This paper presents new fractal-based examples demonstrating the Lavrentiev gap in variational problems with variable exponents, challenging previous assumptions about the role of the dimensional threshold.
Contribution
It introduces fractal constructions to generate Lavrentiev gaps, showing the threshold is not essential, and extends the analysis to various settings including variable exponents and weighted energies.
Findings
01
Fractal methods produce new Lavrentiev gap examples.
02
The dimensional threshold is not necessary for the gap.
03
Smooth functions are not dense in these new examples.
Abstract
Zhikov showed 1986 with his famous checkerboard example that functionals with variable exponents can have a Lavrentiev gap. For this example it was crucial that the exponent had a saddle point whose value was exactly the dimension. In 1997 he extended this example to the setting of the double phase potential. Again it was important that the exponents crosses the dimensional threshold. Therefore, it was conjectured that the dimensional threshold plays an important role for the Lavrentiev gap. We show that this is not the case. Using fractals we present new examples for the Lavrentiev gap and non-density of smooth functions. We apply our method to the setting of variable exponents, the double phase potential and weighted p-energy.
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Full text
New Examples on Lavrentiev Gap Using Fractals
Anna Kh. Balci
,
Lars Diening
Anna Kh. Balci/Lars Diening, University Bielefeld, Universitätsstrasse 25, 33615
Bielefeld, Germany.
Zhikov showed 1986 with his famous checkerboard example that
functionals with variable exponents can have a Lavrentiev gap. For
this example it was crucial that the exponent had a saddle point
whose value was exactly the dimension. In 1997 he extended this
example to the setting of the double phase potential. Again it was
important that the exponents crosses the dimensional threshold.
Therefore, it was conjectured that the dimensional threshold plays
an important role for the Lavrentiev gap. We show that this is not
the case. Using fractals we present new examples for the Lavrentiev
gap and non-density of smooth functions. We apply our method to the
setting of variable exponents, the double phase potential and
weighted p-energy.
This research was supported by the Russian Science Foundation
under grant 19-71-30004 and the German Research
Foundation (DFG) through the CRC 1283.
1. Introduction
The Lavrentiev gap is a phenomenon that may occur in the study of
variational problems. In particular, the minimum of the integral
functional G taken over smooth functions may differ from
the one taken over the associated energy space.
The first example for Lavrentiev gap was constructed by Lavrentiev in
[14]. A simpler one was provided by Maniá in [15], who considered the functional
[TABLE]
subject to the boundary condition w(0)=0 and w(1)=1. Now,
Maniá showed that there exists τ>0 such that
G(w)≥τ for all w∈C1([0,1]) with w(0)=0
and w(1)=1. However, the function x31∈W1,1((0,1))
has strictly smaller energy, namely G(x31)=0. This gap between zero and τ is the so called
Lavrentiev gap.
In the example of Maniá the integrand
f(x,w,ξ):=(x−w3)2∣ξ∣2 depends on x, w and
ξ. If the integrand only depends on x and ξ, then the
Lavrentiev gap does not appear in the case of one-dimensional
problems, see [14].
The corresponding question for two and higher dimensional problems
with integrands of the form f(x,∇w(x)) remained open for a
very long time.
1.1. Zhikov’s Famous Checkerboard Example – Variable Exponents
In 1986 Zhikov presented his famous two-dimensional checkerboard
example with a Lavrentiev gap, see [19]. In particular, he
considered the functional
where 1<p1<2<p2 and b∈Lp′(⋅)(Ω) with
p′(x)1+p(x)1=1. At this Lp(⋅)(Ω) denotes
the space of Lebesgue space with variable exponent p. The
natural energy space for this functional is W01,p(⋅)(Ω), the
space of functions w∈W01,1(Ω) with
∇w∈Lp(⋅)(Ω). See
Subsections 3.1
and 4.1 for a precise definition of all
function spaces. Now, Zhikov constructed a special
vector field b∈Lp′(⋅)(Ω) such that the infimum
of G taken over W01,p(⋅)(Ω) is strictly smaller
than the one taken over the smooth functions C0∞(Ω). If
we denote by H01,p(⋅)(Ω) the closure of C0∞(Ω)
in W1,p(⋅)(Ω), then we can summarize his result as
[TABLE]
The important feature of this example is that the exponent p has a
saddle point, where it crosses the dimensional threshold, i.e.
p1<2<p2. Moreover, the vector field b
satisfies divb=0 in the sense of distributions, so
∫Ωb⋅∇wdx=0 for w∈C0∞(Ω).
However, for a suitable cut-off
function η∈C0∞(Ω), we have
∫Ωb⋅∇(ηu)dx=−1 (see
Proposition 22 and 23). Thus, b doesn’t
see the gradients of C0∞(Ω)-functions but it sees the
one of ηu∈W01,φ(⋅)(Ω). Therefore, the
vector field b is also called separating vector field. Another useful
feature is that ∣b∣⋅∣∇u∣=0 almost everywhere.
The question of the Lavrentiev gap is closely related to the density
of smooth functions, i.e. if
W01,p(⋅)(Ω)=H01,p(⋅)(Ω) and
W1,p(⋅)(Ω)=H1,p(⋅)(Ω). Using his checkerboard
exponent Zhikov showed that the function (see Figure 1)
[TABLE]
defined in polar coordinates x=(rcosθ,rsinθ) satisfies
u∈W1,p(⋅)(Ω)∖H1,p(⋅)(Ω).
The vector field b∈Lp′(⋅)(Ω) is in Zhikov’s example defined as
b(x):=∇⊥(u(x⊥)) with x⊥=(−x2,x1) and
∇⊥=(−∂2,∂1), see
[22, Section 3].
Now, u∈/W1,p2(Ω), since p2>2=d and
u jumps at the point [math]. But, since u changes its value in the
area of the exponent p1<2, we still get
u∈W1,p(⋅)(Ω).
However, u cannot be approximated by smooth functions un. Indeed,
it follows from un∈W1,p2(Q1)∩W1,p2(Q3) and the
continuity of un at [math] that the un are uniformly Hölder
continuous on Q1∪Q3 with exponent
α:=1−p22>0 uniformly in n, but the limit u is
not even continuous.
It is possible to generalize this example to higher dimensions, i.e.
Ω=(−1,1)d with d≥2. Again the variable
exponent p has a saddle point at zero. It takes the value p2>d on
the double
cone Ω∩{x=(x′,xd):∣xd∣≥∣x′∣} and
p1<d on its complement. The crucial point is again
that W1,p2(Ω)↪C0,α(Ω)
for α=1−p2d. So the exponent has a saddle point,
where it just crosses the dimension d.
Up to now no other examples of
H1,p(⋅)(Ω)=W1,p(⋅)(Ω) with variable exponents
were known. This led people to the question if the dimension plays a
critical role, i.e. that it is important that at the saddle point the
variable exponent p crosses the threshold d. This question has been
repeatedly raised by Zhikov and also by
Hästö [6].
The saddle point setup is the simplest geometry for the Lavrentiev gap
to appear. It has been shown by Zhikov [19] that if p(⋅)
takes only two values separated by a smooth surface,
then H1,p(⋅)(Ω)=W1,p(⋅)(Ω). Even more, if we take a piecewise constant
exponent which takes three constant values in three sectors of the
plane separated by rays emanating from the origin, then
also H1,p(⋅)=W1,p(⋅). This is a special case of the montonicity
condition on cones by Edmunds and Rakosnik [7] that
ensures H1,p(⋅)(Ω)=W1,p(⋅)(Ω).
