1 Introduction and main results

The boundedness of fractional integral operators on the classical Morrey spaces was studied by Adams [1], Chiarenza and Frasca et al. [2]. In [2], by establishing a pointwise estimate of fractional integrals in terms of the Hardy-Littlewood maximal function, they showed the boundedness of fractional integral operators on the Morrey spaces. In 2005, Sawano and Tanaka [3] gave a natural definition of Morrey spaces for Radon measures which might be non-doubling but satisfied the growth condition, and they investigated the boundedness in these spaces of some classical operators in harmonic analysis. Later on, Sawano [4] defined the generalized Morrey spaces on R n for non-doubling measure and showed the properties of maximal operators, fractional integral operators and singular operators in this space.

Simultaneously, in 1999, Kenig and Stein [5] gave the boundedness for multilinear fractional integrals on Lebesgue spaces. In 2002, Grafakos and Torres [6] obtained the boundedness for multilinear Calderón-Zygmund operators on Lebesgue spaces. From then on, the theory on multilinear integral operators has attracted much attention as a rapidly developing field in harmonic analysis. Recently, the authors have studied the boundedness of multilinear fractional integrals on Herz-Morrey spaces in [710] and the boundedness of multilinear Calderón-Zygmund operators on the Morrey-type spaces in [1114]. Particularly, the authors [7, 11, 13, 15] established the boundedness for the multilinear operators on Morrey spaces over R n with non-doubling measures. In this paper, we focus on the multilinear operators on generalized Morrey spaces over quasi-metric space (X,ρ,μ) of non-homogeneous type and extend the works in [37, 11, 16].

Let (X,ρ) be a quasi-metric space with the quasi-metric function ρ:X[0,) satisfying the conditions:

  1. (1)

    ρ(x,y)>0 for all xy, and ρ(x,x)=0 for all xX.

  2. (2)

    There exists a constant a 0 1 such that ρ(x,y) a 0 ρ(y,x) for all x,yX.

  3. (3)

    There exists a constant a 1 1 such that

    ρ(x,y) a 1 ( ρ ( x , z ) + ρ ( z , y ) )
    (1.1)

for all x,y,zX.

Here we point out that there is no notion of dyadic cubes on the quasi-metric space and so the method for R n used in [15] does not work on (X,ρ). Recently, Hytönen [17] introduced the notion of geometrically doubling space.

Definition 1.1 The quasi-metric space (X,ρ) is called geometrically doubling if there exists some N 0 N such that any ball B(x,r)X, where B(x,r):={yX:ρ(x,y)<r} with the center x and the radius r, can be covered by at most N 0 balls B( x i ,r/2) with x i B(x,r).

Remark 1.2 Similarly as Hytönen showed in Lemma 2.3 in [17], one can deduce that if the quasi-metric space (X,ρ) is geometrically doubling, then, for any δ(0,1), any ball B(x,r)X can be covered by at most N 0 δ n balls B( x i ,δr) with x i B(x,r), where n= log 2 N 0 .

Given a Borel measure μ on the quasi-metric space (X,ρ) such that μ is finite on bounded sets, and let (X,ρ) be geometrically doubling, then continuous, boundedly supported functions are dense in L p (X,μ) for p[1,). See Proposition 3.4 in [17] for details.

The above triple (X,ρ,μ) will be called a quasi-metric space of non-homogeneous type if the measure μ satisfies the following growth condition,

μ ( B ( x , r ) ) C 0 r
(1.2)

with the constant C 0 independent of the ball B(x,r)X. The set of all balls BX satisfying μ(B)>0 is denoted by B(μ). We know that the analysis on non-homogeneous spaces plays important roles in solving the Painlevé problem as well as the Vitushkin conjecture [18, 19]. For motives of developing analysis on non-homogeneous spaces and more examples, one could see [20].

Now we give the definition of the generalized Morrey space over (X,ρ,μ), which is a generalization of the classical Morrey space. Here we remark that Morrey spaces play important roles in the study of partial differential equations.

