This paper establishes complex interpolation results for vector-valued Sobolev spaces with Dirichlet boundary conditions on the half-line, with applications to evolution equations and fractional domain spaces.
Contribution
It provides new results on complex interpolation of weighted Sobolev spaces with boundary conditions and introduces a simplified proof for related multiplier theorems.
Findings
01
Characterization of fractional domain spaces of the first derivative operator
02
New simplified proof for pointwise multipliers in Bessel potential spaces
03
Application to evolution equations with boundary conditions
Abstract
We prove results on complex interpolation of vector-valued Sobolev spaces over the half-line with Dirichlet boundary condition. Motivated by applications in evolution equations, the results are presented for Banach space-valued Sobolev spaces with a power weight. The proof is based on recent results on pointwise multipliers in Bessel potential spaces, for which we present a new and simpler proof as well. We apply the results to characterize the fractional domain spaces of the first derivative operator on the half line.
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Full text
Complex interpolation with Dirichlet boundary conditions on the half line
We prove results on complex interpolation of vector-valued Sobolev spaces over the half-line with Dirichlet boundary condition. Motivated by applications in evolution equations, the results are presented for Banach space-valued Sobolev spaces with a power weight. The proof is based on recent results on pointwise multipliers in Bessel potential spaces, for which we present a new and simpler proof as well. We apply the results to characterize the fractional domain spaces of the first derivative operator on the half line.
The first and third author
are supported by the VIDI subsidy 639.032.427 of the Netherlands Organisation for Scientific Research (NWO)
1. Introduction
The main result of the present paper is the following. Let W01,p(R+;X) be the first order Sobolev space over the half line with values in a UMD Banach space X vanishing at t=0, where p∈(1,∞). Then for complex interpolation we have
[TABLE]
see Theorems 6.7 and (6.6). Here H0θ,p denotes the fractional order Bessel potential space with vanishing trace for θ>1/p, and H0θ,p=Hθ,p for θ<1/p. In more generality, we consider spaces with Muckenhoupt power weights wγ(t)=tγ, where the critical value 1/p is shifted accordingly.
In the scalar-valued case X=C, the result is well-known and due to Seeley [43]. The vector-valued result was already used several times in the literature without proof. Seeley also considers the case θ=1/p, which we ignore throughout for simplicity, and the case of domains Ω⊆Rd. The corresponding result for real interpolation is due to Grisvard [17] and more elementary to prove.
At the heart of complex interpolation theory with boundary conditions is the pointwise multiplier property of the characteristic function of the half-space 1R+ on Hθ,p(R;X) for 0<θ<1/p. It is due to Shamir [44] and Strichartz [45] in the scalar-valued case. In [36] by the second and third author, a general theory of pointwise multiplication of weighted vector-valued functions was developed. As a main application the multiplier result was extended to the vector-valued and weighted setting. An alternative approach to this was found by the first author in [27] and is based on a new equivalent norm for vector-valued Bessel potential spaces. In Section 4 we present a new and simpler proof of the multiplier property of 1R+, which is based on the representation of fractional powers of the negative Laplacian as a singular integral and the Hardy-Hilbert inequality.
For future reference and as it is only a minimal extra effort, we will formulate and prove some elementary assertions for the half space R+d for d≥1 or even domains, and general Ap weights w. In order to make the presentation as self-contained as possible, we further fully avoid the use of Triebel–Lizorkin spaces and Besov spaces, but we point out where they could be used. We will only use the UMD property of X through standard applications of the Mihlin multiplier theorem. Several results will be presented in such a way that the UMD property is not used. A detailed explanation of the theory of UMD spaces and their connection to harmonic analysis can be found in the monograph [20]. In their reflexive range, all standard function spaces are UMD spaces.
The complex interpolation result has applications in the theory of evolution equations, as it yields a characterization of the fractional power domains of the time derivative D((d/dt)θ) and D((−d/dt)θ) on R+. Here the half line usually stands for the time variable and X is a suitable function space for the space variable. For instance such spaces can be used in the theory of Volterra equations (see [38, 48, 49]), in evolution equations with form methods (see [9, 12]), in stochastic evolution equations (see [37]).
In order to deal with rough initial values it is useful to consider a power weights wγ(t)=tγ in the time variable. Examples of papers in evolution equation where such weights are used include [3, 8, 23, 28, 31, 32, 35, 39, 41]. The monographs [2, 29, 40] are an excellent source for applications of weighted spaces to evolution equations. In order to make our results available to this part of the literature as well, we present our interpolation results for weighted spaces.
For the application to evolution equations it suffices to consider interpolation of vector-valued Sobolev spaces over R+ with Dirichlet boundary conditions and therefore we focus on this particular case. In a future paper we extend the results of [17] and [43] to weighted function spaces on more general domains Ω⊆Rd, in the scalar valued situation, where one of the advantages is that Bessel potential spaces have a simple square function characterization.
Overview
•
In Section 2 we discuss some preliminaries from harmonic analysis.
•
In Section 3 we introduce the weighted Sobolev spaces and Bessel potential spaces.
•
In Section 4 we present an elementary proof of the pointwise multiplier theorem.
•
In Section 5 we present some results on interpolation theory without boundary conditions.
•
In Section 6 we present the main results on interpolation theory with boundary conditions and applications to fractional powers.
Notation
R+d=(0,∞)×Rd−1 denotes the half space. We write x=(x1,x~)∈Rd with x1∈R and x~∈Rd−1 and define the weight wγ by wγ(x1,x~)=∣x1∣γ. Sometimes it will be convenient to also write (t,x)∈Rd with t∈R and x∈Rd−1. The operator F denotes the Fourier transform. We write A≲pB whenever A≤CpB where Cp is a constant which depends on the parameter p. Similarly, we write A≂pB if A≲pB and B≲pA.
Acknowledgements
We thank the anonymous referees for their helpful comments.
2. Preliminaries
2.1. Weights
A locally integrable function w:Rd→(0,∞) will be called a weight function. Given a weight function w and a Banach space X we define Lp(Rd,w;X) as the space of all strongly measurable f:Rd→X for which
[TABLE]
is finite. Here we identify functions which are a.e. equal.
Although we will be mainly interested in a special class of weights, it will be natural to formulate some of the result for the class of Muckenhoupt Ap-weights. For p∈(1,∞), we say that w∈Ap if
[TABLE]
Here the supremum is taken over all cubes Q⊆Rd with sides parallel to the coordinate axes. For p∈(1,∞) and a weight w:Rd→(0,∞) one has w∈Ap if and only the Hardy–Littlewood maximal function is bounded on Lp(Rd,w).
We refer the reader to [16, Chapter 9] for standard properties of Ap-weights. For a fixed p and a weight w∈Ap, the weight w′=w−1/(p−1)∈Ap′ is the p-dual weight. By Hölder’s inequality one checks that
[TABLE]
for f∈Lp(Rd,w) and g∈Lp′(Rd,w′). Using this, for each w∈Ap one can check that Lp(Rd,w;X)⊆Lloc1(Rd;X).
The following will be our main example.
Example 2.1*.*
Let
[TABLE]
As in [16, Example 9.1.7]) one sees that wγ∈Ap if and only if γ∈(−1,p−1).
Lemma 2.2**.**
Let p∈(1,∞) and w∈Ap. Assume ϕ∈L1(Rd) and ∫ϕdx=1. Let ϕn(x)=ndϕ(nx). Assume ϕ satisfies any of the following conditions:
(1)
ϕ* is bounded and compactly supported*
2. (2)
There exists a radially decreasing function ψ∈L1(Rd) such that ∣ϕ∣≤ψ a.e.
