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Journal of Function Spaces and Applications
Volume 2012 (2012), Article ID 128520, 20 pages
Weighted Estimates for Maximal Commutators of Multilinear Singular Integrals
Department of Mathematics, Jiangxi Normal University, Nanchang 330022, China
Received 11 July 2012; Accepted 1 September 2012
Academic Editor: Ti- Xiao
Copyright © 2012 Dongxiang Chen and Suzhen Mao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper is concerned with the pointwise estimates for the sharp function of the maximal multilinear commutators and maximal iterated commutator , generalized by -linear operator and a weighted Lipschitz function . The boundedness and the boundedness are obtained for maximal multilinear commutator and maximal iterated commutator , respectively.
1. Introduction and Notation
The theory of multilinear Calderón-Zygmund singular integral operators,originated from the work of Coifman and Meyers’, has an important role in harmonic analysis. Its study has been attracting a lot of attention in the last few decades. So far, a number of properties for multilinear operators are parallel to those of the classical linear Calderón-Zygmund operators but new interesting phenomena have also been observed. A systematic analysis of many basic properties of such multilinear operators can be found in the articles by Coifman and Meyer , Grafakos and Torres [2–4], and Lerner et al. . So we first recall the definition and results of multilinear Calderón-Zygmund operators as well as the corresponding maximal multilinear operators.
Definition 1.1. Let be a multilinear operator initially defined on the m-fold product of Schwartz space and taking values into the space of tempered distributions:
Following , we say that is an m-linear Calderón-Zygmund operator if for some , it extends to a bounded multilinear operator from to , where , and if there exists a function , defined off the diagonal in , satisfying
for all supp.
And for some and all , where .
The maximal multilinear singular integral operator was defined by where is the smooth truncation of given by As pointed in , is pointwise well defined when with .
The study for the multilinear singular integral operator and its maximal operators attracts many authors’ attention. For maximal multilinear operator , one can see  for details. We list some results for as follows.
Theorem A (see ). Let and q such that and . Let be an m-linear Calderón-Zygmund operator. Then there exists a constant , such that for all satisfying where W is the norm of in the mapping : .
Theorem B (see ). Let be an m -linear Calderón-Zygmund operator. Then, for all exponents , satisfying , one has when , one also has when at least one is equal one. In either cases the norm of is controlled by a constant multiple of .
Definition 1.2 (see  (commutators in the th entry)). Given a collection of locally integrable function , we define the commutators of the -linear Calderón-Zygmund operator to be where each term is the commutator of and in the th entry of , that is
In , the following more general iterated commutators of multilinear Calderón-Zygmund operators and pointwise multiplication with functions in BMO were defined and studied in products of Lebesgue spaces, including strong type and weak end-point estimates with multiple weights. That is,
For the operator , when is the Calderón-Zygmund singular integral operator and (the homogeneous Lipschitz spaces), Paluszyński  established the boundedness with and . Hu and Gu  extended this results to the case: with .
Now we present the definitions of two classes of maximal commutators of multilinear singular integral operators. One is the other is where . It is obvious to see that The main purpose of this paper is to extend the results in  to the maximal commutators generated by multilinear singular integrals and functions .
We can formulate our result as following.
Theorem 1.3. Assume that the kernel satisfies (1.3) and (1.4). Let be given numbers satisfying . And assume that maps to . For and let , , , and with , . Given such that and , then one has From (1.15) and (1.16), one can get
If , one can get the following.
The following theorem states the weighted estimates with two different weights for maximal iterated commutator of multilinear singular integrals.
Similarly as Theorem 1.4, one also obtains the unweighted estimates of maximal iterated commutators.
The rest of this paper is organized as follows. In Section 2, we recall some standard definitions and lemmas. Section 3 is devoted to the proof of our theorems. Throughout this paper, we use the letter to denote a positive constant that varies line to line, but it is independent of the essential variable. For any , the is always used to denote the dual index such that .