Definition 1.3 Let 1p< and a function ϕ:(0,)(0,) be such that r 1 p ϕ(r) is non-decreasing. The generalized Morrey space L p , ϕ (X,k,μ) over X, where k> a 1 , is defined as

L p , ϕ (X,k,μ):= { f L loc p ( μ ) : f L p , ϕ ( X , k , μ ) < }

with the norm f L p , ϕ ( X , k , μ ) given by

f L p , ϕ ( X , k , μ ) := sup B B ( μ ) 1 ϕ ( μ ( k B ) ) ( 1 μ ( k B ) B | f ( x ) | p d μ ( x ) ) 1 p ,

where kB is the ball with the same center and k times radius of the ball B.

In case ϕ(r)= r 1 q , 1p<q<, the space L p , ϕ (X,k,μ) becomes the classical Morrey space L p , q (X,k,μ) over X. Particularly, L p , p (X,k,μ)= L p (X,μ).

Remark 1.4 It is worth to point out that if k 1 , k 2 > a 1 , then L p , ϕ (X, k 1 ,μ) and L p , ϕ (X, k 2 ,μ) coincide as a set and their norms are mutually equivalent. This can be observed by the same arguments used in [4]. For the sake of convenience, we provide the detail. Let a 1 < k 1 k 2 . Then the inclusion L p , ϕ (X, k 1 ,μ) L p , ϕ (X, k 2 ,μ) is obvious by that fact that r 1 p ϕ(r) is non-decreasing. To see the reverse inclusion, let f L p , ϕ (X, k 2 ,μ) and B(x,r)B(μ) be fixed. It is sufficient to estimate

I= 1 ϕ ( μ ( B ( x , k 1 r ) ) ) ( 1 μ ( B ( x , k 1 r ) ) B ( x , r ) | f ( x ) | p d μ ( x ) ) 1 p .

The geometrically doubling condition shows that the ball B(x,r) can be covered by at most N= N 0 δ n balls B( x i ,δr) with x i B(x,r) for any δ(0,1). Moreover, by the quasi-triangle inequality (1.1), we can see that B( x i , k 2 δr)B(x, k 1 r) if we choose 0<δ<( k 1 a 1 )/( a 1 k 2 ). Thus,

I p i = 1 N 1 ϕ ( μ ( B ( x , k 1 r ) ) ) p μ ( B ( x , k 1 r ) ) B ( x i , δ r ) | f ( x ) | p d μ ( x ) i : B ( x i , δ r ) B ( μ ) 1 ϕ ( μ ( B ( x i , k 2 δ r ) ) ) p μ ( B ( x i , k 2 δ r ) ) B ( x i , δ r ) | f ( x ) | p d μ ( x ) N ( f L p , ϕ ( X , k 2 , μ ) ) p ,

which implies that L p , ϕ (X, k 1 ,μ)= L p , ϕ (X, k 2 ,μ) for any k 1 , k 2 > a 1 . With this fact in mind, we sometimes omit parameter k in L p , ϕ (X,k,μ), i.e., write it by L p , ϕ (X,μ).

In this article, we consider the multilinear fractional integral operator, the multilinear Calderón-Zygmund operator and the multi-sublinear maximal operator. The multilinear fractional integral is defined by

I α , m ( f 1 ,, f m )(x)= X m f 1 ( y 1 ) f m ( y m ) ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α dμ( y 1 )dμ( y m ),

where 0<α<m. When m=1, we denote I α , m by I α .

Let be a multilinear operator initially defined on the m-fold product of Schwartz spaces and taking values into the space of tempered distributions. Following [6], we say that is an m-linear Calderón-Zygmund operator if it extends to a bounded multilinear operator from L p 1 (X,μ)× L p 2 (X,μ)×× L p m (X,μ) to L p (X,μ) for some 1 p 1 ,, p m < and 1 p = 1 p 1 + 1 p 2 ++ 1 p m , and if there exists a kernel function , the so-called multilinear Calderón-Zygmund kernel, defined away from the diagonal x= y 1 == y m in X m + 1 , satisfying

T( f 1 ,, f m )(x)= X m K(x, y 1 ,, y m ) f 1 ( y 1 ) f m ( y m )dμ( y 1 )dμ( y m )

for all x i = 1 m supp f i , where f i ’s are smooth functions with compact support; and the kernel function satisfies the size condition

| K ( x , y 1 , y 2 , , y m ) | C ( i = 1 m ρ ( x , y i ) ) m
(1.3)

and some smoothness conditions; see [6, 16] for details. In fact, as for the m-linear Calderón-Zygmund operator , we assume that, by a similar argument as that in [6, 16] for the case X= R n , if 1 p = 1 p 1 + 1 p 2 ++ 1 p m , then the m-linear Calderón-Zygmund operator satisfies

T: L p 1 (X,μ)× L p 2 (X,μ)×× L p m (X,μ) L p (X,μ)

for any 1< p 1 , p 2 ,, p m <.