Another situation for H1,p(⋅)(Ω)=W1,p(⋅)(Ω) is,
when p has certain regularity. In 1995 Zhikov [22] found
the celebrated local log-Hölder condition
[TABLE]
This condition allows to use mollification to prove density of smooth
functions [22], [4], [5, Section
4.6]. The log-Hölder continuity is also important for
many other properties like boundedness of the maximal operator, the
Riesz potential, singular integral operators and sharp Sobolev
embeddings. For more details we refer to the
books [5, 3, 12]. For the density of
smooth functions it is possible to weaken the modulus of continuity
slightly by an extra double log factor, see [21].
In Zhikov’s original example the exponent p(⋅) jumped at the
saddle point. However, it is possible to modify the exponent to a
uniformly continuous one (not log-Hölder continuous). Again the
exponent has a saddle point, where it crosses the dimensional
threshold. Such examples have been obtained independently by
Zhikov [22] and Hästö [11].
Zhikov also showed with his counter example that the notion of
p(⋅)-harmonic functions becomes ambiguous. In particular, minimizers
of
[TABLE]
for given nice boundary may differ depending if we minimize in
H1,p(⋅)(Ω) or in W1,p(⋅)(Ω).
One of the goals of this paper is to provide new examples of variable
exponents, such that the Lavrentiev gap occurs, but which do not need
to cross the dimensional threshold, see
Subsection 4.1. We also show the non-density
of smooth functions, i.e. H1,p(⋅)(Ω)=W1,p(⋅)(Ω)
and the ambiguity of p(⋅)-harmonicity.
1.2. Double Phase Potential
The famous checkerboard example became the guiding principle for other
models. In 1995 Zhikov [22, Example 3.1] considered the double phase potential
[TABLE]
where 1<p<q<∞ and a∈C0,α(Ω)
is a non-negative weight. He constructed with a similar checkerboard
setup a weight a∈C0,α(Ω) with
α=1, Ω=(−1,1)2 and p<2<2+α=3<q such that
the Lavrentiev gap occurs. On the quadrants Q1 and Q3 he
chose a(x)=∣x∣x1x2 and on the quadrants Q2
and Q4 he chose a(x)=0. The exponents take the same values as in
Figure 1 with p1=p and p2=q.
Again he showed that there exists a
functional G(w)=F(w)+∫Ωb⋅∇wdx such that
[TABLE]
This example was generalized by Esposito, Leonetti and Mingione
in [8] to the case of higher dimensions and less
regular weights, i.e. α∈(0,1]. In particular
for Ω=(−1,1)d, they constructed a
weight a∈C0,α(Ω) and exponents
1<p<d<d+α<q such that the Lavrentiev gap occurs. For
this they changed a
to a(x)=∣x∣αmax{∣x∣2xd2−∣xˉ∣2,0} with
x=(xˉ,xd). In both examples by Zhikov and
Esposito-Leonetti-Mingione the two exponents p and q cross the
dimensional threshold d. So again, there was the question, if this
threshold is important for the Lavrentiev gap.
This phenomenon for the double phase potential can also be seen as a
lack of higher regularity, see Marcellini [16] for the first
example in this direction. In fact, local minimizers of F
need not be W1,q-functions unless a, p and q satisfy
certain assumptions. In fact, if pq≤1+dα
and a∈C0,α, then minimizers of F are
automatically in W1,q, see [2]. Moreover, bounded
minimizers of F are automatically W1,q
if a∈C0,α and q≤p+α,
see [1]. If the minimizer is from C0,γ, then
the requirement can be relaxed to q≤p+1−γα
[1, Theorem 1.4]. The example of
Esposito-Leonetti-Mingione shows that in some sense these estimates
are sharp. However, they are sharp only for p=d−ε
with ε>0 small. In this paper we will provide new examples
for the Lavrentiev gap that get rid of this
condition p=d−ε. We will present new examples that show
that the conditions q≤p+α and
q≤p+1−γα are sharp for a much wider range
of p and q, see Subsection 4.2. In
particular, we present examples without the dimensional threshold.
The question of Lavrentiev gap can also be viewed from the point of
function spaces. In fact, the energy F defines a
generalized Sobolev-Orlicz space W1,φ(⋅)(Ω) and its
counterpart W01,φ(⋅)(Ω) with zero boundary values, see
Subsection 3.1 for the precise definition of
the spaces. Then the above Lavrentiev gap can be also written as
[TABLE]
where H01,φ(⋅)(Ω) is the closure of C0∞(Ω)
functions in W1,φ(⋅)(Ω). Hence, the question of the
Lavrentiev cap is closely related to the density of smooth functions,
i.e. if H01,φ(⋅)(Ω)=W01,φ(⋅)(Ω) and
H1,φ(⋅)(Ω)=W1,φ(⋅)(Ω).
We present fractal examples without the dimensional threshold that
support the Lavrentiev gap, the non-density of smooth functions and
the ambiguity of the related harmonicity.
1.3. Weighted p-Energy
Zhikov also considered another example, namely the one of weighted
Sobolev spaces. In particular, he considered the energy
[TABLE]
Again, he used a checkerboard setup to construct weights a,
resp. ω that provide for p=2 a Lavrentiev gap and non-density
of smooth functions, see [22, Example 3.3]. His weight is
unbounded but it is bounded from above and below by two Muckenhoupt
weights from A2. In [20, Section 5.3] he presented another
more complicated example with a bounded weight, see
Remark 37.
Again, we present fractal examples without the dimensional threshold
that support the Lavrentiev gap, the non-density of smooth functions
and the ambiguity of the related harmonicity.
If a itself is a Muckenhoupt weight, then it is well known that
smooth functions are dense, so
W1,φ(⋅)(Ω)=H1,φ(⋅)(Ω). For other results on the
density in the context of weighted Sobolev spaces with even variable
exponents, we refer to [17, 18].
1.4. Structure of the Article
The structure of the article is as follows. In
Section 2 we will use fractals to construct the
functions u and b that we need later in our applications. We start
with a modified version of the checker board example by Zhikov, which
works in all dimensions. Then we introduce the necessary fractals of
Cantor type to construct function u and the vector field b without the problem of
the dimensional threshold.
In Section 3 we show how u and b can be used
to deduce the Lavrentiev gap, the non-density of smooth functions and
ambiguity of the related harmonicity. In this section we also introduce the
necessary function spaces.
In Section 4 we apply out technique to the model
of variable exponents, the double phase potential and weighted
p-energy. From the point of applications these are the main results
of our paper.
2. Construction of Fractal Examples
In this section we will use fractals to construct the functions u
and b, which are necessary to study later in
Section 3 the Lavrentiev gap and the other
phenomena. The construction of these functions is independent of the
models that we consider in
Section 4.
Let us clarify our notation. By Brm(x) we denote the ball
of Rm with radius r and center x. We denote
by \mathbbm1A the indicator function of the
set A. By Lp(Ω) and W1,p(Ω) we denote the usual
Lebesgue and Sobolev spaces. Moreover, let W01,p(Ω) be the
Sobolev space with zero boundary values. By Lloc1(Ω) we
denote the space of locally integrable functions (integrable on
compact subsets) with Wloc1,1(Ω) defined analogously. We
use c>0 for a generic constants whose value may change from line to
line but does not depend on critical parameters. We also abbreviate
f≲g for f≤cg.
2.1. One Building Block
We begin with a multidimensional, revised version of the Zhikov
example. We will use it later as the building block for fractal
examples.
