A Note on Sharp Affine Poincaré-Sobolev Inequalities and Exact in Minimization of Zhang’s Energy on Bounded Variation and Exactness ()
1. Introduction
The variational issues have been extensively researched within the domain of boundedly variable functions BV(Ω). This has mostly been in connection with the availability of solutions where the 1-Laplace operator is present, such as in the well-known Cheeger’s problem [1]. See, among other places, [2] - [7] for contributions along this line of thought. A portion of them place a greater emphasis, more especially, on the challenge of reducing the functional
where is a bounded open in
with Lipschitz border,
, and
, and either on the full BV(Ω) space or restricted to some portion of it. Total variation measure of the sequence
, its trace on
, and its Hausdorff measure in dimension
are denoted by
and
, respectively.
Two subsets of BV(Ω) typically considered are:
The associated minimization issue involves proving the existence of minimizers for the least amount of energy.
The relevant issue of minimizing consists of determining whether or not there are minimizers for exponents with the lowest possible quantities of energy.
:
Other non-critical examples are discussed in [5], whereas some crucial cases have been the subject of research in [2] [3] [8] [9] [10]. [5] has been cited for its work.
The reducing of Φ in the sets X and Y (with
) is the fact that several classical functional inequalities, including the [11], have nonzero solutions (extremal functions) is another driving force, and
[11] for
. More specifically, their respective sharp versions on BV(Ω) state that
1) Poincaré inequality (
):
If
such that
;
2) Poincaré-Wirtinger inequality (
):
There exists an optimal constant
such that
;
3) Poincaré-Sobolev inequality (
):
Then
such that
;
4) Poincaré-Wirtinger-Sobolev inequality (
):
Then
such that
,
where
denotes the average of
over Ω, see [12] [13] [14] [15].
Several weaker inequalities than those listed above have been proposed to explain the presence of extremal functions for their sharp affine counterparts, and this serves as inspiration for our own theory of minimization for functional in which the term
gives place to the Zhang’s affine energy.
In [8], Zhang introduced the affine
energy (or functional) for functions
given by
where
. Here,
and
in
. The property
for every
, where
denotes the special linear group of
matrices with determinant equal to 1.
The result of [16] ensures that the sharp Sobolev-Zhang inequality
(1)
holds for all
, under invertible
matrices. Actually, characteristic functions are not in
, but rather belong to
.
The Sobolev-Zhang inequality (II) is weaker than the classical sharp
Sobolev inequality
(2)
since
(3)
(see page 194 of [14] ) as well as (3) being unyielding on non-spherical ellipsoid features. In addition, Zhang said that the Petty projection inequality (e.g. [17] [18] ) is the underlying geometric inequality for (1), whereas the traditional isoperimetric inequality is the underlying geometric inequality for (2). In further work, Wang [19] proved that the Sobolev-Zhang inequality generalizes to functions
, where the affine BV energy is naturally represented by, just as it does in the Sobolev case (e.g. [20] ).
where
the Radon-Nikodym derivative of
, the total variation
on Ω, which satisfies
almost everywhere in Ω (w.r.t.
). Moreover, equality in (1) is exactly accomplished by multiples of ellipsoid characteristic functions, and even after being translated to (3), it retains its inferiority to the classical predecessor
(4)
After Zhang’s first breakthrough, a wealth of further literature was produced detailing several refinements and new affine functional inequalities. The majority of the contributions are available at [21] - [38]. Given a function
, denote by
its zero extension outside of Ω. The Lipschitz regularity of
guarantees that
,
(5)
and
-almost everywhere on
, where
denotes the unit outward normal to
(see e.g. page 38 of [27] ). Implies that
The preceding Formulas (4) and (5), and a reverse Minkowski inequality compare the affine BV energy of zero extended functions to local expressions:
(C1)
for all
;
(C2)
for all
;
(C3)
for all
with
on
(a.e.) or limitless potential so long as is non-flat in the sense that
on
(a.e.) for every
, where
denotes the subspace of
of functions with zero trace on
,
and
(C3) is more complicated than (C1) and (C2) (Corollary 3.1). Ball domains satisfy the geometric requirement. They are affine invariants.
and
for every
.