We will also consider the multi-sublinear maximal operator M κ , for κ> a 1 2 , defined by

M κ ( f 1 ,, f m )(x)= sup x B B ( μ ) i = 1 m 1 μ ( κ B ) B | f i ( y i ) | dμ( y i ).

In case m=1, we denote it by M κ .

The main result of this paper can be stated as follows.

Theorem 1.5 Let 0<α<m and 1< p i <, and let 1 q = 1 p 1 ++ 1 p m α>0. For each i=1,,m, let ϕ i :(0,)(0,) satisfy

1 C 1 ϕ i ( t ) ϕ i ( r ) C 1 if 1 t r 2,
(1.4)

and

r t α / m 1 ϕ i (t)dt C 2 r α / m ϕ i (r)
(1.5)

with positive constants C 1 and C 2 independent of r>0. Then there exists a constant C independent of any admissible f i such that

I α , m ( f 1 , , f m ) L q , ψ ( X , μ ) C i = 1 m f i L p i , ϕ i ( X , μ ) ,

where ψ(t)= t α ϕ 1 (t) ϕ 2 (t) ϕ m (t).

If we take ϕ i (t)= t 1 l i and 0< l i < m α , then ϕ i satisfies conditions (1.4) and (1.5). We remark that if condition (1.4) is replaced by

ϕ i (u) C 3 ϕ i (v)for uv
(1.6)

with the constant C 3 >0, then the theorem is also valid. This can be seen from the proof of the theorem in the next section. Theorem 1.5 yields the following corollary.

Corollary 1.6 Let 0<α<m and 1< p i <, and let 1 q = 1 p 1 ++ 1 p m α>0. Let 0< l i < m α and 1 h = 1 l 1 ++ 1 l m α. Then there exists a constant C independent of f i such that

I α , m ( f 1 , , f m ) L q , h ( X , μ ) C i = 1 m f i L p i , l i ( X , μ ) .

Theorem 1.7 Let 1< p i < and 1 p = 1 p 1 ++ 1 p m <1. If the functions ϕ i :(0,)(0,) satisfy condition (1.4) or (1.6), and satisfy

r ϕ i ( t ) p i p d t t C 4 ϕ i ( r ) p i p
(1.7)

with the constant C 4 independent of r>0, then there exists a constant C independent of any admissible f i such that

T ( f 1 , , f m ) L p , ϕ ( X , μ ) C i = 1 m f i L p i , ϕ i ( X , μ ) ,
(1.8)

where ϕ(t)= ϕ 1 (t) ϕ 2 (t) ϕ m (t).

Here we point out that if each f i L p i (X,μ) L p i , ϕ i (X,μ), then the multilinear Calderón-Zygmund operator T( f 1 ,, f m ) is well defined, and we will prove estimate (1.8) with the absolute constant C independent of these admissible functions. More remarks on the admissibility for f i L p i , ϕ i (X,μ) will be given in Remark 3.1 in Section 3.

Observe that ϕ i (t)= t 1 l i , for any 0< l i <, satisfies the conditions in the theorem, thus the corollary follows.

Corollary 1.8 Let 1< p i < and 1 p = 1 p 1 ++ 1 p m <1. Let 0< l i < and 1 l = 1 l 1 ++ 1 l m . Then there exists a constant C independent of f i such that

T ( f 1 , , f m ) L p , l ( X , μ ) C i = 1 m f i L p i , l i ( X , μ ) .

Theorem 1.9 Assume that M κ is a multi-sublinear maximal operator. Let 1< p i <, 1 p = 1 p 1 ++ 1 p m <1, and ϕ i satisfy condition (1.6). Then there exists a constant C independent of any admissible f i such that

M κ ( f 1 , , f m ) L p , ϕ ( X , μ ) C i = 1 m f i L p i , ϕ i ( X , μ ) ,

where ϕ(t)= ϕ 1 (t) ϕ m (t).