Then for all f∈Lp(Rd;X), ϕn∗f→f in Lp(Rd,w;X) as n→∞. Moreover, there is a constant C only depending on ϕ such that ∥ϕn∗f∥≤CMf almost everywhere.
Proof.
For convenience of the reader we include a short proof. By [20, Theorem 2.40 and Corollary 2.41] ϕn∗f→f almost everywhere and ∥ϕn∗f∥≤∥ψ∥L1(Rd)Mf almost everywhere, where M denotes the Hardy–Littlewood maximal function. Therefore, the result follows from the dominated convergence theorem.
∎
2.2. Fourier multipliers and UMD spaces
Let S(Rd;X) be the space of X-valued Schwartz functions and let S′(Rd;X)=L(S(Rd),X) be the space of X-valued tempered distributions. For m∈L∞(Rd) let Tm:S(Rd;X)→S′(Rd;X) be the Fourier multiplier operator defined by
[TABLE]
There are many known conditions under which Tm is a bounded linear operator on Lp(Rd;X).
In the scalar-valued the set of all Fourier multiplier symbols on L2(Rd) for instance coincides with L∞(Rd).
In the case p∈(1,∞)∖{2} a large set of multipliers for which Tm is bounded is given by Mihlin’s multiplier theorem. In the vector-valued case difficulties arise and geometric conditions on X are needed already if d=1 and m(ξ)=sign(ξ); in fact, in [5, 6] it was shown that in this specific case the boundedness of Tm on Lp(R;X) characterizes the UMD property of X.
Since the work of [5, 6, 30] it is well-known that the right class of Banach spaces for vector-valued harmonic analysis is the class of UMD Banach spaces, as many of the classical results in harmonic analysis, such as the classical Mihlin multiplier theorem, have been extended to this setting. We refer to [7, 20, 42] for details on UMD spaces and Fourier multiplier theorems.
All UMD spaces are reflexive. Conversely, all spaces in the reflexive range of the classical function spaces have UMD: e.g.: Lp, Bessel potential spaces, Besov spaces, Triebel-Lizorkin spaces, Orlicz spaces.
The following result is a weighted version of the Mihlin multiplier theorem which can be found in [36, Proposition 3.1] and is a simple consequence of [19].
Proposition 2.3**.**
Let X be a UMD space, p∈(1,∞) and w∈Ap. Assume that m∈Cd+2(Rd∖{0}) satisfies
[TABLE]
Then Tm is bounded on Lp(Rd,w;X) and has an operator norm that only depends Cm,d,p,X,[w]Ap.
3. Weighted function spaces
In this section we present several results on weighted function spaces, which do not require the UMD property of the underlying Banach space (except in Proposition 3.2).
3.1. Definitions and basic properties
For an open set Ω⊆Rd let D(Ω) denote the space compactly supported smooth functions on Ω equipped with its usual inductive limit topology.
For a Banach space X, let D′(Ω;X)=L(D(Ω),X) be the space of X-valued distributions. For a distribution u∈D′(Ω;X) and an open subset Ω0⊆Ω, we define the restriction u∣Ω0∈D′(Ω0;X) as u∣Ω0(f)=u(f) for f∈D(Ω0).
For p∈(1,∞) and w∈Ap let Wk,p(Ω,w;X)⊆D′(Ω;X) be the Sobolev space of all f∈Lp(Ω,w;X) with ∂αf∈Lp(Ω,w;X) for all ∣α∣≤k and set
[TABLE]
Here for α∈Nd, ∂α=∂1α1…∂dαd.
Let Js denote the Bessel potential operator of order s∈R defined by
[TABLE]
where f denotes the Fourier transform of f and Δ=∑j=1d∂j2. For p∈(1,∞), s∈R and w∈Ap let Hs,p(Rd,w;X)⊆S′(Rd;X) denote the Bessel potential space of all f∈S′(Rd;X) for which Jsf∈Lp(Rd,w;X) and set
[TABLE]
In the following lemma we collect some properties of the operators Js.
Lemma 3.1**.**
Fix s>0. There exists a function Gs:Rd→[0,∞) such that Gs∈L1(Rd) and J−sf=Gs∗f for all f∈S′(Rd;X). Moreover, Gs has the following properties:
(1)
For all ∣y∣≥2, Gs(y)≲s,de−2∣y∣.
2. (2)
For ∣x∣≤2,
[TABLE]
3. (3)
for all s>k≥0 and all ∣α∣≤k, there exists a radially decreasing function ϕ∈L1(Rd) such that ∣∂αGs∣≤ϕ pointwise.
In particular, if d=1, p∈(1,∞), γ∈(−1,p−1) and s>p1+γ, then Gs∈Lp′(R,wγ′).
Proof.
The fact that the positive function Gs∈L1(Rd) exists, together with (1) and (2), follows from [16, Section 6.1.b].
To prove (3), we use the following representation of Gs (see [16, Section 6.1.b]):
[TABLE]
By induction one sees that ∂αGs(x) is a linear combination of functions of the form Gs−2j(x)∣x∣β with ∣β∣≤j≤k. Therefore, by (2) for ∣x∣≤2, ∣∂αGs(x)∣≲s,d,α∣x∣ε−d for some ε∈(0,d). On the other hand for ∣x∣≥2, ∣∂αGs(x)∣≲s,d,α∣x∣βe−2∣x∣≲d,s,ke−4∣x∣. Now the function ϕ(x)=C1∣x∣ε−d for ∣x∣≤2 and ϕ(x)=C2e−4∣x∣ for certain constants C1,C2>0. satisfies the required conditions.
To prove the final assertion for d=1, note that the blow-up behaviour near [math] gets worse as s decreases. Therefore, without loss of generality we may assume that s∈(p1+γ,1), in which case (2) yields
[TABLE]
which is integrable. Integrability, for ∣x∣>2, is clear from (1).
∎
The following result is proved in [36, Proposition 3.2 and 3.7] by a direct application of Proposition 2.3.
Proposition 3.2**.**
Let X be a UMD space, p∈(1,∞), k∈N0, w∈Ap.
Then Hk,p(Rd,w;X)=Wk,p(Rd,w;X) with norm equivalence only depending on d, X, p, k and [w]Ap.
The UMD property is necessary in Proposition 3.2
(see [20, Theorem 5.6.12]). Sometimes it can be avoided by instead using the following simple embedding result which holds for any Banach space. The sharper version Wk,p(Rd,w;X)↪Hs,p(Rd,w;X) if s<k and k∈N0. can be obtained from [33, Propositions 3.11 and 3.12] but is more complicated.
Lemma 3.3**.**
Let X be a Banach space, p∈(1,∞), k∈N0, s∈(k,∞) and w∈Ap. Then the following continuous embeddings hold
[TABLE]
with embedding constants which only depend on d,s,k and [w]Ap.
Proof.
The first embedding is immediate from J2kf=(1−Δ)kf and Leibniz’ rule. For the second embedding let f∈Hs,p(Rd,w;X) and write fs=Jsf∈Lp(Rd,w;X). By Lemma 3.1 (3) and Lemma 2.2, for all ∣α∣≤k,
[TABLE]
where ϕ∈L1(Rd) is a radially decreasing function depending on α, k and s.
Therefore, by the boundedness of the Hardy–Littlewood maximal function, we have ∂αf∈Lp(Rd,w;X) with
[TABLE]
Now the result follows by summation over all α.
∎
We proceed with two density results.
Lemma 3.4**.**
Let X be a Banach space, p∈(1,∞), s∈R and w∈Ap.
Then S(Rd;X)↪Hs,p(Rd,w;X)↪S′(Rd;X). Moreover, Cc∞(Rd)⊗X is dense in Hs,p(Rd,w;X).
Proof.