From (C1), the term
weakens the right-hand side of (
) and (
), encouraging us to study the new functional.
,
The well-definedness of
for limited weights a and b may be shown by invoking the trace embedding and (4).
Consider the least energy levels of
on X and Y:
Theorem 1.1. The levels
and
are attained for any
.
The next one covers critical cases.
Theorem 1.2. The levels
and
are attained for any
, provided that
and
, respectively.
As a result of its weak* closure in
,, the logic used to prove Theorems 1.1 and 1.2 yields equivalent assertions on the space
(Proposition 3.2). To be more specific, when applied to functions with zero trace in
, the functional
calculated using (C2) yields
Denote by
and
the respective least energy levels of
on the sets
and
.
Theorem 1.3. The levels
and
are attained for any
.
Theorem 1.4. The levels
and
are attained for any
, provided that
and
, respectively.
The Sobolev-Zhang inequality on
yields the sharp affine variants of (
) and (
) and also of (
) and (
) for
:
1) Inequality of Poincaré affineness (
):
A best constant may be found.
such that
;
2) Inequality via the affine Poincaré-Wirtinger transform (
):
There exists an optimal constant
such that
;
3) The Poincaré-Sobolev inequality (
):
A best constant may be found
such that
;
4) Affine Poincaré-Wirtinger-Sobolev inequality (
):
A best constant may be found
such that
.
It also deserves to be noticed that
and
are incomparable via a one-way inequality in
. In effect, since
and
, there is no constant
such that
holds for all
. On the other hand, a reverse inequality also fails in view of the example of [38] in
. Accordingly, (
) and (
) seem to be natural affine counterparts of (
) and (
), respectively.
Nonetheless, the term
appears on the right-hand side when we restrict ourselves to functions in
. In this space, we denote the respective inequalities by (
), (
), (
) and (
).
A direct application of Theorems 1.1 and 1.3 for
is as follows:
Theorem 1.5. The inequalities (
) and (
) and also (
) and (
) with
admit extremal functions in
. The same conclusion holds true in
for (
), (
), (
) and (
).
Recent work has focused on finding extremal functions for local affine
-Sobolev type inequalities, and to our knowledge, this topic has only been discussed in the context of functions with zero trace in the publications [38] and [39]. In particular, the first one provides extremals for the affine L2-Sobolev inequality on
,, while the second one provides extremals for the affine L(1+)-Poincaré inequality on
for any
and on
for
. For example, in [38], the authors provide a different demonstration of Theorem 1.5 for on
using an elegant method based on their Lemma 1 and Theorem 9.
In the critical case
, one knows from (1) that characteristic functions of ellipsoids in Ω are extremals of (
), however, exist no extremal for (
). The usual argument of nonexistence consists in showing, by means of a standard rescaling, that the optimal constant corresponding to
is also
. The key points are the strict continuity of
on
(Theorem 4.4 of [19] ) and the density of
in (
) (Corollary 3.2 of [40] ), where
denotes the space of bounded functions in
with compact support.
We close the introduction with an application of Theorems 1.1 and 1.3 for
.
We point out that (
), (
), (
) and (
) are prototypes of more general affine inequalities depending on
and
. Precisely, for each
, let
be the unique function that satisfies
for all
. It is important to note that
is continuous, 1-homogeneous and bounded on bounded subsets of
. Of course,
for
. The construction of
is canonical and makes use of basic results as the mean value theorem and dominated and monotone convergence theorems.
The properties satisfied by
together with (1) produce two new affine inequalities for
that extend (
), (
), (
) and (
).
1) Generalized affine [11] inequality (
) on
:
There exists an optimal constant
such that
.
