1. Introduction
The classical space
, originally formulated by Coifman and Rochberg in [
1], comprises all locally integrable functions
h such that the following is written:
where the supremum runs over all cubes
and the following:
A significant characterization of
was established by Bennett in 1982 [
2], using the natural maximal operator in connection with the
space. Liu and Yang [
3] extended Bennett’s result [
2] to Gauss measure metric space. For a more comprehensive account of the research on the space
, we refer the reader to Leckband [
4], Jiang [
5], Tang [
6], Yang [
7,
8] and the references therein [
9,
10,
11,
12,
13].
The problem of characterizing
under weaker integrability conditions can be traced back to Strömberg [
14]. Afterwards, the studies of [
15,
16,
17] further demonstrate the weak conditions of defining
. More recently, assuming concavity of the function
, Canto, Pérez and Rela in [
18] (Theorem 1.1) further researched the findings of [
15] by establishing minimal integrability conditions in terms of Luxemburg-type norms, specifically expressed as follows:
Throughout these discussions, setting
for some
yields the equivalence
.
Although the space
has been extensively investigated under minimal integrability assumptions, analogous results for
remain largely undeveloped. Motivated by this gap, the present work is devoted to establishing Luxemburg-type characterizations of
spaces under both convexity and concavity conditions. The Luxemburg norm, originating from the modular approach to Orlicz spaces, provides a classical yet versatile framework for studying generalized integrability conditions. For a recent application of the Luxemburg norm in approximation theory, we refer the reader to Costarelli and Vinti [
19].
Our aim is to identify the minimal integrability requirements for characterizing via Luxemburg-type formulations. To this end, we begin by recalling several fundamental notions.
For a cube
R, if
:
is a function and
is a locally integrable function on
R, then the Luxemburg-type norm is given by the following:
Moreover, we define the following
Definition 1. Let φ:. The Luxemburg-type space, denoted by , consists of the collection of all measurable functions h: such that the composition is locally integrable over , and satisfies the following:where is defined as in (2). If , then the Luxemburg-type space coincides with the classical space . We now recall the definitions of convex and concave functions. Let
and
. If the following is true:
then
:
is the said convex function. If the following is true:
then
:
is said concave function.
Remark 1. Recall [20] (Remark 1.4), if : is convex satisfying and , then we find that the inverse function is well defined on , where is given by (5). In addition, if is concave and satisfies , then is necessarily increasing on . Furthermore, when is increasing and concave with , it follows from [15] (Remark 1.3) that for any , the following is calculated: Definition 2. Let φ: be a given function, and denote a space endowed with a quasi-metric d and a doubling measure η. Let be defined as in (2). - (i)
The space consists of all functions h satisfying the following: - (ii)
The space includes all functions h for which is locally integrable function on and the following:
Definition 3. Let φ: be a function, be defined as in (2) and ω be non-atomic measure. - (i)
The space consists of all functions h for which the following is calculated: - (ii)
The space includes all functions h for which is locally integrable function on and the following:
Definition 4. For any cube centered at x with side length L, assume the existence of constants for which the following is calculated:holds for . Then we assert that the measure ω is non-atomic. The structure of the paper is organized as follows.
Section 2 is devoted to Luxemburg norm characterizations of
in Theorems 1 and 2, where we establish the fundamental equivalence results in the Euclidean setting.
Section 3 addresses Luxemburg norm characterizations of
in Theorem 3, extending the previous analysis to the space of homogeneous type.
Section 4 presents Luxemburg norm characterization of
in Theorem 4, in which we further investigate the weighted framework under non-atomic measures. Finally,
Section 5 provides a conclusion, where we summarize the main contributions.
In this paper, the following terminology and notation will be employed: Define . For subset , denote its complement by . The notation indicates the existence of a constant such that ; similarly, means . We write when both and hold.
2. Luxemburg Norm Characterizations of ()
In this section, we present Theorems 1 and 2, which establishes the Luxemburg norm characterizations of
. To proceed, we begin by recalling the John–Nirenberg-type inequality for the
space, as stated in [
9] (Lemma 2.1).
Lemma 1 ([
9])
. If , then, there exist constants for which it holds that the following is true:for all , and , where is as in (2). Lemma 2 ([
20])
. Let φ: be convex satisfying and . Then, for any and , calculate the following:where is defined in (5). Theorem 1. Assume that φ: is a function with and . Then the following hold.
- (i)
Suppose that φ is convex and denotes the inverse of φ on with the following:If there exists satisfying the following:then the spaces and can be identified with equivalent norms. - (ii)
If φ is concave, then . Moreover, there exist constants such that the following is calculated:
Proof. Now, we first verify (i). Given any
, we will verify the following:
where
and
is defined in (
5). Observe that
for such
C. We normalize
. Denote by
the constant defined in (
2). For any cube
, we calculate the following:
Applying Lemma 2, we deduce the following:
The inequality (
7) is thus derived by applying the supremum over all cubes
Q.
Next, suppose
. Our goal is to prove the following:
A sufficient condition for (
8) is the existence of a constant
satisfying the following:
To verify (
9), assume
. Set
, where
is as in (
6) and
is from Lemma 1. By Remark 1,
exists on
, with
defined in (
5). Then, we calculate the following:
From condition (
6), one has the following:
Furthermore, since
is convex with
, then, for any
and
, calculated as follows:
We define the following:
Using this, together with the above inequalities (
10) and (
11), we derive the following:
which establishes (
9). Then (
8) holds. Finally, combining (
7) and (
8) yields that
with equivalent norms. This implies that (i) holds.