Definition 1** (Zhikov’s example; revised).**
For d≥2 define ud, Ad and bd on Rd by
[TABLE]
where σd−1 is the surface area of the d−1-dimensional
sphere and θ∈C0∞((0,∞)) is such that
\mathbbm1(21,∞)≤θ≤\mathbbm1(41,∞), ∥θ′∥∞≤6.
The matrix divergence is taken rowwise, i.e for matrix A={Aij} we define (divA)i=∂jAij.
In Figure 2 it is shown how our revised
version of Zhikov’s checkerboard example looks for d=2. The picture
shows the function u2, the (2,1)-component of A2 and a
possible exponent p. The picture should be compared to the one of
Figure 1. There are two main differences. First, our
version is rotated by 45∘ counterclockwise. Second, there is an
additional area, where u2=0. This fact will be very useful
later. Note that on the shaded region of u2, resp. A2, we have
∣x1∣≂∣x2∣≂∣x∣, which allows us later a
freedom in the choice of variable on the shaded region.
Another difference to the example of Zhikov is the improved regularity
away from the singularity at zero.
Proposition 2**.**
There holds
(a)
ud∈L∞(Rd)∩Wloc1,1(Rd)∩C∞(Rd∖{0}),
2. (b)
Ad∈Wloc1,1(Rd)∩C∞(Rd∖{0}),
3. (c)
bd∈Lloc1(Rd)∩C∞(Rd∖{0}).
Moreover, the following estimates hold
[TABLE]
In particular, ∣∇ud∣⋅∣bd∣=0.
Proof.
It is easy to see that
ud,Ad,bd∈C∞(Rd∖{0}) and
ud∈L∞(Rd). Moreover, ud and Ad have the ACL
property (absolutely continuous on almost every line parallel to the
axis). Now, the estimates for ∣∇ud∣, ∣bd∣
are also straight forward. They imply immediately
that ∇ud,bd∈Lloc1(Rd). This proves
the claim.
∎
Note that
[TABLE]
since Ad is skew-symmetric. Moreover, for all ξ∈C0∞(Rd) we have
[TABLE]
again, since Ad is skew-symmetric. Thus,
[TABLE]
This is a crucial property of bd, since it implies that bd is
orthogonal to the gradient of smooth functions. This will allow us
later to separate ud from the smooth functions. Therefore, we
call bd also separating vector field.
It follows from (2) and the regularity of bd that
[TABLE]
Another important feature of ud and bd is the following
proposition on the boundary integral that we would obtain it if we were
allowed to use partial integration
on ∫Ωbd⋅∇uddx (we are not,
since bd∈/W1,1(Ω)).
Proposition 3**.**
Let Ω=(−1,1)d with d≥2. Then
[TABLE]
For a better understanding we show in Figure 3 the
values for b2u2 that we need in
Proposition 3.
Before we get to the proof we need the following lemma.
Lemma 4**.**
There holds
(xˉ↦bd(xˉ,1))∈C0∞((−1,1)d−1) and
[TABLE]
Proof.
Let B:=Bdd−1(0)⊂Rd−1. Then
supp(bd(⋅,1))⊂B and
[TABLE]
Let use define g:Rd−1→Rd−1 as
[TABLE]
Then by the definition of Ad we get
[TABLE]
Thus, by the theorem of Gauß
[TABLE]
using that σd−1 is the surface area of the
d−1-dimensional sphere. This proves the claim.
∎
Note that bd=0 on ∂Ω except for the
sets {xd=±1}∩∂Ω. On these sets ud takes the
values ±21 and ν=±ed. Moreover, bd⋅ed is even
with respect to xd. Thus,
In the Zhikov’s example the contact set S consists just of
one point, the origin, which has dimension zero. For our new examples
we want to use contact sets of higher, fractal dimension. For this
reason we start with the definition of a few fractal Cantor sets that
we need later.
We begin with the one dimensional generalized Cantor
set Cλ with λ∈(0,21), which is also
known as the (1-2λ)-middle Cantor set. We start with the
interval Cλ,0:=(−21,21). Then we
define Cλ,k+1 inductively by removing the
middle 1−2λ parts from Cλ,k. In particular, we
define Cλ:=∩k≥1Cλ,k. The
corresponding Cantor measure μλ (also Cantor distribution)
is then defined as the weak limit of the
measures μλ,k:=(2λ)−k\mathbbm1Cλ,kdx. The factor (2λ)−k is
chosen such
that μλ,k([−21,21])=1=μ([−21,21]). Thus, μλ(R)=1 and
suppμλ=Cλ. The fractal dimension
of Cλ is
dim(Cλ)=log(2)/log(1/λ)∈(0,1),
i.e. λ=2−D.
We will also need the m-dimensional Cantor sets Cλm and
its distribution μλm, which are just the Cartesian
products of Cλ and μλ. Its fractal dimension
is dimCλm=mdimCλ=mlog(2)/log(1/λ)∈(0,m). Note that
Cλm=∩k≥1Cλ,km.
In the construction of our fractal examples we need a
smooth approximation of the indicator function
\mathbbm1{d(xˉ,Cλm)≤3∣x^∣}, where
x=(xˉ,x^)∈Rm×Rd−m. This is the
purpose of the following lemma.
Lemma 5**.**
Let λ∈(0,21), 1≤m≤d and
let S:=Cλm×Rd−m. We use the
notation x=(xˉ,x^)∈Rm×Rd−m. Let
41≤τ1<τ2≤4 and τ2−τ1≥41. Then there exists ρ∈C∞(Rd∖S)
such that
In particular, ρ=1
on {d(xˉ,Cλm)≤τ1∣x^∣} and
ρ=0 on {τ2∣x^∣≤d(xˉ,Cλm)}.
Proof.
Let τ:=2τ2−τ1. The function
\mathbbm1{τ∣x^∣≥d(xˉ,Cλm)}
would satisfy (a) but not the smoothness
requirement. Therefore, we need to mollify this function depending
on the ∣x^∣-value. For this let {ψt} denote a
standard mollifier, i.e. supp(ψ1)=B1d(0),
ψ1≥0, ∫ψ1dx=1, ψ1∈C0∞(B1d(0)) and
ψt(x)=t−dψ(x/t).
[TABLE]
The factor 1001 in the scaling of the mollifier is chosen
so small such that the smeared version of the jump set
{τ∣x^∣=d(xˉ,Cλm)} stays inside
{τ1∣x^∣≤d(xˉ,Cλm)≤τ2∣x^∣}. This proves (a). Now, the standard estimate
implies (b). It is obvious
that ρ∈C∞(Rd∖(Rm×{0}d−m)). Moreover, since ρ=0 on {τ2∣x^∣<d(xˉ,Cλm)} it follows that u is also C∞ at (Rm×{0}d−m)∖S. This proves
that u∈C∞(Rd∖S).
∎
The following two lemmas provides further technical estimates that are used
later to determine the integrability of our fractal examples.
Lemma 6**.**
Let λ∈(0,21), 1≤m≤d and
D:=dim(Cλm)=−mlog(2)/log(λ). We
use the notation x=(xˉ,x^)∈Rm×Rd−m.
Then we have the following properties:
(a)
For every
ball Brm(xˉ) there
holds μλm(Brm(xˉ))≲\mathbbm1{d(xˉ,Cλm)≤r}rD.
2. (b)
For all r>0 there holds
\mathcal{L}^{m}\big{(}{\{{\bar{x}:d(\bar{x},{\mathfrak{C}}^{m}_{\lambda})\leq r}\}}\big{)}\lesssim r^{m-{\mathfrak{D}}}.
3. (c)
For all τ∈(0,4] there
holds
[TABLE]
Proof.
Choose k∈Z such that
λk+1<r<λk. Let A1,…,A2mk
denote the connected components of Cλ,km.