2) Generalized affine [11] inequality (
) on
:
There exists an optimal constant
such that
criteria that follow.
2. Background on the Space BV(Ω)
We talk about some basic definitions and old results about functions with limited changes. Books [13] [20] [40] are good places to look for more information on the subject.
Let be a part of
that is open with
. A function
is said to have bounded variation in if its distributional derivative is a Radon measure with a vector value. Du
in Ω, that is,
is a Radon measure fulfilling
for every
.
stands for the vector space of all functions with bounded variation in
total dispersion is characterized by
where
. The variation
is a positive Radon measure on Ω. Denote by
the Radon Nikodym derivative of
with respect to
. Then,
is a measurable field satisfying
almost everywhere in Ω (w.r.t.
) and
.
For
, the Lebesgue-Radon-Nikodym decomposition of the measure
is given by
where
and
denote respectively the (density) absolutely continuous part and the singular part of
with respect to the
-dimensional Lebesgue measure
and
is the Radon-Nikodym derivative of
with respect to its total variation measure
. In particular,
The space
is Banach with respect to the norm
however, it is neither separable nor reflexive.
The strict (intermediate) topology is induced by the metric
The weak* topology, the weakest of the three ones, is quite appropriate for dealing with minimization problems. A sequence
converges weakly* to
in
, if
strongly in
and
weakly in the measure sense, that is,
for every
.
Let’s pretend is a Lipschitz-bounded bounded open. Listed below are some of the most well-known characteristics that will be used later on:
1) Every
admits a weakly* convergent subsequence;
2) Every weakly* in
is bounded;
3)
is embedded continuously into
for
and compactly for
;
4) Each function
admits a boundary trace
in
and the trace operator
is continuous on
with respect to the strict topology;
5) For any function
, its zero extension
outside of Ω belongs to
;
6)
defines a norm on
equivalent to the usual norm
;
7)
is dense in
with respect to the strict topology.
3. Lower Weak* Semi Continuity of
For an open subset
and
, consider the affine BV energy
We start by giving an answer to the question:
When is the affine energy
zero?
For each
, denote by
the functional on
,
Theorem 3.1. (See [14] ) Let
. Then,
if, and only if,
for some
.
Proof. The sufficiency is the easy part. In fact, assume that
for all
. Thanks to the continuity of
, there exists a constant
so that
for all
. But this lower bound immediately yields
.
Conversely, we prove that
whenever
for some
. Let
be the maximum number of linearly independent vectors
such that
. If
, then clearly
in Ω and thus, by (4), we have
. Else, choose an orthonormal basis
of
so that
for
, which correspond to the last m vectors of basis with
.
For
and
, write
The condition
implies that
for
. So, the Cauchy-Schwarz inequality gives
Set
and
. Since
, we get

and hence
.
An interesting application of Theorem 3.1 of independent interest, is (see [14] )
Corollary 3.1. Let
be a bounded open with Lipschitz boundary. Then,
for all
with
on
(a.e.) or without any restriction in case
is non-flat, where the definitions of
and non-flat boundary were given in the comparison (C3) of the introduction.
Proof. Firstly, the identity
gives
and
. Therefore, if
or
, the conclusion follows.
Assume that
and
are nonzero. Set
and
, where
By Theorem 3.1 we have
for all
. If
and the assuming the statement imply that
for all
. Then, we get
The next step is to prove that of
on
is weak* continuous below uniform bounds on the total variation. Outside of Theorem 3.1, the proof relies on pivotal conclusions by Goffman and Serrin (Theorems 2 and 3 of [39] ). For different enhancements and expansions of [41], we also refer to [42] and [43], as well as references therein.
Let
be a nonnegative convex function with linear growth, that is,
for all
, where
is a constant. Define the recession function
associated to
by
For
, write
and let
defined by
Proposition 3.1
The functional Ψ is strongly lower semicontinuous on
.