We notice that the results above are new even for the case of Euclidean spaces. Throughout this paper, the letter C always denotes a positive constant that may vary at each occurrence but is independent of the essential variable.

2 Proof of Theorem 1.5

Let us first give some requisite theorems and lemmas.

Theorem 2.1 [21]

Let 0<α<1, 1<p< 1 α and 1 q = 1 p α, then the operator I α is bounded from L p (X,μ) into L q (X,μ) if and only if μ(B(x,r))Cr, where the constant C is independent of x and r.

Lemma 2.2 [13]

Suppose that μ is a Borel measure on X with the growth condition (1.2). Let 1 q = 1 p 1 ++ 1 p m α>0 with 0<α<m and 1 p j . Then

  1. (a)

    if each p j >1,

    I α , m ( f 1 , , f m ) L q ( X , μ ) C j = 1 m f j L p j ( X , μ ) ;
  2. (b)

    if p j =1 for some j,

    I α , m ( f 1 , , f m ) L q , ( X , μ ) C j = 1 m f j L p j ( X , μ ) .

Proof This lemma can follow the same argument that, for the classical setting, was given by Kenig and Stein [5]. We may assume that all 1 p i <. One can find 0< α i <1/ p i such that α= i = 1 m α i . Set 1/ q i =1/ p i α i , since 1/q= i = 1 m 1/ q i , 0< α i 1, 1< q i <, and

ρ ( x , y 1 ) 1 α 1 ρ ( x , y 2 ) 1 α 2 ρ ( x , y m ) 1 α m ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α .

It follows that

I α , m ( f 1 ,, f m )(x) i = 1 m I α i ( f i )(x).

Then, by the Hölder inequality and Theorem 2.1, we obtain the lemma. In fact, one could also get the lemma from [13] (or Remark 1.3, p.290 in [13]). □

Now we give the proof of Theorem 1.5.

Proof of Theorem 1.5 Let B=B( x 0 ,r) be the ball in BB(μ), with center x 0 X and radius r>0, and let B =B( x 0 ,2 a 1 r). For f i L p i , ϕ i (X,μ), we split it as f i = f i 0 + f i , where f i 0 = f i χ B for i=1,,m. Using this decomposition, we get

| I α , m ( f 1 , , f m ) ( x ) | | I α , m ( f 1 0 , , f m 0 ) ( x ) | + | I α , m ( f 1 τ 1 , , f m τ m ) ( x ) | ,

where each term in ∑ contains at least one τ i =.

Then it suffices to show

1 ψ ( μ ( k B ) ) ( 1 μ ( k B ) B | I α , m ( f 1 τ 1 , , f m τ m ) | q d μ ) 1 q C i = 1 m f i L p i , ϕ i ( X , μ )
(2.1)

for some k> a 1 and for each τ i {0,}.

Let us first estimate for the case τ 1 == τ m =0. From the definition of L p i , ϕ i (X,μ) we have

( B | f i ( x ) | p i d μ ( x ) ) 1 p i C f i L p i , ϕ i ( X , μ ) ϕ i ( μ ( k B ) ) μ ( k B ) 1 p i .
(2.2)

From this and by the L p 1 (X,μ)×× L p m (X,μ) L q (X,μ) boundedness of I α , m , Lemma 2.2, we have

( 1 μ ( k B ) B | I α , m ( f 1 0 , , f m 0 ) ( x ) | q d μ ( x ) ) 1 q C μ ( k B ) 1 q i = 1 m f i 0 L p i ( X , μ ) C μ ( k B ) α ϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) C ψ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) ,

which implies that in the case all τ i =0, inequality (2.1) holds.

To estimate (2.1) for the case τ 1 == τ m =, let xB, then

| I α , m ( f 1 , , f m ) ( x ) | ( X B ) m | f 1 ( y 1 ) f m ( y m ) | d μ ( y 1 ) d μ ( y m ) ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α .

Note, for xB and y i X B , we get by (1.1) that

2 a 1 r<ρ( x 0 , y i ) a 1 ( ρ ( x 0 , x ) + ρ ( x , y i ) ) a 1 ( r + ρ ( x , y i ) ) ,

hence ρ(x, y i )r. This and condition (1.2) of the measure μ imply that

ρ(x, y i )r ( 2 a 1 C 0 k ) 1 μ ( k B ) := r

and so

( X B ) m i = 1 m { y i : ρ ( x , y i ) r } { ( y 1 , y 2 , , y m ) : i = 1 m ρ ( x , y i ) r } .