Let us prove (a). If
d(xˉ,Cλm)>r, then
μλm(Brm(xˉ))=0. This explains the indicator
function in (a). Clearly,
[TABLE]
By the construction of Cλ,km the sets Aj are pairwise disjoint translates
of (0,λk)m. So the number of indices l such that the intersection Brm(xˉ)∩Al is nonempty does not exceed 2m. Thus
[TABLE]
using again 2m=λ−D and λk≤rλ−1. This finishes the proof of (a).
Note that integrability exponents βd and
βd−D in Lemma 7 are sharp. In
particular,
∣x^∣−β\mathbbm1{∣xˉ∣≤4∣x^∣}∈/Lβd(Ω) and
∣x^∣−β\mathbbm1{d(xˉ,Cλm)≤4∣x^∣}∈/Lβd−D(Ω) with Ω=(−1,1)d.
2.3. Construction of Fractal Examples
We can now construct our fractal examples, namely the functions u
and b. The contact set S will in our examples be a subset
of Rd−1×{0} or {0}d−1×R. In
particular, we split Rd into Rd−1×R and
write x=(xˉ,xd)∈Rd−1×R.
We will provide some pictures
after the formal definition.
Definition 9** (Fractal Examples).**
Let Ω:=(−1,1)d with d≥2. Let ud,Ad,bd,
be as Definition 1. Let 1<p0<∞. We
define u,A,b on Ω distinguishing three cases:
(a)
(Matching the dimension; Zhikov) p0=d:
Let u:=ud, A:=Ad, b:=bd, S:={0} and D:=dimS=0.
2. (b)
(Sub-dimensional) 1<p0<d:
Let S:=Cλd−1×{0} and
D=dim(S)=log(1/λ)(d−1)log2,
where λ∈(0,21) is chosen such that
p0=d−D. Let ρ∈C∞(Rd∖S)
be such that (using Lemma 5)
(i)
\mathbbm1{d(xˉ,Cλd−1)≤2∣xd∣}≤ρ≤\mathbbm1{d(xˉ,Cλd−1)≤4∣xd∣}.
2. (ii)
Let S:={0}d−1×Cλ and
D=dim(S)=log(1/λ)log2,
where λ∈(0,21) is chosen such that
p0=1−Dd−D. Let ρ∈C∞(Rd∖S) be such that (using
Lemma 5)
(i)
\mathbbm1{d(xd,Cλ)≤2∣xˉ∣}≤ρ≤\mathbbm1{d(xd,Cλ)≤4∣xˉ∣}.
2. (ii)
∣∇ρ∣≲∣xˉ∣−1\mathbbm1{2∣xˉ∣≤d(xd,Cλ)≤4∣xˉ∣}.
We define
[TABLE]
Remark 10**.**
We will use the functions u,b from the
Definition 9 with the exponent p0 later
to construct a variable exponent p:(−1,−1)d→(1,∞)
with saddle point value p0 that provides a Lavrentiev gap,
see Subsection 4.1. This explains that we
use p0 as a parameter to label our fractal examples. Another
reason is that ∇u is in the Marcinkiewicz (weak Lebesgue)
space Lp0,∞ and b∈Lp0′,∞(Ω), see
Corollary 15 and Remark 16.
Let us provide a few pictures for the 2D case to illustrate our
fractal examples from Definition 9. Using
the 31-Cantor set C311 we provide in
Figure 5, resp. Figure 6, the
sub-dimensional, resp. super-dimensional case. The case of matching the dimension
is already considered in Figure 1. The left picture
shows the values of u. The right picture shows the
component A1,2 of the skew-symmetric A. The vertical and
horizontal patterns indicate that the function is almost linear along
those lines.
Remark 11**.**
The use of the skew-symmetric A allows us to avoid the language
of differential forms:
(a)
For d=2 we can rewrite A as
[TABLE]
with v:R2→R. Then
divA=(−∂2v,∂1v)T=∇⊥v. Thus, divdivA=divb=0 becomes the well known
div∇⊥v=0, compare (3) and
Proposition 18.
2. (b)
If d=3 we can rewrite A as
[TABLE]
with v:R3→R3. Then divA=curlv. Thus, divdivA=divb=0 becomes
the well known divcurlv=0. Hence, for d=3 we
could also work with v and curlv instead of A and
divA. Compare also (3) and
Proposition 18.
Remark 12**.**
If we use
Remark 11(b) to
find v with A3=curlv. Then
(x1,x2)↦v(x1,x2,x3) is just a smooth version of the
so called Rankine vortex. It has a central core of
radius 21∣x3∣, where the velocity increases linearly,
surrounded by a free vortex, where the velocity drops off from the
center like r1 with r=∣(x1,x2)∣.
2.4. Properties of the Fractal Examples
Let us derive a few useful properties of u, A and b.
The case p0=d follows from Proposition 2. We
continue with the sub-dimensional case 1<p0<d. It is easy to
see that
u∈C∞(Ω∖S)∩L∞(Ω). Since Ad∈C∞(Rd∖{0})
and supp(μλd−1×δ0)=S, it
follows from the definition by convolution that
A∈C∞(Ω∖S), so also
b∈C∞(Ω∖S). It also follows
that A∈W1,1(Ω) and b∈L1(Ω). The
case p0>d is similar.
∎
We begin with (a). The case p0=d follows directly
from Proposition 2. We continue with the sub-dimensional
case 1<p0<d. It follows from the properties of ρ that
This proves the super-dimensional case and concludes (a).
The estimates in (a) immediately imply that the
support of ∇u and b only overlaps at S, which
is a null set. This proves (b).
∎
The following corollary clarifies the role of p0 in
Definition 9.
Corollary 15**.**
For 1<p0<∞ let u,b be as in
Definition 9. Then
∇u∈Lp0,∞(Ω),
b∈Lp0′,∞(Ω).
Proof.
The proof is an immediate consequence of Lemma 7
in combination with
Proposition 14(a). For this recall
that we have p0=d for matching the dimension, p0=d−D in the
sub-dimensional case and p0=1−Dd−D in the
super-dimensional case. We apply Lemma 7 for
m=d−1 and for m=1 to cover all cases.
∎
Remark 16**.**
The integrability exponents of ∇u and b are sharp. In
particular, ∇u∈/Lp0(Ω) and
b∈/Lp0′(Ω). This can be shown with the help of
Remark 8.
We also need localized version of u, A and b.
Definition 17**.**
For 1<p0<∞ let u,A,b be as is
Definition 9. Let
η∈C0∞(Ω) with
\mathbbm1(−64,64)d≤η≤\mathbbm1(−65,65)d and ∥∇η∥∞≤c. Then we define
[TABLE]
The following proposition shows that b and b∘ are divergence
free in the sense of distributions.
Proposition 18**.**
For all w∈C∞(Ω) we have
[TABLE]
For all w∈C0∞(Ω) we have
[TABLE]
Moreover, divb=divb∘=0 in the
distributional sense and on Ω∖S in the classical
sense.
Proof.
For w∈C∞(Ω) we get by partial integration
[TABLE]
since A is anti-symmetric. For
w∈C0∞(Ω) we also get by partial
integration
[TABLE]
since A is anti-symmetric. It follows that
divb=divb∘=0 in the distributional
sense. Since by Proposition 13 we have
b∈C∞(Ω∖S), it follows that
divb=divb∘=0 on Ω∖S
in the classical sense.
∎
Due to Proposition 18 the functions b and b∘
are called separating vector fields.
The case p0=d is already contained in
Proposition 3.