Theorem 3.2. (See [14] ) If
strongly in
and
is bounded, then
Proof. Let
be a sequence converging strongly to
in
such that
is bounded. If
for some
,
by Theorem 3.1, we have
and the conclusion follows trivially.
It then suffices to assume that
for all
. Set
for any
. Since
is convex, nonnegative, 1-homogeneous and
, we have
Hence, by Proposition 3.1
is strongly lower semicontinuous on
, and so
(6)
We now ensure the existence of a constant
and an integer
, both independent of
, such that, for any
,
(7)
Otherwise, module a renaming of indexes, we get a sequence
such that
and
Using the assumption that
is bounded, we find a constant
such that
Then, by (6), we get
.
Finally, combining (6), (7) and Fatou’s lemma, we derive
and thus

As an immediate consequence of Theorem 3.2 we have:
Corollary 3.2. If
weakly* in
, then
This result is the key point towards the lower weak* semicontinuity of the functional
. We recall that
where
and
. Since the integral functional on Ω is clearly weakly* continuous on
, it only remains to discuss the semicontinuity of the boundary integral term.
Proposition 3.2. (See [44] ) If
weakly* in
, then
Proof. Let
be a sequence converging weakly* to
in
. For each
, we consider the norm
on
Since
,
is equivalent to
and
, and so
(8)
Take a constant
so that
and a subsequence
such that
By (8), for j large, we get
Letting
and after
, the statement follows as wished.
Finally, Corollary 3.2 and Proposition 3.2 lead to
Corollary 3.3. The functional
is lower weakly* semicontinuous on
.
4. Subcritical Minimizations with Constraints on BV(Ω)
Theorems 1.1 and 1.3 are proved. Corollary 3.3 and the Rellich Kondrachov compactness theorem are key:
Theorem 4.1. The affine ball
is compact in
for any
.
Proof requires two preliminary outcomes. First, weak* convergence of displacements of limited sequences in
and strong convergence in
. In other spaces, embedding co-compactness has been extensively investigated [45] [46] [47]. This proves the completeness.
Proposition 4.1. (See [14] ) Let
be a bounded sequence in
. Then,
locally weakly* in
for any sequence
in
if, and only if,
strongly in
for any
.
Proof. Assume first that
strongly in
for some
. If
doesn’t converge locally weakly* to zero
in
for some sequence
in
, then there is a bounded open subset Ω of
and
such that, module a subsequence,
or
for some
, where
. Since
is bounded in
, one may assume that
weakly* in
. Thus, letting
in the two cases, one gets
or
. On the other hand, one knows that
strongly in
and
strongly in
, so
in Ω. But this contradicts the last two inequalities.
Conversely, assume that
locally weakly* in
for any sequence
in
. Choose a fixed
and consider the
-cube
. Using the continuity of the Sobolev immersion
↪
, we deduce that
for every
, where C is a constant independent of
.
By adding the inequality over
, we obtain
(9)
Right-hand side of (9) is finite.
, bounds u k, hence it also bounds
and in
by Sobolev inequality. Then,
and a simple interpolation.
Choose
so that
Hence, (9) gives
(10)
for some constant
independent of k.
However, the rigorous condition
lets us apply the Rellich-Kondrachov compactness theorem to the embedding
↪
In order to make a rough calculation of the right side of (10). In fact, module a subsequence, we have
strongly in
. But, by assumption,
locally weakly* in
, and so
strongly in
. Therefore,
in Q and, since
, we deduce from (10) that
strongly in
.
As noted, exist no upper bound for
in terms of
on
.
However, Huang and Li (Theorem 1.2 of [48] ) established that such an estimate holds true for functions
unless an acceptable affine transformation T depends on
. Wang’s [49] tools allow the finding to apply to
.
Proposition 4.2 (Huang-Li Theorem). For any
, one has
where
.
Proof of Theorem 4.1. (See [44] ) Let
be a sequence in
. By Proposition 4.2 there is a matrix
such that
. Note also that
, so
is bounded in
. We now analyze two possibilities.