First we prove that S(Rd;X)↪Hs,p(Rd,w;X). It suffices to prove this in the case s=0 by continuity of Js=(1−Δ)s/2 on S(Rd;X). In the case s=0, the continuity of the embedding follows from
To prove the density assertion note that Lp(Rd,w)⊗X is dense in Lp(Rd,w;X) and S(Rd) is dense in Lp(Rd,w) (see [16, Exercise 9.4.1])
it follows that S(Rd)⊗X is dense in Lp(Rd,w;X). Since J−s leaves S(Rd) invariant, also S(Rd)⊗X is dense in Hs,p(Rd,w;X).
Combining this with S(Rd;X)↪Hs,p(Rd,w;X) and the fact that Cc∞(Rd) is dense in S(Rd) (see [10, Lemma 14.7]) we obtain the desired density assertion.
To prove the embedding Hs,p(Rd,w;X)↪S′(Rd;X) it suffices again to consider s=0. In this case from (2.1) and S(Rd)↪Lp′(Rd,w′) densely, we deduce
[TABLE]
∎
Lemma 3.5**.**
Let X be a Banach space, p∈(1,∞), k∈N and w∈Ap.
Then S(Rd;X)↪Wk,p(Rd,w;X)↪S′(Rd;X). Moreover, Cc∞(Rd)⊗X is dense in Wk,p(Rd,w;X).
Proof.
The case k=0 follows from Lemma 3.4
and the case k≥1 follow by differentiation.
Let ϕ∈Cc∞(Rd) be such that ∫Rdϕdx=1 and define ϕn:=ndϕ(n⋅) for every n∈N.
Then, by Lemma 2.2 and standard properties of convolutions, fn:=ϕn∗f→f in Wk,p(Rd,w;X) as n→∞ with ϕn∗f∈W∞,p(Rd,w;X)=⋂l∈NWl,p(Rd,w;X).
In particular, W2k+2,p(Rd,w;X) is dense in Wk,p(Rd,w;X).
This yields Hk+1,p(Rd,w;X)↪dWk,p(Rd,w;X) by Lemma 3.3.
The density of Cc∞(Rd)⊗X in Wk,p(Rd,w;X) now follows from Lemma 3.4.
∎
Lemma 3.6**.**
Let X be a Banach space, p∈(1,∞), s∈R and w∈Ap.
Assume ϕ∈Cc∞(R) with ∫ϕdx=1. Let ϕn(x)=ndϕ(nx).
Then, for all f∈Hs,p(Rd,w;X),
[TABLE]
with ϕn∗f→f in Hs,p(Rd,w;X) as n→∞ with ϕn∗f∈H∞,p(Rd,w;X)=⋂t∈RHt,p(Rd,w;X).
Proof.
The first part of the statement follows from Lemma 2.2 and Js(ϕn∗f)=ϕn∗Jsf.
For the last part, note that ϕn∗f=J−s[ϕn∗Jsf]∈H∞,p(Rd,w;X) by basic properties of convolutions in combination with Lemma 3.3.
∎
The following version of the Hardy inequality will be needed (see [33, Corolllary 1.4] for a related result). The result can be deduced from [34, Theorem 1.3 and Proposition 4.3] but for convenience we include an elementary proof.
Lemma 3.7** (Hardy inequality with power weights).**
Let γ∈(−1,p−1) and s∈(0,1). Let wγ(t,x)=∣t∣γ for t∈R and x∈Rd−1. Then
Hs,p(Rd,wγ;X)↪Lp(Rd,wγ−sp;X).
Proof.
It suffices to prove ∥Gs∗f∥Lp(wγ−sp;X)≲p,s,d,γ∥f∥Lp(wγ;X), where Gs is as in Lemma 3.1 and f∈Lp(wγ;X). Since Gs≥0, by the triangle inequality it suffices to consider the case of scalar functions f with f≥0.
To prove the result we first apply Minkowski’s and Young’s inequality in Rd−1:
[TABLE]
Here gs(t)=∥Gs(t,⋅)∥L1(Rd−1) and ϕ(τ)=∥f(τ,⋅)∥Lp(Rd−1). Then for ∣t∣≤2, by Lemma 3.1 (1) and (2),
[TABLE]
where we used s<1. For ∣t∣>2, by Lemma 3.1 (2) and ∣(t,x)∣≂∣t∣+∣x∣, we find
[TABLE]
Finally by the weighted version of Young’s inequality (see and [22, Theorem 3.4(3.7)]) in dimension one, we find that
[TABLE]
where C=supt∈R∣t∣1−sgs(t)<∞.
∎
We end this section with a weighted version of the classical Hardy–Hilbert inequality.
Lemma 3.8** (Hardy–Hilbert inequality with power weights).**
Let p∈(1,∞) and γ∈(−1,p−1). Let wγ(x1,x~)=∣x1∣γ and k(x,y)=((∣x1∣+∣y1∣)2+∣x~−y~∣2)d/21, where x=(x1,x~) and y=(y1,y~).
Then the formula
[TABLE]
yields a well-defined bounded linear operator Ik on Lp(Rd,wγ).
Proof.
It suffices to consider h≥0.
Moreover, by symmetry it is enough to consider x1,y1>0. Thus we need to show that
[TABLE]
Step I.The case d=1. Replacing k by
[TABLE]
with β=γ/p, it suffices to consider the unweighted case.
To prove the required result we apply Schur’s test in the same way as in [14, Theorem 5.10.1]. Let s(x)=t(x)=x−pp′1. Then since −1<β−p′1<0
[TABLE]
Similarly, since −1<−β−p1<0
[TABLE]
Step II.The general case.
By Minkowski’s inequality we find
[TABLE]
Fix y1>0 and let gr(y~)=f(y1,ry~). Setting r=x1+y1 and substituting u:=x~/r and v:=y~/r we can write
[TABLE]
where we applied Young’s inequality for convolutions. Therefore,
[TABLE]
Taking Lp((0,∞),wγ)-norms in x1 and applying Step I yields the required result.
∎
Remark 3.9*.*
Actually, the kernel k of Lemma 3.8 is a standard Calderón–Zygmund kernel, because k is a.e. differentiable and
[TABLE]
Although we will not need it below let us note that
[19, Corollary 2.10] implies that Ik is bounded on Lp(Rd,w) for any w∈Ap
4. Pointwise multiplication with 1R+d
In this section we prove the pointwise multiplier result, which is central in the characterization of the complex interpolation spaces of Sobolev spaces with boundary conditions in Section 6. Let wγ(x1,x~)=∣x1∣γ, where x1∈R and x~∈Rd−1.
Theorem 4.1**.**
Let X be a UMD space, p∈(1,∞), γ∈(−1,p−1), γ′=−γ/(p−1), and assume −p′γ′+1<s<pγ+1. Then for all f∈Hs,p(Rd,wγ;X)∩Lp(Rd,wγ;X), we have 1R+df∈Hs,p(Rd,wγ;X) and
[TABLE]
and therefore, pointwise multiplication by 1R+d extends to a bounded linear operator on Hs,p(Rd,wγ;X).
To prove this the UMD property will only be used through the norm equivalence of Lemma 4.2 below.
Lemma 4.2**.**
Let X be a UMD space, p∈(1,∞), s∈R, σ≥0, w∈Ap. Then
[TABLE]
defines for each r∈R (by extension by density) a bounded linear operator from Hr+σ,p(Rd,w;X) to Hr,p(Rd,w;X), independent of r and w (in the sense of compatibility), which we still denote by (−Δ)σ/2.
Moreover, f∈Hs+σ,p(Rd,w;X) if and only if f,(−Δ)σ/2f∈Hs,p(Rd,w;X), in which case
[TABLE]
Proof.
