโโฒ๐ ๐ขโ|1โ|๐ทโ
๐ ๐ขโ|321 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
121 + โ|๐ขโ|21โ|๐ทโ
๐ ๐ขโ|121 โ|๐ท
โโฒ๐ ๐ท
โ๐ ๐ขโ|
321
+ โ|b โ|1โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ|1,
from which it follows by Youngโs inequality and (E.5) that
โ|๐ทโโฒ๐ ๐ท
โ๐ ๐ขโ|21 . 1 + โ|๐ขโ|1321 + โ|b โ|221 ,
with an implicit constant that does not depend on โ,โโฒ. As in the proof of Proposition E.1, wenotice that a bound on supโ,โโฒโ(0,1] โ|๐ทโ
๐ ๐ทโโฒ๐ ๐ขโ|21 implies a bound on โ|๐1 |๐ ๐ขโ๐ฟ2 + โ|๐2 |
23๐ ๐ขโ๐ฟ2 for
๐ โ [2, 3) by Lemma B.6 and (2.2). ๏ฟฝ
Appendix F. Approximation of qadratic functionals of the noise by cylinderfunctionals
In this section we show the following approximation result, which seems classical but sincewe could not nd a proof in the literature we include it here:
Lemma F.1. Let ๐พ be a linear operator on the space of Schwartz distributions Sโฒ(T2) such that
๐พ (Sโฒ(T2)) โ Cโ(T2) and ๐พ : ๐ฟ2(T2) โ ๐ฟ2(T2) is HilbertโSchmidt. Assume further that the
probability measure ใยทใ satises Assumption 1.1 (iv). Consider the quadratic functional๐บ : Sโฒ(T2) โR given by
๐บ (b) := b (๐พb).Then under the assumption that ใ|๐บ (b) |ใ < โ, ๐บ is well-approximated by cylindrical functionals in
with respect to the norm ใ|๐บ (b) |2๐ใ12๐ + ใโ ๐๐บ
๐b(b)โ2๐
๐ฟ2ใ
12๐
for every 1 โค ๐ < โ.
Proof. Without loss of generality, we may assume that๐พ is symmetric. Since๐พ is HilbertโSchmidt,there exists an orthonormal system {๐๐}๐โN of ๐ฟ2(T2) and a sequence {_๐}๐โN โ R such that
๐พ =โ๏ธ๐โN
_๐ (๐๐, ยท)๐๐, and โ๐พ โ2๐ป๐ =โ๏ธ๐
_2๐ < โ. (F.1)
Note that by the assumption ๐พ (Sโฒ(T2)) โ Cโ(T2) there holds {๐๐}๐โN โ Cโ(T2), in particularb (๐๐) is well-dened for any ๐ โ N, and given ๐ โ N we may dene ๐พ๐ b :=
โ๐โค๐ _๐b (๐๐)๐๐ .
Step 1 We rst show that for any b โ Sโฒ(T2), ๐พ๐ b โ ๐พb in Sโฒ(T2) as ๐ โ โ.Indeed, with b๐ก := b โ๐๐ก โ Cโ(T2), for any ๐ โ Cโ(T2) we have
| (๐พ๐ b โ ๐พb, ๐) | โค |(๐พ๐ b โ ๐พ๐ b๐ก , ๐) | + |(๐พ๐ b๐ก โ ๐พb๐ก , ๐) | + |(๐พb๐ก โ ๐พb, ๐) |.