Assume first that
. Let
be an arbitrary sequence in
. The boundedness of
in
implies, module a subsequence, that
locally weakly* in
. Since
, the Rellich Kondrachov compactness theorem also gives
strongly in
and
almost everywhere in
, up to a subsequence. Consider the set

Since
and Ω is bounded, X has zero Lebesgue measure (e.g. page 7 of [46] ). For
, we have
for any
, which yields
for every k, up to a subsequence. Thus,
and hence
locally weakly in
for any sequence
in
. By Proposition 4.1,
strongly in
and so
strongly in
.
If
, then one may assume that
converges to some
. Choose
large enough so that
and
for every k. Module a subsequence, we know that
weakly* in
and
strongly in
.
Set
in Ω. Notice that
once
. Let
be the extension of
by zero outside of Ω. Since
converges to the identity I, by the generalized dominated convergence theorem, it follows that
. Consequently, since
, we have
A fact that follows from the proof and deserves to be highlighted is
Corollary 4.1. Let
be a sequence in
such that
strongly in
for some
. If
, then
is bounded in
.
Proof of Theorem 1.1. (See [13] ) Let
,
in X. By Hölder’s inequality,
is bounded in
,
on
, the affine energy
is also bounded. Therefore, by Theorem 4.1 there exists
such that
strongly in
. Therefore,
and, by Corollary 4.1,
is bounded in
.
Passing to a subsequence, if necessary, one may assume that
weakly* in
. Then, by Corollary 3.3 we derive
and thus
minimizes
in X.
The same argument also works for a minimizing sequence
of
in Y. So,
weakly* in
and
strongly in
, module a subsequence, and thus
and
It remains to check that
, which it follows readily from Theorem 4.1 applied to
for
.
Proof of Theorem 1.3. (See [14] ) Applying Proposition 3.2 with
, we conclude that the space
is weakly* closed in
. Then, the limitation of
to
may be shown as before.
5. Critical Minimizations under Constraints on BV(Ω)
Consider the truncation for
:
Proposition 2.3 of [2] ensures that
for every
.
Proposition 5.1. (See [14] ) For any
,
Proof. We first prove the inequality for functions
. From the definition of
, we have
and
for all
, where
Note that this decomposition implies
and
. Thus, the statement follows if
or
.
Assuming that
and
are nonzero, by Theorem 3.1, we have
for all
. So, by the Minkowski’s inequality for negative exponents, we get
Finally, the inequality extends to
by using both the density of
in
and the continuity of
with respect to the strict topology.
Proof of Theorems 1.2 and 1.4. (See [14] ) Thanks to the weak* closure of
in
, it is enough to just prove Theorem 1.2.
Let
be a minimizing sequence of
in X. Proceeding as in the proof of Theorem 1.1 by Theorem 4.1, have
strongly in
, module a subsequence. One may also assume that
almost
everywhere in Ω and
weakly in
.
Using the Sobolev-Zhang inequality on
,
and that b is nonnegative, we derive
so the condition
implies that
. Hence, by Corollaries 3.3 and 4.1 we have
weakly* in
and
. It only remains to show that
.
By Proposition 5.1, we easily deduce that
Applying Lemma 3.1 of [2], we have
Using the condition
and letting
, one obtains
and thus
because
.
The sequence
of
is taken in Y, then
almost everywhere in Ω,
and
. On the other hand, the first two properties along with Brezis-Lieb Lemma imply that
strongly in
. Finally, since
, it follows that
.
6. Conclusion
We establish the existence of minimizers for a class of restricted variational problems on
using the affine energy first presented by Zhang in [16], both for subcritical and critical limitations. Functionals that are related to this one have non-coercive geometry, and further in the weak* topology you’ll find features like lower semicontinuity and affine compactness. Our work also proves the existence of extremal functions for certain classes of affine Poincaré-Sobolev inequalities.