All assertions follow from the fact that the symbols
In the proof of Theorem 4.1 we will use the norm equivalence of the above lemma via (a variant of) a well known representation for (−Δ)σ/2 as a singular integral.
For f∈Hσ,p(Rd) this representation reads as follows:
[TABLE]
with limit in Lp(Rd) (see [26, Theorem 1.1(e)]); here Th denotes the left translation and Cd,σ is a constant only depending on d and σ.
In the proof we want to use a formula as above for f replaced by 1R+df, which in general is an irregular function even if f is smooth; in particular, a priori it is not clear that 1R+df∈Hσ,p(Rd). We overcome this technical obstacle by Proposition 4.4 below, which provides a (non sharp) representation formula for (−Δ)σ/2 in spaces of distributions.
For the proof of Proposition 4.4 we need the following simple identity.
Lemma 4.3**.**
For each σ∈(0,1) there exists a constant cd,σ∈(−∞,0) such that
[TABLE]
Moreover, for all ϕ∈S(Rd)
[TABLE]
Proof.
Let ξ∈Rd∖{0} and choose R∈O(n) with Rξ=∣ξ∣e1.
Then h⋅ξ=Rh⋅Rξ=∣ξ∣Rh⋅e1 and the substitution y=∣ξ∣Rh yields
[TABLE]
Observing that the integral on the right is a number in (−∞,0), the first identity follows.
Next we show (4.1).
Given ϕ∈S(Rd), the first identity gives
[TABLE]
Since ϕ∈S(Rd) and
[TABLE]
we may invoke Fubini’s theorem in order to get
[TABLE]
as desired.
∎
For f∈S′(Rd;X) let δhf=Thf−f, where Th denotes the left translation by h. For 0<r<R let A(r,R):={x∈Rd:r<∣x∣<R} be an annulus.
Proposition 4.4** (Representation of (−Δ)2σ).**
Let p∈(1,∞) and σ∈(0,1).
For all s≥0 and f∈Hs,p(Rd)⊗X⊂Lp(Rd;X) we have
The weights are left out on purpose, because translations are not well-behaved on weighted Lp-spaces. Moreover, no UMD is required in the result above.
Proof.
We prove this proposition by proving the following three statements:
(1)
The linear operator
[TABLE]
is bounded from Hs,p(Rd;X) to L1(Rd;Hs−2,p(Rd;X)) for all s∈R and thus gives rise to a bounded linear operator
[TABLE]
2. (2)
For all s≥0 we have
[TABLE]
for every f∈Hs,p(Rd;X)⊂Lp(Rd;X).
3. (3)
For all f∈H−∞,p(Rd)⊗X,
[TABLE]
where cd,σ is the constant of Lemma 4.3.
Here H−∞,p(Rd)=⋃s∈RHs,p(Rd).
(1): To prove this it is enough to establish the boundedness from Hs,p(Rd;X) to L1(Rd;Hs−2,p(Rd;X)).
As the Bessel potential operator Js commutes with δh, we may restrict ourselves to the case s=2.
Since by Lemma 3.3H2,p(Rd;X)↪W1,p(Rd;X), we only need to estimate
[TABLE]
To this end, let f∈W1,p(Rd;X).
Then
[TABLE]
where the integral is an Lp(Rd;X)-valued Bochner integral.
It follows that
(2): Let s≥0 and f∈Hs,p(Rd;X)⊂Lp(Rd;X).
By the first assertion and the Lebesgue dominated convergence theorem,
[TABLE]
where the integrals ∫A(r,R)∣h∣d+σδhfdh are Bochner integrals in Hs−2,p(Rd;X).
As f∈Lp(Rd;X), h↦∣h∣d+σδhf is in L1(A(r,R);Lp(Rd;X)) for every 0<r<R<∞. Since Lp(Rd;X),Hs−2,p(Rd;X)↪S′(Rd;X), it follows that the integrals ∫A(r,R)∣h∣d+σδhfdh in (4.4) can also be considered as Bochner integrals in Lp(Rd;X), implying that ∫A(r,R)∣h∣d+σδhfdh=[x↦∫A(r,R)∣h∣d+σδhf(x)dh] (see [20, Proposition 1.2.25]).
(3) By linearity it suffices to consider the scalar case f∈Hs,p(Rd) for some s∈R. By the density of S(Rd)⊆Hs,p(Rd) (see Lemma 3.4) it suffices to consider f∈S(Rd). Indeed, this follows from the boundedness of Iσ and (−Δ)σ/2 (see (1). Now (4.2) follows from well-known results (see [26, Theorem 1.1(e)]). For convenience we include a direct proof.
Using Lemma 4.3, for each f∈S(Rd;X) we find
[TABLE]
where all integrals are in S′(Rd;X).
By (1), for every f∈S(Rd;X)⊂H0,p(Rd;X) we have Iσf=∫Rd∣h∣d+σδhfdh, where the integral is taken in H−1,p(Rd;X)↪S′(Rd;X).
This proves (4.2), as desired.
∎
Finally we are in position to prove the pointwise multiplier result.
We only consider s≥0. The case s<0 follows from a duality argument using [36, Proposition 3.5].
By Lemma 3.4 it is enough to prove ∥1R+df∥Hs,p(Rd,wγ;X)≲s,p,d,γ,X∥f∥Hs,p(Rd,wγ;X) for an arbitrary f∈S(Rd)⊗X. Let g:=1R+df∈Lp(Rd)⊗X. By Lemma 4.2, we have
[TABLE]
Clearly, ∥g∥Lp(Rd,wγ;X)≤∥f∥Lp(Rd,wγ;X)
from which we see that it suffices to show
We first consider {G1,j}j∈N.
Since Is,jf⟶j→∞(−Δ)s/2f in Lp(Rd;X) by Proposition 4.4,
it follows that G1:=1R+d(−Δ)s/2f=limj→∞G1,j in Lp(Rd;X).
By Proposition Lemma 4.2,
[TABLE]
We next consider {G2,j}j∈N.
Observing that
[TABLE]
for all h=(h1,h~)∈Rd and t∈R with (t,h1)∈S, we find
[TABLE]
where k(x,y)=((∣x1∣+∣y1∣)2+∣y~−x~∣2)2d.
Applying Lemma 3.8 to the function ϕ(y)=∣y1∣−s∥f(y)∥X
we thus obtain
[TABLE]
where in the last step we applied Lemma 3.7. It follows that the limit G2:=limj→∞G2,j exists in Lp(Rd,wγ;X) and, moreover,
[TABLE]
Finally, combining the just obtained results for {G1,j}j∈N and {G2,j}j∈N, we see that
G:=G1+G2=limj→∞Is,jg in Lp(Rd,wγ;X)+Lp(Rd;X)↪S′(R;X)
and (4.6) holds as desired.
∎
5. Interpolation theory without boundary conditions
For details on interpolation theory we refer the reader to [4, 46]. In this section we present some weighted and vector-valued versions of known results.
The following extension operator will allow us to reduce the half space case R+d to the full space Rd.
Lemma 5.1** (Extension operator).**
Let X be a Banach space. Let p∈(1,∞), and m∈N0.
Let w∈Ap be such that w(−x1,x~)=w(x1,x~) for x1∈R and x~∈Rd−1. Then there exists an operator E+m:Lp(R+d,w;X)→Lp(Rd,w;X) such that
(1)
For all f∈Lp(R+d,w;X), (E+mf)∣R+d=f;
2. (2)
for all k∈{0,…,,m}, E+m:Wk,p(R+d,w;X)→Wk,p(Rd,w;X) is bounded,
Moreover, if f∈Lp(R+d,w;X)∩Cm(R+d;X), then E+mf is m-times continuous differentiable on Rd.