Hence we can derive that

| I α , m ( f 1 , , f m ) ( x ) | i = 1 m ρ ( x , y i ) r | f 1 ( y 1 ) f m ( y m ) | d μ ( y 1 ) d μ ( y m ) ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α = j = 0 2 j r i = 1 m ρ ( x , y i ) < 2 j + 1 r | f 1 ( y 1 ) f m ( y m ) | d μ ( y 1 ) d μ ( y m ) ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α j = 0 1 ( 2 j r ) m α i = 1 m ρ ( x , y i ) < 2 j + 1 r | f i ( y i ) | d μ ( y i ) .

Using the Hölder inequality and the inequality similar to (2.2), we can see that the inequality above can be controlled by

C j = 0 1 ( 2 j r ) m α i = 1 m ( B ( x , 2 j + 1 r ) | f i ( y i ) | p i d μ ( y i ) ) 1 p i ( μ ( B ( x , 2 j + 1 r ) ) ) 1 1 p i C j = 0 1 ( 2 j r ) m α i = 1 m ϕ i ( μ ( B ( x , k 2 j + 1 r ) ) ) μ ( B ( x , k 2 j + 1 r ) ) f i L p i , ϕ i ( X , μ ) C j = 0 1 ( 2 j r ) m α i = 1 m ϕ i ( 2 j μ ( k B ) ) 2 j μ ( k B ) f i L p i , ϕ i ( X , μ ) C i = 1 m [ j = 0 ( 2 j μ ( k B ) ) α / m ϕ i ( 2 j μ ( k B ) ) ] f i L p i , ϕ i ( X , μ ) ,

where, in the second inequality, we have utilized the non-decreasing of function r 1 p i ϕ i (r) and the fact μ(B(x,k 2 j + 1 r )) C 0 k 2 j + 1 r 2 j μ(k B ). Recall conditions (1.4) (or (1.6)) and (1.5) for the function ϕ i , one sees that

j = 0 ( 2 j μ ( k B ) ) α / m ϕ i ( 2 j μ ( k B ) ) C j = 0 2 j μ ( k B ) 2 j + 1 μ ( k B ) t α / m 1 ϕ i ( t ) d t C μ ( B ) t α / m 1 ϕ i ( t ) d t C μ ( k B ) α / m ϕ i ( μ ( k B ) ) .

Hence we obtain the pointwise estimate

| I α , m ( f 1 , , f m ) ( x ) | Cψ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ )

for xB, which follows from inequality (2.1) for the case all τ i =.

It is left to consider the case τ i 1 == τ i l =0 for some { i 1 ,, i l }{1,,m} and 1l<m. For this case, we can write for xB that

| I α , m ( f 1 τ 1 , , f m τ m ) ( x ) | X m | f 1 ( y 1 ) f m ( y m ) | d μ ( y 1 ) d μ ( y m ) ( ρ ( x , y 1 ) + + ρ ( x , y m ) ) m α ( B ) l i { i 1 , , i l } | f i ( y i ) | d μ ( y i ) ( X B ) m l i { i 1 , , i l } | f i ( y i ) | d μ ( y i ) ( i { i 1 , , i l } ρ ( x , y i ) ) m α : = A 1 ( x ) A 2 ( x ) .

To estimate A 1 (x), we use the Hölder inequality to give that, for any xB,

A 1 ( x ) = i { i 1 , , i l } B | f i ( y i ) | d μ ( y i ) C i { i 1 , , i l } ( B | f i | p i d μ ( y i ) ) 1 p i μ ( B ) 1 1 p i C μ ( k B ) l i { i 1 , , i l } ( ϕ i ( μ ( k B ) ) f i L p i , ϕ i ( X , μ ) ) .