VARIATIONAL METHODS FOR A SINGULAR SPDE 61
Note that b๐ก โ b in Sโฒ as ๐ก โ 0, hence for any ๐ > 0 we may choose ๐ก > 0 small enough so that bysymmetry of ๐พ๐ and ๐พ ,
| (๐พ๐ b โ ๐พ๐ b๐ก , ๐) | = | (b โ b๐ก ) (๐พ๐๐) | <๐
3 ,
| (๐พb๐ก โ ๐พb, ๐) | = | (b โ b๐ก ) (๐พ๐) | <๐
3 ,
for any๐ โ N. The remaining term can be bounded using Cauchy-Schwarz and Besselโs inequalityfor orthonormal systems to obtain
| (๐พ๐ b๐ก โ ๐พb๐ก , ๐) | =๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ(โ๏ธ๐>๐
_๐ (๐๐, b๐ก ) (๐๐, ๐))๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ๏ฟฝ โค
(โ๏ธ๐>๐
_2๐ | (๐๐, b๐ก ) |2) 1
2(โ๏ธ๐โN
| (๐๐, ๐) |2) 1
2
โค โb๐ก โ๐ฟ2(โ๏ธ๐>๐
_2๐
) 12
โ๐ โ๐ฟ2 <๐
3
if ๐ is chosen suitably large, since {_๐}๐ is square-summable.Step 2 We next claim that ๐บ๐ (b) := b (๐พ๐ b) satises ๐บ๐ (b) โ ๐บ (b) as ๐ โ โ for all b โSโฒ(T2).
For the proof of this claim we again appeal to the convergence b๐ก โ b in Sโฒ by splitting|๐บ๐ (b) โ๐บ (b) | = |b (๐พ๐ b) โ b (๐พb) |
โค |b (๐พ๐ b) โ b๐ก (๐พ๐ b) | + |b๐ก (๐พ๐ b) โ b๐ก (๐พb) | + |b๐ก (๐พb) โ b (๐พb) |.As in Step 1, there holds
|b (๐พ๐ b) โ b๐ก (๐พ๐ b) | โ 0, |b๐ก (๐พb) โ b (๐พb) | โ 0
as ๐ก โ 0 for any ๐ โ N, since ๐พ๐ b, ๐พb โ Cโ(T2). Moreover, by Step 1, we have|b๐ก (๐พ๐ b) โ b๐ก (๐พb) | = | (๐พ๐ b โ ๐พb, b๐ก ) | โ 0
as ๐ โ โ.Step 3 We show that ๐๐บ๐ (b)
๐bโ ๐๐บ (b)
๐bas ๐ โ โ in ๐ฟ๐ใยทใ๐ฟ
2๐ฅ for any 1 โค ๐ < โ.
Indeed, by symmetry of ๐พ and ๐พ๐ we have that๐๐บ๐ (b)๐b
= 2๐พ๐ b = 2โ๏ธ๐โค๐
_๐b (๐๐)๐๐, and ๐๐บ (b)๐b
= 2๐พb = 2โ๏ธ๐โN
_๐b (๐๐)๐๐ .
With this we obtain by orthonormality of the {๐๐}๐ that ๐(๐บ โ๐บ๐ ) (b)๐b
2๐ฟ2
= 4โ๏ธ๐>๐
_2๐b (๐๐)2,
hence, applying (5.1) in the form ofโจb (๐๐)2๐
โฉ 12๐ .๐ โ๐๐ โ๐ฟ2 .๐ 1,
for all ๐ โ N, it follows thatโจ ๐๐บ (b)๐b
โ ๐๐บ๐ (b)๐b
2๐๐ฟ2
โฉ 12๐
=
โจ(4โ๏ธ๐>๐
_2๐b (๐๐)2)๐โฉ 1
2๐
โค 2(โ๏ธ๐>๐
_2๐โจb (๐๐)2๐
โฉ 1๐
) 12
.๐
(โ๏ธ๐>๐
_2๐
) 12๐โโโโ 0,
by the niteness of โ๐พ โ๐ป๐ .
62 R. IGNAT, F. OTTO, T. RIED, AND P. TSATSOULIS
Step 4 We show that the sequence {๐บ๐ (b) โ ใ๐บ๐ (b)ใ}๐ โN is Cauchy in ๐ฟ2๐ใยทใ for any 1 โค ๐ < โ,in particular, there exists a centred random variable ๐บโ(b) such that ๐บ๐ (b) โ ใ๐บ๐ (b)ใ โ ๐บโ(b)for ใยทใ-almost every b as ๐ โ โ along a subsequence.