A nonnegative function defined on is called weight if it is locally integrable. A weight is said to belong to the Muckenhoupt class , , if there exists a constant such that for every ball . A weight is said to belong to class if for every ball . The class can be characterized as .
Many properties of weights can be found in the book , we only collect some of them in the following lemma which will be used bellow.
Lemma 2.1. for ;(ii) if , then for ;(iii)for , if and only if .
A locally integrable function belongs to the weighted Lipschitz space for , and if The smallest bound satisfying (1.19) is then taken to be the norm of denoted by . Put .
If , from the definition of , it is obvious to see where .
The important properties of the weights are the weighted estimates for the maximal function, the sharp maximal function and their variants. One first recalls the maximal function defined by It is well known that for , maps into itself if and only if , see .
The sharp maximal function is defined by One also recalls the variants , and . We denote the weighted fractional maximal operators by Recall that is the weighted fractional maximal operators, that is The following lemmas are all from .
Lemma 2.2 (Kolmogorov’s inequality). Let be a probability measure space and let then there exists a constant such that for any measurable function
Lemma 2.3. Let and , there exists depending on the constant of such that for any function for which the left side of the above inequality is finite.
Lemma 2.4. Suppose that , , . If , then there exists a constant such that for any measurable function
Lemma 2.5. Suppose that , , . If , then there exists a constant such that for any measurable function
3. Two Estimates for Maximal Multilinear Commutators
We will prove our theorems in this section. To begin, we prepare another two iterated operators to control the commutators.
Let such that , and satisfying We define the maximal operators For simplicity, we denote , and The kernels of and satisfy conditions (1.3) and (1.4) uniformly in , respectively. And by the same argument in , both and have the same weighted estimates to that appeared in Theorems A and B.
It is easy to see that . Moreover, where For simplicity, we will only prove for the case . The arguments for the case are similar. For the similarity to the two commutators and , we might as well consider the former. We only consider the former. And we establish the following crucial lemma.
Lemma 3.1. Let and , with , . Let . Then one has
Proof. Without loss of generality, we only consider the case and denote by for convenience. Fix and let , be the average of on , where . To proceed, we decompose , where , . Let be a constant to be fixed along the proof.
Since , we have For , since , and , by Hölder’ inequality, we have
To estimate the second term . Since , using Kolmogorov’s inequality with , , , and the -boundedness of , we derive that where we have used the analogous technique in to get the last inequality.
For the term , using the fact for any , , and note that satisfies (1.3) uniformly in , we obtain For the term , using the fact for any , , and note that satisfies (1.3) uniformly in , and using (2.4), we obtain
For , fix the value of by taking , recall that satisfies (1.4) uniformly in , then we can obtain where in the last inequality, we use the same computation in the term.
Consequently, combining the estimates of , and , we conclude the proof of Lemma 3.1.
Now we are ready to return to prove Theorem 1.3.
Proof. First, by Lemma 2.1, we have that , and hence . Then by Lemma 2.3, we obtain
For , by Lemma 3.1, we reduce to bound the norm of the right-hand side of (3.6). For the first term, since and taking such that , by Lemma 2.4, and Theorem B(ii), we have
For the second term, we let , and . Then by Lemma 2.4 again, together with Hölder’s inequality, we obtain We can obtain that Similarly, we have Consequently, by the above arguments, we conclude the proof of Theorem 1.3.
Lemma 3.2. Let and ; , and . And let , . Then one has
Proof. Fix and let with . Taking , the average of on , , where . Let be a constant to be fixed along the proof. We split in the following way:
Since , then we have
For the term , since , and , then by Hölder’s inequality, we have
For the term , noting that , we use the facts and , then by Hölder’s inequality and Komolgorov’s inequality (Lemma 2.2) and Theorem B, we have Similarly, for the term , we have
Now we turn to estimate the last term . To proceed, we denote that , where ,