By a reflection argument the same holds for R−d. The corresponding operator will be denoted by E−m.
Proof.
The result is a simple extension of the classical construction given in [1, Theorem 5.19] to the weighted setting.
The final assertion is clear from the construction of E+m.
∎
To define Bessel potential spaces on domains, we proceed in an abstract way using factor spaces.
Definition 5.2**.**
Let F↪D′(Rd;X) be a Banach space.
Define the restricted space/factor space to an open set Ω⊆Rd as
[TABLE]
and let
[TABLE]
We say that E is an extension operator for F(Ω) if
(1)
for all f∈F(Ω), (Ef)∣Ω=f;
2. (2)
E:F(Ω)→F* is bounded.*
For p∈(1,∞), w∈Ap and an open set Ω⊂Rd, we define the Bessel potential space Hs,p(Ω,w;X) as the factor space
[TABLE]
By Lemma 5.1 and for w as stated there, we find that Wk,p(R+d,w;X) can be identified (up to an equivalent norm) with the factor space [Wk,p(Rd,w;X)](R+d), where an extension operator can also be found.
Indeed, let Wfactork,p(R+d,w;X)=[Wk,p(Rd,w;X)](R+d) denote the factor space. For f∈Wfactork,p(Rd,w;X) let g∈Wk,p(Rd,w;X) be such that g∣R+d=f. Then
[TABLE]
Taking the infimum over all of the above g, we find
[TABLE]
Next let f∈Wk,p(R+d,w;X). Then E+f∈Wk,p(Rd,w;X) and
[TABLE]
Next we present two abstract lemmas to identify factor spaces in the complex interpolation scale. The result is a straightforward consequence of [46, Theorem 1.2.4]. We include the short in order to be able to track the constants. For details on complex interpolation theory we refer to [46, Section 1.9.3].
Lemma 5.3**.**
Let (X0,X1) and (Y0,Y1) be interpolation couples and let Xθ=[X0,X1]θ and Yθ=[Y0,Y1]θ for a given θ∈(0,1). Assume R:X0+X1→Y0+Y1 and S:Y0+Y1→X0+X1 are linear operators such that S∈L(Yj,Xj), R∈L(Xj,Yj) and RS is the identity operator on Yj for j∈{0,1}. Then
SR defines a projection on Xθ and
R is an isomorphism from SR(Xθ) onto Yθ with inverse S. Moreover, the following estimates hold:
[TABLE]
where CR=maxj∈{0,1}∥R∥L(Xj,Yj) and CS=maxj∈{0,1}∥S∥L(Xj,Yj).
Proof.
By complex interpolation we know
[TABLE]
and RS is the identity operator on Yθ. This proves the upper estimates for S and R. To see that SR is a projection note that (SR)(SR)=SR. The lower estimate for S follows from
[TABLE]
To prove the lower estimate for R note that for x:=SRu∈SR(Xθ)
[TABLE]
∎
Lemma 5.4**.**
Let F0,F1↪D′(Rd;X) be two Banach spaces. For θ∈(0,1), let
[TABLE]
Let Ω⊆Rd be an open set, and define Fθ(Ω) as in Definition 5.2, and assume there is an extension operator E for Fs(Ω) for s∈{0,1}. Then
[F0(Ω),F1(Ω)]θ=Fθ(Ω) and
[TABLE]
where C only depends on the norms of the extension operator. Moreover, E is an extension operator for Fθ(Ω).
Proof.
Define R:Fj→Fj(Ω) by Rf=f∣Ω and S:Fj(Ω)→Fj as S=E. Then ∥R∥≤1,∥S∥≤C and RS=I. From Lemma 5.3 we conclude that for all f∈[F0(Ω),F1(Ω)]θ
[TABLE]
Conversely, let f∈Fθ(Ω). Choose, g∈Fθ such that Rg=g∣Ω=f. Since ∥R∥≤1, by complex interpolation we find
[TABLE]
Taking the infimum over all g as above, the result follows.
To show the final assertion, note that E∈L(Fθ(Ω),Fθ) by the above. Moreover, for f∈F0(Ω)∩F1(Ω), (Ef)∣Ω=f. By density (see [46, Theorem 1.9.3]) this extends to all f∈Fθ(Ω).
∎
Proposition 5.5**.**
Let X be a UMD space, p∈(1,∞), k∈N0 and assume w∈Ap is such that w(x1,x~)=w(−x1,x~) for x1∈R and x~∈Rd−1. Then Hk,p(R+d,w;X)=Wk,p(R+d,w;X)
Proof.
This is immediate from Proposition 3.2 and the fact that Wk,p(R+d,w;X) coincides with the factor space [Wk,p(Rd,w;X)](R+d).
∎
Next we identify the complex interpolation spaces of Hs,p(Ω,w;X). Here the UMD property is needed to obtain bounded imaginary powers of −Δ.
Proposition 5.6**.**
Let X be a UMD space and p∈(1,∞).
Let w∈Ap be such that w(−x1,x~)=w(x1,x~) for all x1∈R and x~∈Rd−1.
(1)
Let θ∈[0,1] and s0,s1,s∈R be such that s=s0(1−θ)+s1θ. Then for Ω=Rd or Ω=R+d one has
[TABLE]
2. (2)
For each m∈N0 there exists an E+m∈L(H−m,p(R+d,w;X),H−m,p(Rd,w;X)) such that
•
for all ∣s∣≤m, E+∈L(Hs,p(R+d,w;X),Hs,p(Rd,w;X)),
•
for all ∣s∣≤m, f↦(E+f)∣R+d equals the identity operator on Hs,p(R+,w;X).
Moreover, if f∈Lp(R+d,w;X)∩Cm(R+d;X), then E+mf∈Cm(Rd;X).
By a reflection argument the same holds for R−d. The corresponding operator will be denoted by E−m.
Proof.
(1): For Ω=Rd, the result follows from [36, Proposition 3.2 and 3.7] (see [20, Theorem 5.6.9] for the unweighed case).
(2): Fix m∈N. We first construct E+m∈L(H−m,p(Rd,w;X)) such that
(i)
E+m∈L(Hs,p(Rd,w;X)) for all ∣s∣≤m;
2. (ii)
E+mf∣R+d=f∣R+d;
3. (iii)
E+mf=0 if f∣R+d=0;
Given E+m we can define E+m:Hs,p(R+d,w;X)→Hs,p(Rd,w;X)
by E+mf=E+mf where f∈Hs,p(Rd,w;X) satisfies f∣R+d=f. This is well-defined by (iii).
In order to construct E+m let 0<λ1<…<λ2m+2<∞ and b1,…,b2m+2∈R be as in [46, 2.9.3]. For λ∈R∖{0} we write Tλf(x)=f(−λx1,x~). Let E+m∈L(Lp(Rd,w;X)) and E+m∈L(Lp′(Rd,w′;X∗)) be defined by
[TABLE]
Then one can check that
[TABLE]
Moreover, by the special choice of b1,…,b2m+2 it is standard to check that E+m∈L(Wm,p(Rd,w;X)) and E+m∈L(Wm,p′(Rd,w′;X∗)). In view of (1) for Ω=Rd and Proposition 3.2, complex interpolation gives E+m∈L(Hs,p(Rd,w;X)) and E+m∈L(Hs,p′(Rd,w′;X∗)) for all 0≤s≤m.
Recall that Hs,p(Rd,w;X)=(H−s,p′(Rd,w′;X∗))∗ (see [36, Proposition 3.5]), X being reflexive as a UMD space (see [20, Theorem 4.3.3]). By the duality relation (5.1) we find that E+m extends to a bounded linear operator on Hs,p(Rd,w;X) for each s∈[−m,0]. Therefore, (i) follows and moreover (ii) follows by a density argument.