Estimating A 2 (x), by the same idea used for the case all τ i = above, we get for any xB that

A 2 ( x ) j = 0 1 ( 2 j r ) m α i { i 1 , , i l } B ( x , 2 j + 1 r ) | f i ( y i ) | d μ ( y i ) C j = 0 1 ( 2 j r ) m α i { i 1 , , i l } ϕ i ( 2 j μ ( k B ) ) 2 j μ ( k B ) f i L p i , ϕ i ( X , μ ) C j = 0 1 ( 2 j μ ( k B ) ) l α l / m i { i 1 , , i l } ϕ i ( 2 j μ ( k B ) ) ( 2 j μ ( k B ) ) α / m f i L p i , ϕ i ( X , μ ) .

Noting llα/m>0 and using condition (1.5), we have

A 2 ( x ) C ( μ ( k B ) ) α l / m l i { i 1 , , i l } ϕ i ( μ ( k B ) ) μ ( k B ) α / m f i L p i , ϕ i ( X , μ ) C ( μ ( k B ) ) α l i { i 1 , , i l } ϕ i ( μ ( k B ) ) f i L p i , ϕ i ( X , μ ) .

Therefore, for xB, we have

| I α , m ( f 1 τ 1 , , f m τ m ) ( x ) | A 1 ( x ) A 2 ( x ) C μ ( k B ) α i = 1 m ϕ i ( μ ( k B ) ) f i L p i , ϕ i ( X , μ ) C ψ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .

Hence we obtain the desired inequality (2.1) for any cases. The proof of the theorem is complete. □

3 Proof of Theorems 1.7 and 1.9

In this section we first investigate the boundedness of the m-linear Calderón-Zygmund operator on the product of spaces L p i , ϕ i (X,μ) for i=1,2,,m.

Proof of Theorem 1.7 We also let B=B( x 0 ,r) be the ball in B(μ), with center x 0 X and radius r>0, and let B =B( x 0 ,2 a 1 r). For the admissible f i L p i , ϕ i (X,μ), without loss of generality, we may initially assume that f i are all smooth boundedly supported functions, which are dense in L p i (X,μ), and let f i L p i (X,μ) L p i , ϕ i (X,μ), then T( f 1 ,, f m ) is a well-defined function belonging to L p (X,μ). If we split each f i as f i = f i 0 + f i , where f i 0 = f i χ B for i=1,,m, and utilize the multi-linearity of , we have the following decomposition,

| T ( f 1 , , f m ) ( x ) | | T ( f 1 0 , , f m 0 ) ( x ) | + | T ( f 1 τ 1 , , f m τ m ) ( x ) | ,

where each term in ∑ contains at least one τ i =.

Noting that is bounded from L p 1 (X,μ)×× L p m (X,μ) L p (X,μ), we have

( 1 μ ( k B ) B | T ( f 1 0 , , f m 0 ) ( x ) | p d μ ( x ) ) 1 p C μ ( k B ) 1 p i = 1 m f i 0 L p i ( X , μ ) C ϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .
(3.1)

For the case τ 1 == τ m =, we note that for xB and y i X B , one can deduce from the properties of the quasi-metric ρ that

1 2 a 1 ρ( x 0 , y i )ρ(x, y i ) ( a 0 2 + a 1 ) ρ( x 0 , y i ).

Thus we can observe that

1 ( i = 1 m ρ ( x , y i ) ) m 1 ( i = 1 m ρ ( x 0 , y i ) ) m =m ρ ( x 0 , y 1 ) + + ρ ( x 0 , y m ) d l l m + 1 .

This, together with the Fubini theorem, we have, for xB,

| T ( f 1 , , f m ) ( x ) | ( X B ) m i = 1 m | f i ( y i ) | d μ ( y i ) ( i = 1 m ρ ( x , y i ) ) m C i = 1 m ρ ( x 0 , y i ) 2 a 1 r ( ρ ( x 0 , y 1 ) + + ρ ( x 0 , y m ) d l l m + 1 ) i = 1 m | f i ( y i ) | d μ ( y i ) C 2 a 1 r 1 l m + 1 ( i = 1 m ρ ( x 0 , y i ) < l i = 1 m | f i ( y i ) | d μ ( y i ) ) d l C 2 a 1 r 1 l m + 1 ( i = 1 m ρ ( x 0 , y i ) < l | f i ( y i ) | d μ ( y i ) ) d l .