Let us continue with the sub-dimensional case 1<p0<d. Note
that b=0 on ∂Ω except on the sets {xd=±1}∩∂Ω. On these sets u takes the
values ±21 and ν=±ed. Moreover, bd is even
with respect to xd. Thus,
[TABLE]
using the first part of Lemma 4. By definition of b
we have
Let us continue with the super-dimensional case p0>d. Note
that b=0 on ∂Ω except on the sets {xd=±1}∩∂Ω. On these sets ud takes the
values ±21 and ν=±ed. Moreover, bd⋅ed is even
with respect to xd. Thus,
[TABLE]
By definition
of b we have
[TABLE]
Let g(xˉ):=(ρ(xˉ)−1)edTAd(xˉ,1). Then
g∈C0∞((−1,1)d−1) and
For 1<p0<∞ with the notation of
Definition 17 we have
(a)
supp(u∘),supp(A∘),supp(b∘)⊂[−65,65]d⋐Ω.
2. (b)
u∂,A∂,b∂∈C0∞(Ω∖S).
Proof.
The claim follows immediately from the definition,
S⋐(−64,64)d and
Proposition 13.
∎
3. Important Consequences
Zhikov used the functions u2 and b2 in order to derive the
Lavrentiev gap, H=W and the different notions of p(⋅)-harmonic
functions. We show in this section that also our fractal examples
display these phenomena. We will do this in this section in
quite general form and apply it to specific examples in
Section 4.
3.1. Energy and Generalized Orlicz Spaces
In this section we introduce the necessary function spaces, the so
called generalized Orlicz and Orlicz-Sobolev spaces.
We assume that Ω⊂Rd is a domain of finite
measure111It is no problem to consider infinite domains, but it
is not needed in this context of counter examples.. Later in our
applications we will only use Ω=(−1,1)d.
We say that ϕ:[0,∞)→[0,∞] is an Orlicz
function if ϕ is convex, left-continuous, ϕ(0)=0,
limt→0ϕ(t)=0 and
limt→∞ϕ(t)=∞. The conjugate Orlicz
function ϕ∗ is defined by
[TABLE]
In particular, st≤ϕ(t)+ϕ∗(s).
In the following we assume that
φ:Ω×[0,∞)→[0,∞] is a generalized
Orlicz function, i.e. φ(x,⋅) is an Orlicz function for
every x∈Ω and φ(⋅,t) is measurable for
every t≥0. We define the conjugate function φ∗ pointwise,
i.e. φ∗(x,⋅):=(φ(x,⋅))∗.
We further assume the following additional properties:
(a)
We assume that φ satisfies the Δ2-condition,
i.e. there exists c≥2 such that for
all x∈Ω and all t≥0
[TABLE]
2. (b)
We assume that φ satisfies the ∇2-condition,
i.e. φ∗ satisfies the Δ2-condition. As a consequence,
there exist s>1 and c>0 such that for all x∈Ω,
t≥0 and γ∈[0,1] there holds
[TABLE]
3. (c)
We assume that φ and φ∗ are proper, i.e. for
every t≥0 there holds ∫Ωφ(x,t)dx<∞ and
∫Ωφ∗(x,t)dx<∞.
Let L0(Ω) denote the set of measurable function on Ω
and Lloc1(Ω) denote the space of locally integrable
functions.
We define the generalized Orlicz norm by
[TABLE]
Then generalized Orlicz space Lφ(⋅)(Ω) is defined as the
set of all measurable functions with finite generalized Orlicz norm
[TABLE]
For example the generalized Orlicz function φ(x,t)=tp
generates the usual Lebesgue space Lp(Ω).
The Δ2-condition of φ and φ∗ ensures that our space
is uniformly convex. The condition that φ and φ∗ are proper
ensure that Lφ(⋅)(Ω)↪L1(Ω) and
Lφ∗(⋅)(Ω)↪L1(Ω). Thus Lφ(⋅)(Ω)
and Lφ∗(⋅)(Ω) are Banach spaces.
We define the generalized Orlicz-Sobolev space W1,φ(⋅) as
[TABLE]
with the norm
[TABLE]
In general smooth functions are not dense
in W1,φ(⋅)(Ω). Therefore, we define H1,φ(⋅)(Ω)
as
[TABLE]
See [5] and [10] for further properties of
these spaces.
We also introduce the corresponding spaces with zero boundary values
as
[TABLE]
with same norm as in W1,φ(⋅)(Ω). And the corresponding space of smooth functions is defined as
[TABLE]
The space W01,φ(⋅)(Ω) are exactly those function, which can
be extended by zero to W1,φ(⋅)(Rd) functions.
Let us define our
energy F:W1,φ(⋅)(Ω)→R by
[TABLE]
In the language of function spaces F is a semi-modular
on W1,φ(⋅)(Ω) and a modular on W01,φ(⋅)(Ω).
3.2. H = W and H0= W0
In this section we show how to use the function u and the
vector b from Definition 9 to give examples
for W1,φ(⋅)(Ω)=H1,φ(⋅)(Ω) and
for W01,φ(⋅)(Ω)=H01,φ(⋅)(Ω). In this
section, we need the following assumption:
Assumption 21**.**
Let u,u∘,u∂,b,b∘,b∂ be as in
Section 2, i.e.
Proposition 13, 14, 19
and 20 hold. Let φ be such that
u∈W1,φ(⋅)(Ω) and b∈Lφ∗(⋅)(Ω).
For all w∈W1,φ(⋅)(Ω) we define the continuous functionals
[TABLE]
This is well defined, since
b,b∘,b∂∈Lφ∗(⋅)(Ω).
Proposition 22**.**
For all w∈H1,φ(⋅)(Ω) we have
S∘(w)=0. Moreover, for all w∈H01,φ(⋅)(Ω) we have S(w)=0.
Proof.
Due to Proposition 18 we have
S∘(w)=0 for w∈C∞(Ω) and
S(w)=0 for w∈C0∞(Ω). Now,
the claim follows by density.
∎
Due to Proposition 22 the functionals S
and S∘ are called separating functionals.
Proposition 23**.**
There holds
(a)
S(u)=0, S(u∂)=1 and S(u∘)=−1.
2. (b)
S∂(u)=1,
S∂(u∂)=1 and
S∂(u∘)=0.
3. (c)
S∘(u)=−1, S∘(u∂)=0 and S∘(u∘)=−1.
Proof.
Since ∇u⋅b=0 everywhere, we have S(u)=0.
Since
u∂,v∂∈C0∞(Ω∖S), we can use partial integration to get
[TABLE]
using also Proposition 19. Since
u∂∈C0∞(Ω∖S),
b∘∈C∞(Ω∖S),
suppb∘⋐Ω and divb∘=0 on Ω∖S, we can use
partial integration together to get
Recall that
u∘∈W01,φ(⋅)(Ω)⊂W1,φ(⋅)(Ω). Due
to Proposition 22 we
know that S∘=0 on H1,φ(⋅)(Ω) and therefore
also on
H01,φ(⋅)(Ω). However,
S∘(u∘)=−1 by proposition 23. This proves
u∘∈/H1,φ(⋅)(Ω) and
u∘∈/H01,φ(⋅)(Ω). This proves the claim.
∎
3.3. Lavrentiev Gap
In this section we show how to use the function u and the vector
field b from
Definition 9 for the Lavrentiev gap. In this
section, we need the following assumption:
Assumption 25**.**
Let u,u∘,u∂,b,b∘,b∂ as in
Section 2, i.e.
Proposition 13, 14, 19
and 20 hold. Let φ be such that
u∈W1,φ(⋅)(Ω) and b∈Lφ∗(⋅)(Ω). Also
recall, that φ∗ satisfies the Δ2-condition.