Indeed, since๐บ๐ (b) is a cylinder functional and ใยทใ satises Assumption 1.1 (iv), in particularProposition 5.1, we can apply (5.1) to obtain the boundโจ|๐บ๐ (b) โ ใ๐บ๐ (b)ใ โ (๐บ๐ (b) โ ใ๐บ๐ (b)ใ) |2๐
โฉ 12๐ =
โจ|๐บ๐ (b) โ๐บ๐ (b) โ ใ๐บ๐ (b) โ๐บ๐ (b)ใ|2๐
โฉ 12๐
.๐
โจ ๐(๐บ๐ โ๐บ๐ ) (b)๐b
2๐๐ฟ2
โฉ 12๐
,
for ๐ โฅ ๐ . Hence, by Step 3,โจ|๐บ๐ (b) โ ใ๐บ๐ (b)ใ โ (๐บ๐ (b) โ ใ๐บ๐ (b)ใ) |2๐
โฉ 12๐ ๐,๐โโโโ 0,
for any 1 โค ๐ < โ.
Step 5 We claim that ๐บ๐ (b) โ ๐บ (b) in ๐ฟ2๐ใยทใ as ๐ โ โ.Indeed, by Step 2 we know that ๐บ๐ (b) โ ๐บ (b) almost surely, so that with the result from
Step 4 we may conclude thatใ๐บ๐ (b)ใ = ๐บ๐ (b) โ (๐บ๐ (b) โ ใ๐บ๐ (b)ใ) โ ๐บ (b) โ๐บโ(b)
almost surely along a subsequence as ๐ โ โ. But since ใ๐บ๐ (b)ใ is constant in b (recall that bdenotes the dummy variable over which ใยทใ integrates), the random variable ๐บ (b) โ๐บโ(b) mustbe almost surely constant, i.e.
๐บ (b) โ๐บโ(b) = ใ๐บ (b) โ๐บโ(b)ใ = ใ๐บ (b)ใ,since ใ๐บใ < โ by assumption and ๐บโ is centred. Hence ใ๐บ๐ (b)ใ โ ใ๐บ (b)ใ as ๐ โ โ alonga subsequence. Since the above argument can be repeated for any subsequence, we obtainthat ใ๐บ๐ (b)ใ โ ใ๐บ (b)ใ as ๐ โ โ. Since ๐บ๐ (b) โ ๐บ (b) almost surely, we conclude that๐บโ(b) = ๐บ (b) โ ใ๐บ (b)ใ almost surely, which together with Step 4 implies that ๐บ๐ (b) โ ๐บ (b) in๐ฟ2๐ใยทใ as ๐ โ โ.
By Step 3โ5, we conclude that๐บ๐ โ ๐บ with respect to the norm ใ|๐บ (b) |2๐ใ12๐ + ใโ ๐๐บ
๐b(b)โ2๐
๐ฟ2ใ
12๐ .๏ฟฝ
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(R. Ignat) Institut deMathรฉmatiqes de Toulouse & Institut Universitaire de France, UMR 5219, Universitรฉde Toulouse, CNRS, UPS IMT, F-31062 Toulouse Cedex 9, France
Email address: [email protected]
(F. Otto)Max-Planck-Institut fรผr Mathematik in den Naturwissenschaften, Inselstrasse 22, 04103 Leipzig,Germany
Email address: [email protected]
(T. Ried)Max-Planck-Institut fรผr Mathematik in den Naturwissenschaften, Inselstrasse 22, 04103 Leipzig,Germany
Email address: [email protected]
(P. Tsatsoulis) Max-Planck-Institut fรผr Mathematik in den Naturwissenschaften, Inselstrasse 22, 04103Leipzig, Germany
Email address: [email protected]