To check (iii) let f∈H−m,p(Rd,w;X) with f∣R+d=0 be given. Let ϕ∈Cc∞(R−d) be such that ∫ϕdx=1 and set ϕn:=n−dϕ(n⋅) for n∈N. Then, by Lemma 3.6, ϕn∗f→f in H−m,p(Rd,w;X) and ϕn∗f∈Lp(Rd,w;X). Now since ϕn∗f∣R+d=0 it follows that E+mf∣R+d=limn→∞E+mϕn∗f∣R+d=0.
Finally, note that for f∈Lp(R+d,w;X)∩Cm(R+d;X), Em+f∈Cm(R−d;X)⊕Cm(R+d;X) with
[TABLE]
and by the special choice of b1,…,b2m+2, one can check that f∈Cm(Rd;X).
Now (1) for Ω=R+d follows from Lemma 5.4 and (2).
∎
For an open set Ω⊆Rd, and s∈R let HΩs,p(Rd,wγ;X) be the closed subspace of Hs,p(Rd,wγ;X) of functions with support in Ω.
Proposition 5.7**.**
Let X be a UMD space, p∈(1,∞), k∈N, w(−x1,x~)=w(x1,x~) for all x1∈R and x~∈Rd−1. Let θ∈[0,1] and s0,s1,s∈R be such that s=s0(1−θ)+s1θ.
Then the following identity holds with equivalence of norms
[TABLE]
Proof.
To show this we consider the case of R+d. The other case can be proved in the same way. Let E−m be the (reflected) extension operator of Proposition 5.6 with m the least integer above max{∣s0∣,∣s1∣}.
Define R:Hs0∧s1,p(Rd,w;X)→HR+ds0∧s1,p(Rd,w;X) by
[TABLE]
and let S:HR+ds0∧s1,p(Rd,w;X)→Hs0∧s1,p(Rd,w;X) be the inclusion operator.
For each t∈[s0∧s1,m], R and S restrict to bounded linear operators R:Ht,p(Rd,w;X)→HR+dt,p(Rd,w;X) and S:HR+dt,p(Rd,w;X)→Ht,p(Rd,w;X) with the property that SR(Ht,p(Rd,w;X))=HR+dt,p(Rd,w;X).
Using Lemma 5.3 in combination with Proposition 5.6 we find that R restricts to an isomorphism from HR+ds,p(Rd,w;X)=SR(Hs,p(Rd,w;X)) to [HR+ds0,p(Rd,w;X),HR+ds1,p(Rd,w;X)]θ.
Since Rf=f for all f∈HR+ds,p(Rd,w;X), this proves the required identity for the interpolation space. The norm equivalence follows from the estimates in Lemma 5.3 as well.
∎
To end this section we present a variation of a classical interpolation inequality.
The result can be deduced from the weighted Gagliardo-Nirenberg type inequality [33, Proposition 5.1]. We provide a more direct proof which also yields additional information. The unweighted and scalar-valued case can be found in [24, Theorem 1.5.1]. However, the proof given there does not extend to the weighted setting. The lemma can also be deduced from Proposition 2.3, but this would require X to be a UMD space (cf. the proof of [13, Corollary 5.3]).
Lemma 5.8** (Gagliardo-Nirenberg inequality).**
Let X be a Banach space and k∈N. Let Ω=Rd or Ω=R+d. Let w∈Ap be such that w(−x1,x~)=w(x1,x~) if Ω=R+d. Then for all u∈Wk,p(Ω,w;X) and j∈{1,…,k−1},
[TABLE]
Proof.
By an iteration argument one sees that it suffices to consider j=1 and k=2 (see [24, Exercise 1.5.6]).
First consider the case Ω=Rd. For u∈W2,p(Rd,w;X), it follows from Lemma 3.3 that
[TABLE]
For λ>0 let uλ(x)=u(λx) and wλ=w(λx) and note that [w]Ap=[wλ]Ap. Then applying the estimate to uλ and the weight wλ, a substitution yields
[TABLE]
Minimizing over λ>0 the result follows.
In the case Ω=R+d we use a standard extension argument. Let E+2 be the extension operator from Lemma 5.1. Then by [1, Theorem 5.19], E+2 has the following additional property: for all ∣α∣≤2, ∂αE+2=Eα∂α, where Eα is an extension operator for W2−∣α∣(R+d,w;X). Therefore, from the case Ω=Rd applied to E+2u and the boundedness of the extension operators we find that
[TABLE]
Clearly, ∥E+nu∥Lp(Rd,w;X)≤∥u∥Lp(R+d,w;X). Moreover, since ∂αE+2=E0∂α,
[TABLE]
Therefore, the result follows if we combine the two estimates.
∎
6. Application to interpolation theory and the first derivative
For p∈(1,∞), s∈R and a weight w∈Ap, let H0s,p(R,w;X) denote the closure of Cc∞(R∖{0};X) in H0s,p(R,w;X).
In this section we characterize the complex interpolation space [Lp(R+,wγ;X),H01,p(R+,wγ;X)]θ. Moreover, we use this to characterize the domains of fractional powers of the first derivative.
6.1. Results on the whole real line
For k∈N0 let
[TABLE]
Since f(y)−f(x)=∫xyf′(t)dt, it follows that f has a version which is uniformly continuous on bounded intervals, and hence f(j)(0) for j∈{0,…,k} is defined in a pointwise sense
We will need the following simple lemma.
Lemma 6.1**.**
Let X be a Banach space and k∈N0. If f∈Wlock+1,1(R;X) satisfies f(0)=…=f(k)(0)=0, then 1R+f∈Wlock+1,1(R;X) with
[TABLE]
Proof.
Using an inductive argument we may reduce to the case k=0.
So suppose f∈Wloc1,1(R;X) satisfies f(0)=0.
Then f(x)=∫0xf′(t)dt for all x∈R, from which it follows that
[TABLE]
This shows 1R+f∈Wloc1,1(R;X) with (1R+f)′=1R+f′.
∎
Proposition 6.2**.**
Let X be a UMD Banach space, p∈(1,∞) and γ∈(−1,p−1). Assume s>p1+γ−1 and k∈N0 are such that p1+γ−1+k<s<p1+γ+k.
For all f∈Hs,p(R,wγ;X)∩Wloc,0k+1,1(R;X) we then have
[TABLE]
As a consequence, 1R+ is a pointwise multiplier on H0s,p(R,wγ;X).
Moreover, for all f∈H0s,p(R,wγ;X) it holds that
[TABLE]
Proof.
As in [36, Proposition 3.4] one checks the following equivalence of extended norms on S′(R;X):
[TABLE]
Let f∈Hs,p(R,wγ;X)∩Wloc,0k+1,1(R;X)
Using (6.2), Lemma 6.1 and Theorem 4.1 we find
[TABLE]
By a density argument we find that 1R+ is a pointwise multiplier on H0s,p(R,wγ;X).
Finally, to check that (6.1) holds for f∈H0s,p(R,wγ;X), observe that for 0≤j≤k, by (6.2) and the above estimate
[TABLE]
Therefore, if f∈H0s,p(R,wγ;X), then letting fn∈Cc∞(R∖{0};X) be such that fn→f in H0s,p(R,wγ;X), we find that ∂j(1R+fn)→∂j(1R+f) in Hs−k,p(R,wγ;X). Since ∂jfn→∂jf in Hs−k,p(R,wγ;X), by Theorem 4.1 also 1R+∂jfn→1R+∂jf in Hs−k,p(R,wγ;X).