From the Δ2-condition of φ∗, see (7), it follows that
Due to Proposition 22 we have
G=F on H01,φ(⋅)(Ω), which
implies that infG(H01,φ(⋅)(Ω))=0. However,
for t>0 we have
[TABLE]
using S∘(u∘)=−1 by Proposition 23.
Since limt→0tF(tu∘)=0
by (9), the right-hand side becomes negative for
small t>0. Thus infG(W01,φ(⋅)(Ω))<0.
∎
3.4. H-harmonic = W-harmonic
In this section we show that the spaces W1,φ(⋅)(Ω) and
H1,φ(⋅)(Ω) lead to different concepts of φ(⋅)-harmonic functions.
Let us start by introducing spaces with boundary values: for
g∈H1,φ(⋅)(Ω) we define
[TABLE]
For g∈W1,φ(⋅)(Ω) we define
[TABLE]
Since u∂∈W1,φ(⋅)(Ω), we can define
[TABLE]
Formally, it satisfies the Euler-Lagrange equation (in the weak sense)
[TABLE]
where φ′(x,t) is the derivative with respect to t.
However, since also u∂∈H1,φ(⋅)(Ω), we can define
[TABLE]
Then
[TABLE]
If φ(x,t)=21t2, then Δφ(⋅) is just the standard Laplacian.
If φ(x,t)=p1tp, then Δφ(⋅) is the p-Laplacian.
Thus hW and hH are both φ(⋅)-harmonic but hW is
φ(⋅)-harmonic in the sense of W1,φ(⋅) and hH is
φ(⋅)-harmonic with respect to H1,φ(⋅).
Our goal is to provide an example, where these concepts differ. For
this we assume the following:
Assumption 27**.**
Let u,u∘,u∂,b,b∘,b∂ as in
Section 2, i.e.
Proposition 13, , 14, 19
and 20 hold. Let φ be such that
u∈W1,φ(⋅)(Ω) and b∈Lφ∗(⋅)(Ω).
Moreover, assume that there exists s,t>0 such that
[TABLE]
where
[TABLE]
We come to the main result of this subsection.
Theorem 28** (H-harmonic = W-harmonic).**
Under the Assumption 27 there
exists g∈H1,φ(⋅)(Ω) such that the φ(⋅)-harmonic
functions hW in the sense of W1,φ(⋅) and the
φ(⋅)-harmonic function hH in the sense of H1,φ(⋅) with
the same boundary values g differ. In particular, for
[TABLE]
we have hW=hH and F(hW)<F(hH).
Proof.
We define g:=tu∂∈H1,φ(⋅)(Ω), with t>0 to
be chosen later. Now, let
[TABLE]
We have tu=tu∂+tu∘∈Wtu∂1,φ(⋅)(Ω). Thus,
[TABLE]
From the other hand, using Young’s inequality, we get for all s>0 that
[TABLE]
Since ht−tu∂∈H01,φ(⋅)(Ω), we have
S(ht−tu∂)=0 by
Theorem 22. This and
S(u∂)=1 by Proposition 23 imply
for all t,s>0. By Assumption 10 we can
find t,s>0 such that the right hand-side of last inequality is positive. For
these t,s we have F(ht)>F(wt). This
proves the claim for hH:=ht and hW:=wt.
∎
4. Applications
We will now apply our results to the following three models:
[TABLE]
4.1. Variable Exponents
In this section we study the variable exponent model. In particular,
we assume that
[TABLE]
where p:Ω→(1,∞) is a variable exponent. The
corresponding energy is
[TABLE]
We abbreviate W1,p(⋅)(Ω):=W1,φ(⋅)(Ω) and
similarly W01,p(⋅), H1,p(⋅) and H01,p(⋅).
Our main result of the variable exponent model is the following:
Theorem 29**.**
Let Ω=(−1,1)d. Let 1<p−<p+<∞. Then there
exists a variable exponent p:Ω→[p−,p+] such that
(a)
H1,p(⋅)(Ω)=W1,p(⋅)(Ω)* and
H01,p(⋅)(Ω)=W01,p(⋅)(Ω).*
2. (b)
There exists a linear, continuous
functional S∘:W1,p(⋅)(Ω)→R such
that functional G:=F+S∘
has a Lavrentiev gap, i.e.
[TABLE]
3. (c)
The notions of p(⋅)-harmonic functions with respect to
W1,p(⋅) and H1,p(⋅) differ.
Proof.
Choose p0 with p−<p0<p+. Now, let u,b be as in
Definition 9 and S∘ as
in (8).
We begin with the definition of the variable exponent p.
(a)
(Matching the dimension; Zhikov) p0=d: Define
[TABLE]
2. (b)
(Sub-dimensional) 1<p0<d: Define
[TABLE]
3. (c)
(Super-dimensional) p0>d:
Define
[TABLE]
In particular, it follows from Proposition 14 that
Overall, we have constructed u, b, and p such that the
Assumptions 21, 25 and 27
holds. Now, the claim follows from the results of
Theorem 24, 26 and 28 of
Section 3.
∎
The exponent in Theorem 29 was discontinuous at the
singular set S. The following result shows that it is also
possible to construct a uniformly continuous exponent with the same
phenomena. However, this exponent is not log-Hölder continuous,
since this would imply the H1,p(⋅)=W1,p(⋅) by means of
convolution, see [22] and [5, Section 4.6].
Theorem 30**.**
Let Ω=(−1,1)d with d≥2. Let 1<p0<∞. Let
S (the fractal contact set) be as in
Definition 9. Then there exists a
uniformly continuous variable exponent p with saddle points
on S and p=p0 on S and
(a)
H1,p(⋅)(Ω)=W1,p(⋅)(Ω)* and
H01,p(⋅)(Ω)=W01,p(⋅)(Ω).*
2. (b)
There exists a linear, continuous
functional S∘:W1,p(⋅)(Ω)→R such
that functional G:=F+S∘
has a Lavrentiev gap, i.e.
[TABLE]
3. (c)
The notions of p(⋅)-harmonic functions with respect to
W1,p(⋅) and H1,p(⋅) differ.
Proof.
The proof is similar to the one of Theorem 29. So we
only point out the difference. Let u,b be as in
Definition 9 and S∘ as
in (8). We have to show that
∇u∈Lp(⋅)(Ω) and b∈Lp′(⋅)(Ω) and to
verify Assumption 27.
Let σ(t):=(log(e+1/t))κ1 with
0<κ<1. Then for any c1>0 there holds
[TABLE]
(a)
We begin with the case of matching the dimension p0=d.
Let θp∈C0∞((0,∞)) be such that
\mathbbm1(2,∞)≤θp≤\mathbbm1(21,∞) and ∥θp′∥∞≤6 and define
[TABLE]
Then p is uniformly continuous with modulus of
continuity σ. It follows by Proposition 14,
Lemma 6, (14) and p0=d
that
[TABLE]
and
[TABLE]
This proves ∇u∈Lp(⋅)(Ω)
and b∈Lp′(⋅)(Ω).
2. (b)
We continue with the sub-dimensional case 1<p0<d. Let
ρ∈C∞(Rd∖S) be such that (using
Lemma 5)
Then p is uniformly continuous with modulus of
continuity σ. It follows by Proposition 14,
Lemma 6, (14),
p0=1−Dd−D and 1−D=p0−1d−1
that
[TABLE]
and
[TABLE]
This proves ∇u∈Lp(⋅)(Ω)
and b∈Lp′(⋅)(Ω).