We now proceed to prove (ii). Assume that
:
is increasing and concave with
and
. Let
be defined as in (
2). From Remark 1, we find that
is increasing. Given a cube
, applying Jensen’s inequality, we obtain, for constant
, the following:
From this and Definition 1, the following is assumed:
Below, we only need to verify the converse inequality, written as follows:
which directly follows from the following inequality
Suppose that
. Then the Luxemburg norm condition implies that, for any cube
Q, the following is calculated:
To prove (
12), we define the following:
Since the finiteness of
X is not guaranteed, for a large number
t, we instead consider the following truncated quantity:
Then, we have
. From (
13), we know the following:
therefore, if we take
applying the Calderón–Zygmund decomposition yields non-overlapping dyadic cubes
and constant
such that the following properties hold:
- (i)
;
- (ii)
for a.e.;
- (iii)
.
Regarding
, by (ii) and the increasing property of
, it follows that for
, the following is valid:
which implies the following:
Now, we consider
. For any
, according to (
3), (i) and (
13), we see the following:
From this and the following
the following is calculable:
where the penultimate step used the definition of
and the last step used (iii).
Combining the above bounds for
and
, we have the following:
Taking the supremum over all intervals, we choose
and obtain that there exists a constant
such that we calculate the following:
Finally, we let
and obtain (
12). So, we conclude that (ii) holds. This finishes the proof of Theorem 1. □
As application of Theorem 1, we give a related result as follows:
Theorem 2. Let be a function with and . If , then .
Proof. Assume that is measurable function with and . By analyzing the growth of at infinity, we construct a polygonal function such that is concave and for large values of s.
Specifically, for
, define
. For
, the function
is defined as a polygonal curve composed of linear segments joining points of the form
and
, with
chosen so that
is continuous, concave, and satisfies
. As a consequence of this construction, the following is assumed:
Then we only need to verify the following:
To simplify the argument, let
. Assume that
is defined as in (
2). For a fiven cube
Q, we following the proof of (
12), if we claim the following:
Then we repeat the argument of (
12) and obtain that (
14) holds. Moreover, we calculate the following:
It remains to show (
15). Referring the proof of [
18] (pp. 10–11) and replacing
with
, we conclude that (
15) holds. This end the proof of Theorem 2. □
3. Luxemburg Norm Characterization of
In preparation for the proof of Theorem 3, this section first recalls some concepts about the space of homogeneous type (see [
21]) and two key Lemmas from [
18] (Lemmas 3.1 and 3.2).
Assume that
is a set and
d is a quasi-metric, that is,
d satisfies quasi-triangular inequality, written as follows:
where
is a finite constant. For a measure
and a ball
with center
and radius
, if there exists constant
independent of
y and
t such that we calculate the following:
then we say that
satisfies the doubling condition. Define
to be the smallest constant in the doubling condition, and let
denote the doubling dimension of
. For any balls
with
, we utilize the above doubling condition to derive the following:
where
is a positive constant,
and
mean the radius of
and
, respectively.
Assume that
is the set,
d is a quasi-metric and
is a doubling measure. The space of homogeneous type is a triple
. To simplify the concept, for a ball
B, we fix
and define the following:
and
Lemma 3. Assume that is a family of balls whose radius are bounded. Then one can find a subcollection consisting of mutually disjointed balls satisfying the following: Lemma 4. Let and B be a ball. There is a sufficiently large constant for which any ball P whose center lies in B and satisfies the following:it holds that . Furthermore, choosing ϵ sufficiently small ensures that . Theorem 3. Let φ: be a function satisfying and . If φ is concave, then with equivalent norms.
Proof. Proceeding as in the proof of Theorem 1, based on Remark 1, we have that
exist. Let
be defined as in (
2). For any ball
B, by applying Jensen’s inequality, we deduce the following:
which implies the following:
Therefore, we establish the following reverse inequality:
To prove this, we need to show the following:
for all
B balls. Assume that
. Then, we define the following:
To prove (
17), we define the following:
We claim that
X is finite. Assume that
is a parameter to be determined. We define this as follows:
For any
, we use Lebesgue differentiation theorem to derive that there exists
centered at
x satisfying the following:
So, we construct a family
, where
satisfies (
19) and
for all other ball
satisfying (
19). Using Lemma 3, we obtain a maximal subfamily
.
Further, when
L is chosen sufficiently large and
, we utilize Lemma 4 to derive
and the following:
Moreover, we have the following:
where
refers to a constant that depends solely on
.
Now, we summarize the key features of as follows:
- (i)
For , and , we have ;
- (ii)
;
- (iii)
and ;
- (iv)
there exist constants such that .
To verify (
17), by
, we write the following:
For term
, by the definition of
and Remark 1, we obtain, for any
, the following:
which allows us to obtain the following:
Now, we consider
. Based to
, by (
3), (iii) and (
18), we have the following:
where
refers to a constant that depends solely on
. Combining properties (ii) and (iv), we estimate II as follows:
where the third step used the definition of
X and
is as in (iv).
Finally, utilizing the bounds for
and
together, we obtain the following:
Taking the supremum over all intervals and choosing
, we conclude that there exists constant
dependent of
such that we obtain the following:
This allows us to derive (
17). We finish the proof of Theorem 3. □