Noting μ(k B ) C 0 2k a 1 r and applying the Hölder inequality, we see that the inequality above is bounded by

C μ ( k B ) / C 0 k 1 l m + 1 i = 1 m ( B ( x 0 , l ) | f i ( y i ) | p i d μ ( y i ) ) 1 p i μ ( B ( x 0 , l ) ) 1 1 p i d l C μ ( k B ) / C 0 k 1 l m + 1 i = 1 m ( f i L p i , ϕ i ( X , μ ) ϕ i ( μ ( k B ( x 0 , l ) ) ) μ ( k B ( x 0 , l ) ) ) d l

which, by using the non-decreasing of function r ϕ i (r), is controlled by

C μ ( k B ) ( i = 1 m ϕ i ( l ) ) d l l i = 1 m f i L p i , ϕ i ( X , μ ) C ( i = 1 m μ ( k B ) ϕ i ( l ) p i p d l l ) p p i i = 1 m f i L p i , ϕ i ( X , μ ) C ϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .

Therefore, we get for xB that

| T ( f 1 , , f m ) ( x ) | Cϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .
(3.2)

It is left to consider the case that there is 1l<m and { i 1 ,, i l }{1,,m} such that τ i =0 if i{ i 1 ,, i l }, and τ i = if i{ i 1 ,, i l }. For xB, we can write that

| T ( f 1 τ 1 , , f m τ m ) ( x ) | ( B ) l i { i 1 , , i l } | f i ( y i ) | d μ ( y i ) ( X B ) m l i { i 1 , , i l } | f i ( y i ) | d μ ( y i ) ( i { i 1 , , i l } ρ ( x , y i ) ) m : = E 1 ( x ) E 2 ( x ) .

With the same argument as A 1 (x) we have

E 1 (x)Cμ ( k B ) l i { i 1 , , i l } ϕ i ( μ ( k B ) ) f i L p i , ϕ i ( X , μ ) .

Using a similar argument as that for the estimate of T( f 1 ,, f m )(x), we can deduce that

E 2 ( x ) C μ ( k B ) ( i { i 1 , , i l } ϕ i ( t ) ) d t t l + 1 i { i 1 , , i l } f i L p i , ϕ i ( X , μ ) C μ ( k B ) l [ i { i 1 , , i l } ( μ ( k B ) ϕ i ( t ) p i p d t t ) p p i ] i { i 1 , , i l } f i L p i , ϕ i ( X , μ ) C μ ( k B ) l [ i { i 1 , , i l } ϕ i ( μ ( k B ) ) ] i { i 1 , , i l } f i L p i , ϕ i ( X , μ ) .

Hence we obtain that

| T ( f 1 τ 1 , , f m τ m ) ( x ) | E 1 (x) E 2 (x)Cϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .
(3.3)

Therefore, combining inequalities (3.1), (3.2) and (3.3), we have

( 1 μ ( k B ) B | T ( f 1 , , f m ) ( x ) | p d μ ( x ) ) 1 p Cϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) ,

which completes the proof of Theorem 1.7. □

Remark 3.1 We have actually proved Theorem 1.7 in the case f i L p i (X,μ) L p i , ϕ i (X,μ). Here we need give some remarks about the definition and boundedness of T( f 1 ,, f m ) with f i L p i , ϕ i (X,μ) for i=1,2,,m. Fix any x 0 X and R>0, and use the same notations f i τ i = f i χ B ( x 0 , 2 a 1 R ) if τ i =0, and f i τ i = f i f i 0 if τ i =. Using a similar argument as (3.2) and (3.3), we have, if some τ i =,

X m | K ( x , y 1 , , y m ) f 1 τ 1 ( y 1 ) f m τ m ( y m ) | d μ ( y 1 ) d μ ( y m ) C ϕ ( μ ( B ( x 0 , 3 a 1 2 R ) ) ) i = 1 m f i L p i , ϕ i ( X , μ )

with the constant C independent of R, for all f i L p i , ϕ i (X,μ), i=1,,m, and xB( x 0 ,R)X.

In view of this fact, and if lim R ϕ(μ(B( x 0 ,3 a 1 2 R)))=0, then we can extend the definition of for f i L p i , ϕ i (X,μ) by

T ( f 1 τ 1 , , f m τ m ) ( x ) = lim R ( T ( f 1 0 , , f m 0 ) ( x ) + some τ i = X m | K ( x , y 1 , , y m ) f 1 τ 1 ( y 1 ) f m τ m ( y m ) | d μ ( y 1 ) d μ ( y m ) ) .