We have proved ∇u∈Lp(⋅)(Ω)
and b∈Lp′(⋅)(Ω) for all 1<p0<∞. We are now
going to verify Assumption 27. We restrict ourselves
to the sub-dimensional case, since the other cases are similar.
We will show that
[TABLE]
for suitable large s,t.
Let s,t>1 (to be fixed later). For ε>0 we define
the ε-neighborhood of S by
Since
φ(⋅,∣∇u∣),φ∗(⋅,∣b∣)∈L1(Ω), we can choose ε0>0 small such
that I,III<41 for
all ε∈(0,ε0). Then choose t0,s0 large
(depending on ε0) such that
II,IV<41 for all t≥t0 and
s≥s0. Thus, we obtain
[TABLE]
for all t≥t0 and s≥s0. Now, the choice s:=tp0−1
implies for large t that
Overall, we have constructed u, b, and p such that the
Assumptions 21, 25 and 27
hold. Now, the claim follows from the results from
Theorem 24, 26 and 28 of
Section 3.
∎
Theorem 29 and Theorem 30 show in
particular that the dimensional threshold is not important for the
presence of the Lavrentiev gap and the non-density of smooth
functions.
Remark 31**.**
At this point we also have to mention the work of [13],
since it seemingly contradicts our results. The authors claimed that
H1,p(⋅)(Rd)=W1,p(⋅)(Rd) if p−≥d
[13, Theorem 4.1] or if 2≤p−<d and
p+<d−p−dp− [13, Theorem 4.2]. Our
examples show that both claims are wrong.222The mistake is in
Theorem 3.3 of [13]. On page 203 the mollified
gradient Djωλi has no majorant in Lp(⋅)
independent of the mollification parameter λ.
4.2. Double Phase Potential
In this section we study the double phase model. In particular,
we assume that
[TABLE]
where 1<p<q with a weights a,ω≥0. The corresponding
energy is
[TABLE]
Let us denote by Ck the space of k-times differentiable
functions. Moreover, denote by Ck+β for β∈(0,1) and
k∈N0 the space of functions from Ck whose k-th
derivatives are β-Hölder continuous.
Theorem 32**.**
Let Ω=(−1,1)d with d≥2. Let p>1 and
q>p+αmax{1,d−1p−1}
with α>0. Then there
exists a∈Cα(Ω) such that
(a)
H1,φ(⋅)(Ω)=W1,φ(⋅)(Ω)* and
H01,φ(⋅)(Ω)=W01,φ(⋅)(Ω).*
2. (b)
There exists a linear, continuous
functional S∘:W1,φ(⋅)(Ω)→R such
that functional G:=F+S∘
has a Lavrentiev gap, i.e.
[TABLE]
3. (c)
The notions of p(⋅)-harmonic functions with respect to
W1,p(⋅) and H1,p(⋅) differ.
Proof.
Since q>p+αmax{1,d−1p−1} and p+αmax{1,d−1p−1} is continuous in p, we can
choose p0>p such that q>p0+αmax{1,d−1p0−1}. In particular, p<p0<q.
Now, let u,b be as in Definition 9 and
S∘ as in (8). We begin with the
definition of our weight a(x),
resp. ω(x)=(a(x))q1.
(a)
(Matching the dimension; Zhikov) p0=d:
Let θa∈C0∞((0,∞)) be such that
\mathbbm1(2,∞)≤θa≤\mathbbm1(21,∞) and ∥θa′∥∞≤6. We define
[TABLE]
2. (b)
(Sub-dimensional) 1<p0<d: Let ρ∈C∞(Rd∖S) be such
that (using Lemma 5)
In the following let x be such that b(x)>0. Then
a(x)=∣xd∣α>0 for p0≤d and
a(x)=∣xˉ∣α>0 for p0>d. Since
φ(x,t)≥a(x)q1tq=q1(ω(x)t)q, it
follows that
φ∗(x,t)≤q′1(t/ω(x))q′=q′1a(x)−q−11tp′=:ψ(x,t). This implies
[TABLE]
We claim that ψ(⋅,∣b∣)∈Lr,∞(Ω) for
some r>1. To prove this we distinguish three cases using
Proposition 14:
(a)
(Matching the dimension; Zhikov) p0=d:
[TABLE]
Thus, by Lemma 7 we have
φ∗(⋅,∣b∣)∈Lr,∞(Ω) with
r:=α+(d−1)qd(q−1). Now, r>1 is equivalent to
q>d+α=p0+α, which is true by choice of p0.
2. (b)
(Sub-dimensional) 1<p0=d−D<d:
[TABLE]
Thus, by Lemma 7 we have
φ∗(⋅,∣b∣)∈Lr,∞(Ω) with
r:=α+(d−D−1)q(d−D)(q−1). Now, r>1 is
equivalent to q>d−D+α=p0+α, which is true
by choice of p0.
3. (c)
(Super-dimensional) p0=1−Dd−D>d.
[TABLE]
Thus, by Lemma 7 (applied to m=1) we have
φ∗(⋅,∣b∣)∈Lr,∞(Ω) with
r:=α+(d−1)q(d−D)(q−1). Now, r>1 is
equivalent to
q>1−Dα+d−D=1−Dα+p0. Since p0=1−Dd−D, we have
1−D=p0−1d−1. Thus, r>1 is equivalent to
q>p0+αp0−1d−1, which is true by choice
of p0.
We have proved that ψ(⋅,∣b∣)∈Lr,∞(Ω)
some r>1, which proves ψ(⋅,∣b∣)∈L1(Ω). Due
to (18) this implies
φ∗(⋅,∣b∣)∈L1(Ω) and
therefore b∈Lφ∗(⋅)(Ω). Overall, we have verified
Assumption 21.
Since p,q∈(1,∞), it follows that φ and φ∗ satisfy
the Δ2 condition. Thus Assumption 25 also holds.
Now, fix s:=tp0−1. Then for suitable large t (and
therefore large s) we obtain
[TABLE]
where we have used p<p0 and q′<p0′. This proves
Assumption 27.
Overall, we have constructed u, b, and p such that the
Assumptions 21, 25 and 27
holds. Now, the claim follows from the results from
Theorem 24, 26 and 28 of
Section 3.
∎
Remark 33**.**
Theorem 32 shows that the dimensional
threshold is not important for the presence of the Lavrentiev gap
and the non-density of smooth functions. (Recall that the previous
examples needed p<d<d+α<p crossing the dimension.)
Since we have overcome the dimensional threshold, it might be
surprising that we obtain different conditions on p and q
for p≤d and p>d. Therefore, let us explain in the following
that our conditions are sharp:
Consider first the case p≤d. In this case we get Lavrentiev
gap for q>p+α. Now, it has been shown in [2]
that if h is a bounded minimizer of F and
q≤p+α, then h is automatically in W1,q(Ω).
Since
W1,q(Ω)=H1,q(Ω)↪H1,φ(⋅)(Ω) it
follows that h∈H1,φ(⋅)(Ω) and there is no Lavrentiev
gap. This shows that our condition q>p+α is sharp. The
boundeness of the minimizer is a reasonable assumption due to the
maximum principle. Also note that our function u is also
bounded. This is reflected by the fact that functions
in W1,φ(⋅)(Ω) can always be approximated by
L∞(Ω)∩W1,φ(⋅)(Ω) functions by means of
truncation.