The validity of (6.1) for functions from Cc∞(R∖{0}) and uniqueness of limits in Hs−k,p(R,wγ;X) yields (6.1) for general f∈H0s,p(R,wγ;X).
∎
Proposition 6.3**.**
Let γ∈(−1,p−1) and s∈R. Assume k∈N0 satisfies k+p1+γ<s.
Then the following assertions hold:
(1)
trk:Hs,p(R,wγ;X)∩Ck(R;X)→Xk* given by trkf=(f(0),f′(0),…,f(k)(0)) uniquely extends to a bounded linear mapping trk:Hs,p(R,wγ;X)→Xk+1.*
2. (2)
If f∈Hs,p(R,wγ;X) satisfies f∣(0,δ)=0 or f∣(−δ,0)=0 for some δ>0, then trkf=0.
3. (3)
There exists a bounded mapping extk:Xk+1→Hs,p(R,wγ;X) such that trk(extk) is the identity on Xk+1.
Proof.
We first prove (1).
By Lemma 3.4, it is enough to establish boundedness of
[TABLE]
Choosing xj∗∈X∗ with ∥xj∗∥=1 and ∥f(j)(0)∥=⟨f(j)(0),xj∗⟩ for each j∈{0,…,k} we have
⟨f,xj∗⟩∈Hs,p(R,wγ)∩Ck(R) with
[TABLE]
So we may restrict ourselves to the case X=C.
Recall from [36, Proposition 3.4] that d/dt is a bounded linear operator from Hσ,p(R,wγ) to Hσ−1,p(R,wγ) for every σ∈R.
By differentiation it thus suffices to prove that, given θ∈(p1+γ,p1+γ+1), the following estimate holds
[TABLE]
Here we actually only need to consider f∈Hθ,p(R,wγ)∩Cc(R); indeed, given η∈Cc∞(R) with η(0)=1, f↦ηf defines by complex interpolation (see Proposition 5.6) a bounded linear operator on Hθ,p(R,wγ) and we may consider ηf instead of f.
Using Lemma 3.6 together with [15, Theorem 1.2.19] one can check that Cc∞(R) is dense in Hθ,p(R,wγ)∩Cc(R), where Cc(R) has been equipped with the supremum norm.
It thus is enough to estimate
[TABLE]
To this end, let f∈Cc∞(R)⊂S(R) and put g:=(1−Δ)θ/2f∈S(R). Then, letting Gθ∈L1(R) be the kernel Lemma 3.1, we find
To prove (2) consider the case that f=0 on (0,δ). Let ϕ∈C∞(R) be such that ∫ϕ(x)dx=1 and ϕ is supported on (−2,−1) and put ϕn(x):=nϕ(nx).
By Lemma 3.6, ∥ϕn∗f∥Hs,p(R,wγ;X)≲p,γ∥f∥Hs,p(R,wγ;X) with ϕn∗f→f in Hs,p(R,wγ;X).
Clearly, ϕn∗f∈C∞(R;X) and by the support conditions one sees that ϕn∗f(0)=0 for all n>2δ−1. Therefore, trk(ϕn∗f)=0 and the result follows by letting n→∞ and using the continuity of trk.
To prove (3) choose ϕ0,…,ϕk∈Cc∞(R) such that ϕj(n)(0)=δjn for all 0≤j≤k and 0≤n≤k and let extk(xj)j=1k=∑j=0kϕjxj. This clearly satisfies the required properties.
∎
We can now give a characterization of H0s,p(R,wγ;X) in terms of traces.
For it will be convenient to say that the statement trkf=0 for k≤−1 is empty.
Proposition 6.4**.**
Let X be a Banach space, p∈(1,∞) and γ∈(−1,p−1). Let s∈R be such that k+p1+γ<s<k+1+p1+γ with k∈Z,k≥−1. Then
[TABLE]
Note that trkf is well defined by Proposition 6.3.
Proof.
Clearly, trkf=0 for every f∈Cc∞(R∖{0};X). By continuity this extends to every f∈H0s,p(R,wγ;X) (see Proposition 6.3) and hence “⊆” follows. To prove the converse, let f∈Hs,p(R,wγ;X) be such that trkf=0.
By Lemma 3.4 we can find {gn}n∈N⊂Cc∞(R)⊗X such that
gn→f in Hs,p(R,wγ;X) as n→∞.
Let extk be as constructed in the proof of Proposition 6.3 and put hn:=gn−extk(gn(j)(0))j=0k for each n∈N.
Then hn∈{h∈Cc∞(R):trkh=0}⊗X and, by Proposition 6.3, hn→f−extk(0)j=0k=f in Hs,p(R,wγ;X) as n→∞.
It remains to show that we can approximate a function h∈Cc∞(R) satisfying trkh=0
by a function in Cc∞(R∖{0}) with respect to the norm of Hs,p(R,wγ). Writing h=1R+h+1R−h=:h0+h1, it follows from Proposition 6.2 that h0,h1∈Hs,p(R,wγ;X) and hence it suffices to approximate each of the terms h0 and h1. Fix ϕ∈Cc∞(R) with ∫Rϕdx=1 and suppϕ⊆[1,∞) and define ϕn:=nϕ(n⋅) for each n∈N. Then ϕn∗h0∈Cc∞(R∖{0}) with ϕn∗h0→h0 in Hs,p(R,wγ) as n→∞ by Lemma 3.6.
A similar argument can be used for h1.
∎
We can now prove the main result of this section:
Theorem 6.5**.**
Let X be a UMD space and γ∈(−1,p−1). Let θ∈(0,1) and s0,s1>−1+pγ+1. Let s=s0(1−θ)+s1θ.
If s0,s1,s∈/N0+pγ+1, then
[TABLE]
Proof.
Assume s0,s1,s∈/N0+pγ+1 and let Eprodσ,p:=HR+σ,p(R,wγ;X)×HR−σ,p(R,wγ;X), σ∈R, for shorthand notation.
Let σ>−1+pγ+1 with σ∈/N0+pγ+1.
By Proposition 6.3trk vanishes on HR±σ,p(R,wγ;X) for integers k∈[0,σ−pγ+1).
Thus, in view of Proposition 6.4, the map
[TABLE]
is a well-defined contraction.
That the map
[TABLE]
is well-defined and continuous follows from Propositions 6.2 and 6.4.
Since R−1=S, the result follows from Proposition 5.7.
∎
6.2. Results on the positive half line
Let γ∈(−1,p−1) and s∈R. Assume k∈N0 satisfies k+p1+γ<s.
By Proposition 6.3, if f~1,f~2∈Hs,p(R,wγ;X) satisfy f~1∣R+=f~2∣R+, then trkf~1=trkf~2.
Therefore, trk:Hs,p(R,wγ;X)→Xk+1 gives rise to a well-defined bounded linear operator trk,+:Hs,p(R+,wγ;X)→Xk+1 given by trk,+f=trkf~ whenever f~∣R+=f.
After reducing to the scalar-valued case, Proposition 5.6 shows that
[TABLE]
in the case X=C we simply pick the least integer m≥∣s∣ and observe that trk,+=trk∘E+m.
Let H0s,p(R+,wγ;X) denote the closure of Cc∞((0,∞);X) in Hs,p(R+,wγ;X).
Proposition 6.6**.**
Let X be a Banach space, p∈(1,∞), γ∈(−1,p−1) and s∈R.
Assume k∈N0 satisfies k+p1+γ<s<k+1+p1+γ.
Then
[TABLE]
Proof.
Clearly, ⊆ holds.
To prove the converse let f∈Hs,p(R+,wγ;X) be such that trk,+f=0.
Pick f~∈Hs,p(R,wγ;X) with f~∣R+=f.