By the definition, it is easy to see that the following properties hold.

  1. (1)

    If ρ( x 0 ,x) R 0 , then the terms in the brackets on the right-hand side of the equation above do not depend on R as long as R> R 0 .

  2. (2)

    Suppose that 1< p 1 ,, p m <, and if f i L p i (X,μ) L p i , ϕ i (X,μ), then the definitions of T( f 1 ,, f m ) for f i L p i (X,μ) and for f i L p i , ϕ i (X,μ) coincide.

  3. (3)

    Theorem 1.7 holds for any admissible f i L p i , ϕ i (X,μ), i=1,,m.

Finally, we consider the multi-sublinear maximal function M κ ( f 1 ,, f m )(x), which is strictly smaller than the m-fold produce of the maximal function M κ ( f i )(x). Hence we have the following lemma.

Lemma 3.2 If κ> a 1 2 and p, p i >1, and 1 p = 1 p 1 ++ 1 p m , then there exists a constant C independent of f i such that

M κ ( f 1 , , f m ) L p ( X , μ ) C i = 1 m f i L p i ( X , μ ) .

Proof of Theorem 1.9 With the same notions, we decompose each f i L p i , ϕ i (X,μ) according to the ball B :=B( x 0 , a 1 (1+λ)r) as f i = f i 0 + f i , where λ is a large positive constant that will be determined later. We have

| M κ ( f 1 , , f m ) ( x ) | | M κ ( f 1 0 , , f m 0 ) ( x ) | + | M κ ( f 1 τ 1 , , f m τ m ) ( x ) | ,

where each term in ∑ contains at least one τ i 0.

It follows from Lemma 3.2 that for any k> a 1 and κ> a 1 2 ,

( 1 μ ( k B ) B ( x 0 , r ) | M κ ( f 1 0 , , f m 0 ) ( x ) | p d μ ( x ) ) 1 p C ϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .

It is left to study the case τ i 1 == τ i l =0 and τ i l + 1 == τ i m = for some 1l<m. Hence for xB( x 0 ,r) we have

M κ ( f 1 τ 1 , , f m τ m ) ( x ) = sup x D B ( μ ) i = 1 m 1 μ ( κ D ) D | f i τ i ( y i ) | d μ ( y i ) sup x D B ( μ ) i { i 1 , , i l } 1 μ ( κ D ) D | f i 0 ( y i ) | d μ ( y i ) i { i 1 , , i l } 1 μ ( κ D ) D | f i ( y i ) | d μ ( y i ) .

Let r D be the radius of the ball D and c D be the center of D. We note that on the right-hand side of the inequality above, the balls D in the integrals must satisfy that xDB( x 0 ,r) and some y i m D(X B ), which implies

a 1 ρ ( x , y i m ) ρ ( x 0 , y i m ) a 1 ρ ( x 0 , x ) a 1 λ r , ρ ( x , y i m ) a 1 a 0 ρ ( c D , x ) + a 1 ρ ( c D , y i m ) a 1 ( 1 + a 0 ) r D .

Further, a simple calculus yields

B:=B( x 0 ,r) ( a 1 + a 1 3 ( 1 + a 0 ) 2 λ 1 ) D κ + a 1 2 2 a 1 D

as long as we take λ big enough, because of κ> a 1 2 . Thus,

M κ ( f 1 τ 1 , , f m τ m ) (x) sup B D B ( μ ) i = 1 m 1 μ ( 2 a 1 κ κ + a 1 2 D ) D | f i τ i ( y i ) | dμ( y i ).

If let k=2 a 1 κ/(κ+ a 1 2 ), then k> a 1 , and we can get from the Hölder inequality and condition (1.6) on ϕ i that

M κ ( f 1 τ 1 , , f m τ m ) ( x ) sup B D B ( μ ) i = 1 m 1 μ ( k D ) D | f i τ i ( y i ) | d μ ( y i ) C sup B D B ( μ ) i = 1 m f i L p i , ϕ i ( X , μ ) ϕ i ( μ ( k D ) ) C ϕ ( μ ( k B ) ) i = 1 m f i L p i , ϕ i ( X , μ ) .

The theorem is proved. □