Now, consider the case p>d. In this case it has been shown in
[1, Theorem 1.4] that if h is a minimizer
of F, h∈C0,γ(Ω) and
q≤p+1−γα, then h is automatically
in W1,q(Ω). Again
W1,q(Ω)=H1,q(Ω)↪H1,φ(⋅)(Ω)
implies that h∈H1,φ(⋅)(Ω) and there is no Lavrentiev
gap. Now, in our example we constructed a
function u∈C0,D(Ω) with
D=p0−1p0−d. Thus, we can compare our condition
q>p+αd−1p−1 for the Lavrentiev gap with
q≤p+1−γα for γ:=D for the
absence of the Lavrentiev gap. Now,
p+1−Dα=p+αd−1p0−1. Since
p0 can be chosen close to p this shows, that our
condition q>p+αd−1p−1 is sharp.
Remark 34**.**
Fonseca, Malý and Mingione studied in [9] the
size of possible singular sets of minimizer of the double phase
potential. For 1<p<d<d+α<q<∞ they constructed
a weight a such that the singular set has Hausdorff dimension
larger than d−p−ε.
Let us compare this to our result. Since p<d, we can choose
p0=p+δ with δ>0 small. Thus, our function u has a
singular set of Hausdorff
dimension D=d−p0=d−p−δ. In particular, we obtain
a singular set of the same size. Note however, that our function u
is not a minimizer yet, but we expect that we can use u as a
competitor to find a minimizer with a singular set of same Hausdorff
dimension. We will work on this question in a future project. Using
out method we hope to overcome the dimensional threshold p<d<d+α<q from [9].
4.3. Weighted p-Energy
In this section we study the model with weighted p-energy. In
particular, we assume that
[TABLE]
where 1<p<∞ and weights a,ω≥0 (almost
everywhere). The corresponding energy is
[TABLE]
Definition 35**.**
The weight a(x) belongs to the Muckenhoupt class Ap if
[TABLE]
where the supremum is taken over all cubes Q.
Our main result of the weighted p-energy is the following:
Theorem 36**.**
Let Ω=(−1,1)d with d≥2 and 1<p<∞. Then
there exists weights a− and a+ of Muckenhoupt class Ap and
another weight a with a+≤a≤a+ such that the
following holds:
(a)
H1,φ(⋅)(Ω)=W1,φ(⋅)(Ω)* and
H01,φ(⋅)(Ω)=W01,φ(⋅)(Ω).*
2. (b)
There exists a linear, continuous
functional S∘:W1,φ(⋅)(Ω)→R such
that G:=F+S∘
has a Lavrentiev gap, i.e.
[TABLE]
3. (c)
The notions of φ(⋅)-harmonic
functions with respect to W1,φ(⋅) and H1,φ(⋅) differ.
It is possible to choose either a or a1 bounded.
Proof.
Let α,β,γ be such that
[TABLE]
If α,β≥0, then a will be bounded. If
α,β≤0, then a1 will be bounded
If γ=1−pd, let p0:=d. If
γ∈(1−pd,p′1), choose p0∈(1,d)
(and hence p0=d−D) such that γ=1−pp0. If
γ∈(−pd−1,1−pd) choose p0>d (and
hence p0=1−Dd−D) such that
γ=p0−1d−1(1−pp0)=pd−1p0−1p−p0. Moreover, let ε>0 be another
parameter. To obtain (c), we have to
choose ε>0 later small.
Now, let u,b be as in Definition 9 and
S∘ as in (8). For our construction and
proof we distinguish the three cases p0=d, p0<d and p0>d.
(a)
We begin with the case of matching the dimension p0=d.
Let θa∈C0∞((0,∞)) be such that
\mathbbm1(2,∞)≤θa≤\mathbbm1(21,∞) and ∥θa′∥∞≤6. We define
[TABLE]
We can assume that ε≤d2β−α, so
that ω−≤ω≤ω+. The weights ω−
and ω+ are of Muckenhoupt class Ap, since
α,β∈(−p1,p′1). It follows by
Proposition 14 that
[TABLE]
and
[TABLE]
Thus, by Lemma 7 we have
φ(⋅,∣∇u∣)∈Lr,∞(Ω) with
r=(1−β)pd>1 using β>γ=1−pd.
This proves ∇u∈Lφ(⋅)(Ω). Moreover, by
Lemma 7 we have
φ∗(⋅,∣b∣)∈Ls,∞(Ω) with
s=(α+d−1)p′d>1 using
α<γ=1−pd. This
proves b∈Lφ∗(⋅)(Ω).
2. (b)
We continue with the sub-dimensional case 1<p0<d. Let
ρa∈C∞(Rd∖S) be such that (using
Lemma 5)
We can assume that ε≤d2β−α, so
that ω−≤ω≤ω+. The weights ω−
and ω+ are of Muckenhoupt class Ap, since
α,β∈(−p1,p′1). It follows by
Proposition 14 that
[TABLE]
and
[TABLE]
Thus, by Lemma 7 we have
φ(⋅,∣∇u∣)∈Lr,∞(Ω) with
r=(1−β)pd−D>1 using
β>γ=1−pd−D=1−pp0. This
proves ∇u∈Lφ(⋅)(Ω). Moreover, by
Lemma 7 we have
φ∗(⋅,∣b∣)∈Ls,∞(Ω) with
s=d−1−D+αd−D>1 using
α<γ=1−pd−D=1−pp0. This
proves b∈Lφ∗(⋅)(Ω).
3. (c)
Let us turn to the super-dimensional case p0>d. Let
ρa∈C∞(Rd∖S) be such that (using
Lemma 5)
The weights ω− and ω+ are of Muckenhoupt
class Ap, since α,β∈(−pd−1,p′d−1).
It follows by Proposition 14 that
[TABLE]
and
[TABLE]
Thus, by Lemma 7 we have
φ(⋅,∣∇u∣)∈Lr,∞(Ω) with
r=(1−D−α)pd−D>1 using
β>γ=1−D−pd−D=p0−1d−1(1−pp0). This
proves ∇u∈Lφ(⋅)(Ω). Moreover, by
Lemma 7 we have
φ∗(⋅,∣b∣)∈Ls,∞(Ω) with
s=(d−1+β)p′d−D>1 using
β<γ=1−D−pd−D=p0−1d−1(1−pp0). This
proves b∈Lφ∗(⋅)(Ω).
Now 1<p<∞ ensures that φ and φ∗ satisfy the
Δ2-condition.
Overall, we have constructed u, b, and p such that the
Assumptions 21 and 25 hold.
We are now going to verify Assumption 27. This will
be the step, where we have to choose ε>0 small enough. It
suffices to prove Assumption 27 in the case
of p0<d. (The other case are completely analogous.)
Overall, we have constructed u, b, and p such that the
Assumptions 21, 25 and 27
holds. Now, the claim follows from the results from
Theorem 24, 26 and 28 of
Section 3.
∎
Remark 37**.**
Note, that Zhikov has also provided in [20, Section 5.3]
another example for H1,φ(⋅)(Ω)=W1,φ(Ω)
for the model of the weighted p-energy for p=2. He was
interested in an example, where the weight is bounded. Since, the
checker board example does not work in this case, he constructed an
example using fractals. For this he split the domain Ω into
two parts Ω1 and Ω0 separated them by another
part N consisting of a Cantor-necklace, see
Figure 7. He then constructed a
weight a∈L∞(Ω) with a1∈L1(Ω) and a
function u∈(L∞(Ω)∩W1,φ(⋅)(Ω))∖H1,φ(⋅)(Ω) with u=0 on Ω0 and u=1
on Ω1. The weight was chosen such that it is integrable on
each block of the necklace and scaled by the size on the smaller
blocks. So the weight becomes smaller on smaller blocks. His
example is contained in the class of possible weights from
Theorem 36.
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