Then trkf~=trk,+f=0. By Proposition 6.4 we thus get f~=limn→∞f~n in Hs,p(R,wγ;X) for some sequence (f~n)n∈N from Cc∞(R∖{0};X). Now fn:=f~n∣R+∈Cc∞((0,∞);X) with fn→f in Hs,p(R+,wγ;X) as n→∞.
∎
Theorem 6.7**.**
Let X be a UMD space, p∈(1,∞) and γ∈(−1,p−1). Let θ∈(0,1) and s0,s1>−1+pγ+1. Let s=s0(1−θ)+s1θ.
If s0,s1,s∈/N0+pγ+1, then
[TABLE]
Proof.
Let m be the least integer such that m≥max{∣s0∣,∣s1∣}.
For each σ>−1+pγ+1 with ∣σ∣≤m and σ∈/N0+pγ+1,
[TABLE]
is a well-defined bounded linear operator thanks to Propositions 6.4 and 6.6.
For each σ∈R, let R:H0σ,p(R,wγ;X)→H0σ,p(R+,wγ;X) denote the restriction operator.
Using Theorem 6.5, the proof can now be completed as in Proposition 5.7 (2).
∎
6.3. Fractional domain spaces
For p∈(1,∞) and γ∈(−1,p−1) let
[TABLE]
If X is a UMD space, then it follows from Propositions 5.5, 6.6 and (6.4) that
[TABLE]
Let us now briefly recall the H∞-calculus for sectorial operators, for which there are several conventions in the literature.
For a survey and an extensive treatment of the subject we refer the reader to [47] and [18, 21, 25], respectively.
For each θ∈(0,π) we define the sector
[TABLE]
A closed densely defined linear operator (A,D(A)) on X
is said to be sectorial of typeσ∈(0,π) if it is injective and has dense range, Σπ−σ⊂ρ(−A), and for all σ′∈(σ,π)
[TABLE]
The infimum of all σ∈(0,π) such that A is sectorial of type σ is called the sectoriality angle of A and is denoted by ϕA.
Let H∞(Σθ) denote the Banach space of all bounded analytic functions f:Σθ→C, endowed with the supremum norm. Let H0∞(Σθ) denote its linear subspace of all f for which there exists ϵ>0 and C≥0 such that
[TABLE]
If A is sectorial of type σ0∈(0,π), then for all σ∈(σ0,π)
and f∈H0∞(Σσ) we define the bounded linear operator f(A) by
[TABLE]
A sectorial operator A of type σ0∈(0,π) is said to have a bounded H∞(Σσ)-calculus for σ∈(σ0,π) if there exists a C∈[0,∞) such that
[TABLE]
In this case the mapping f↦f(A) extends to a bounded algebra homomorphism from H∞(Σσ) to B(X) of norm ≤C.
The H∞-angle of A is defined as the infimum of all σ for which A has a bounded H∞(Σσ)-calculus and is denoted by ϕA∞.
Below we will make use of the following fact.
Let A be an operator on a reflexive Banach space X. If A is a sectorial operator having a bounded H∞-calculus, then so is A∗ with ϕA∞=ϕA∗∞.
Theorem 6.8**.**
Let X be a UMD space, p∈(1,∞) and γ∈(−1,p−1).
(1)
The realization of ∂t on Lp(R+,wγ;X) with domain W01,p(R+,wγ;X) has a bounded H∞-calculus of angle π/2 with D(∂ts)=H0s,p(R+,wγ;X) for every s>0 with s∈/p1+γ+N0.
2. (2)
The realization of −∂t on Lp(R+,wγ;X) with domain W1,p(R+,wγ;X) has a bounded H∞-calculus of angle π/2 with D((−∂t)s)=Hs,p(R+,wγ;X) for every s>0.
For γ∈[0,p−1) the case dtd follows from [39, Theorem 4.5]. For γ∈[0,p−1) the case −dtd follows from [31, Theorem 2.7]. Below we present a proof that works for all γ∈(−1,p−1), in which (1) is derived from (2) by a simple duality argument.
Proof.
Let us first establish the assertions regarding the H∞-calculus.
We start with (2), from which we will derive (1) by duality.
For (2) we denote by A the realization of −∂t on Lp(R+,wγ;X) with domain W1,p(R+,wγ;X) and by A~ the realization of −∂t on Lp(R,wγ;X) with domain W1,p(R,wγ;X). As in [25, Example 10.2], using Proposition 2.3, one can show that A~ has a bounded H∞-calculus of angle π/2.
So it is enough to show that C+⊂ρ(−A) with
[TABLE]
where E∈B(Lp(R+,wγ;X),Lp(R,wγ;X)) is the extension by zero operator, and R denotes the operator of restriction from R to R+.
For each λ∈C+, S(λ) defines a linear operator from Lp(R+,wγ;X) to W1,p(R+,wγ;X) with the property that (λ+A)S(λ)=I. So, fixing λ∈C+, we only need to show that ker(λ+A)={0}. To this end, let u∈W1,p(R+,wγ;X) satisfy (λ−∂t)u=0.
By basic distribution theory (cf. [10, Theorem 9.4]) we find that u is a classical solution in the sense that u∈C∞(R+;X) with u′=λu, implying that u=cexp(λ⋅) for some c∈X.
Since exp(λ⋅)∈/Lp(R+,wγ), it follows that u=0.
For (1) we denote by A the realization of ∂t on Lp(R+,wγ;X) with domain W01,p(R+,wγ;X) and by B the realization of −∂t on Lp′(R+,wγ′;X∗) with domain W1,p′(R+,wγ′;X∗).
Recall that [Lp(R+,wγ;X)]∗=Lp′(R+,wγ′;X∗) with respect to the natural pairing (see [36, Proposition 3.5]), X being reflexive as a UMD space (see [20, Theorem 4.3.3]).
Integration by parts (see Lemma 6.9 below) yields A⊂B∗.
By (2) (and the fact that duals of UMD spaces are again UMD) it is enough to establish the reverse.
By [11, Exercise 1.21(4)], for the latter it suffices that λ+A is surjective and λ+B∗ is injective for some λ∈C. To this end, let us establish this for some fixed λ∈C+. Then λ∈ρ(−B)=ρ(−B∗) by (2); in particular, λ+B∗ is injective.
As in (2) we can find a linear operator S(λ):Lp(R+,wγ;X)→W1,p(R+,wγ;X) such that
(λ+A)S(λ)=I. Then the operator T(λ):Lp(R+,wγ;X)→W01,p(R+,wγ;X) given by
[TABLE]
satisfies (λ+A)T(λ)=I, which shows that λ+A is surjective.
Finally we will identify the fractional domain spaces. From the definitions it follows that D(∂tk)=W0k,p(R+,wγ;X) and D((−∂t)k)=Wk,p(R+,wγ;X) as sets for every k∈N. Moreover, it follows from Lemma 5.8 and Young’s inequality for products that there is also an equivalence of norms.
The assertions concerning the fractional domain spaces subsequently follow from [18, Theorem 6.6.9], Proposition 5.5 and Theorem 6.7.
∎
Lemma 6.9** (Integration by parts).**
Let X be a Banach space, p∈(1,∞) and w∈Ap. For all u∈W1,p(R+,w;X) and v∈W1,p′(R+,w′;X∗), where w′=w−p−11 is the p-dual weight of w, there holds the integration by parts identity
[TABLE]
Proof.
By the remark preceding this lemma and Lemma 3.5, Cc∞(R+)⊗X is dense in W1,p(R+,w;X) and Cc∞(R+)⊗X∗ is dense in W1,p′(R+,w′;X∗). The desired result thus follows from integration by parts for functions from Cc∞(R+).
∎
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