A LOCAL MEAN OSCILLATION DECOMPOSITION AND SOME ITS APPLICATIONS


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1 A LOCAL MEAN OSCILLATION DECOMPOSITION AND SOME ITS APPLICATIONS ANDREI K. LERNER 1. Introduction A recent result by the author [39] establishes a pointwise control of an arbitrary measurable function in terms of its local mean oscillations. Soon after that, in a surprising work [12], D. CruzUribe, J. Martell and C. Pérez showed that this result can be effectively applied in a variety of questions, including sharp weighted inequalities for classical singular integrals and the dyadic square function. In turn, based on [12] and on a recent concept of the intrinsic square function by M. Wilson [54], the author [40] obtained sharp weighted estimates for essentially any LittlewoodPaley operator. The aim of these notes is to present a unified, extended and almost selfcontained exposition of the abovementioned works [39, 12, 40]. 2. The space BMO 2.1. The classical approach to BMO. The mean oscillation of a locally integrable function f over a cube R n is defined by Ωf; ) = 1 fx) f dx, where f = 1 f. It is easy to see that 1 1 inf fx) c dx Ωf; ) 2 inf fx) c dx. c R c R The space of functions with bounded mean oscillation, BMOR n ), consists of all f L 1 loc Rn ) such that f BMO sup R n Ωf; ) <. This space was introduced by F. John and L. Nirenberg in [30]. In the same work the following fundamental property of BM Ofunctions was 2000 Mathematics Subect Classification. 42B20,42B25,46E30. 1
2 2 ANDREI K. LERNER established: for any f BMO, any cube R n, and for all α > 0, α ) 2.1) {x : fx) f > α} 2 exp. c n f BMO For example, it follows from this inequality that 1 2.2) f BMO sup fx) f p dx for any p 1. The sharp maximal function is defined by f # x) = sup Ωf; ), x ) 1/p where the supremum is taken over all cubes containing the point x. This operator was introduced by C. Fefferman and E.M. Stein [20]. Recall that the HardyLittlewood maximal operator is defined by 1 Mfx) = sup x fy) dy. Since f # x) 2Mfx), we have that f # is bounded on L p for p > 1. The basic property of f # proved in [20] says that the converse inequality is also true, namely if f L p 0, then 2.3) f L p c f # L p 1 < p < ). As we shall see below, the assumption that f L p 0 can be relaxed until f + ) = 0. Originally, inequality 2.3) was applied to describing the intermediate spaces between BMO and L p. A number of other applications of 2.3) concerns L p norm inequalities involving various operators in harmonic analysis see D. Kurtz [31]). Typically, one can obtain a pointwise estimate T 1 f) # x) ct 2 fx), where T 1 is a certain singulartype operator, and T 2 is a maximaltype operator. Combining this with 2.3) yields a norm estimate of T 1 by T 2. Perhaps the first such application was found by A. Cordoba and C. Fefferman in [10] where it was shown that for a singular integral T, 2.4) T f) # x) cm f r )x) 1/r r > 1) Median values and local mean oscillations. Given a measurable function f, its nonincreasing rearrangement is defined by f t) = inf{α > 0 : {x R n : fx) > α} < t} 0 < t < ).
3 LOCAL MEAN OSCILLATION DECOMPOSITION 3 Observe that we have defined the rearrangement as the leftcontinuous function. Usually in the literature see, e.g., [1, p. 39]) one can find the rightcontinuous rearrangement defined by inf{α > 0 : {x R n : fx) > α} t}. The leftcontinuous rearrangement can be also defined in the following very convenient form cf. [5]): f t) = sup inf fx). x E E =t Definition 2.1. By a median value of f over we mean a possibly nonunique, real number m f ) such that {x : fx) > m f )} /2 and {x : fx) < m f )} /2. If follows from this definition that which implies {x : fx) m f ) } /2, m f ) fχ ) /2). Also, if m f ) is a median value of f, then for any constant c, m f ) c is a median value of f c. Hence, applying the previous inequality, we get 2.5) m f ) c f c)χ ) /2 ). Definition 2.2. Given a measurable function f on R n and a cube, the local mean oscillation of f over is defined by ω λ f; ) = ) ) f m f ))χ λ 0 < λ < 1). It follows from 2.5) that for 0 < λ 1/2, ) ) ) ) inf f c)χ λ ωλ f; ) 2 inf f c)χ λ. c R c R Therefore, the median value m f ) plays the same role for the local mean oscillation in the case 0 < λ 1/2) as the usual integral mean value f does for the integral mean oscillation.
4 4 ANDREI K. LERNER 2.3. A local mean oscillation approach to BMO. By Chebyshev s inequality, f t) 1 f t L1, and hence, which shows that ω λ f; ) 2 Ωf; ), λ sup ω λ f; ) 2 λ f BMO. The main result about local mean oscillations obtained by F. John [29] says that for λ < 1/2 the converse inequality holds: 2.6) f BMO c sup ω λ f; ). This result was rediscovered by J.O. Strömberg [51] who showed also that 2.6) remains true for λ = 1/2. Note that this exponent is sharp. Indeed, if λ > 1/2, then ω λ f; ) = 0 for any function f taking only two values, and therefore 2.6) fails. Observe that 2.6) allows to recover BMO under the minimal assumptions on f. In particular, in the definition of ω λ f; ) we suppose only that f is merely measurable. Note also that 2.6) shows that 2.2) holds for any p > 0. Denote f BMOλ = sup ω λ f; ). By the above discussion we have the JohnStrömberg equivalence f BMO f BMOλ 0 < λ 1/2). The proof of this result is based on the following version of the John Nirenberg inequality 2.1): α ) 2.7) {x : fx) m f ) > α} 2 exp. c n f BMOλ It is easy to see that actually 2.7) implies the JohnNirenberg inequality. Indeed, by 2.5) and by Chebyshev s inequality, m f ) f 2Ωf; ) 2 f BMO. Hence, if α > 4 f BMO, we get from 2.7) that {x : fx) f > α} {x : fx) m f ) > α/2} α ) 2 exp. c n f BMO On the other hand, for α 4 f BMO this inequality holds trivially with suitable c n.
5 LOCAL MEAN OSCILLATION DECOMPOSITION 5 An interesting analysis of the JohnNirenberg and JohnStrömberg inequalities and in particular, an attempt to obtain 2.7) with dimension free constants) can be found in a recent work [14] by M. Cwikel, Y. Sagher and P. Shvartsman. Similarly to the FeffermanStein sharp function, one can define the local sharp maximal function by M # λ fx) = sup ω λ f; ). x It was shown by J.O. Strömberg [51] that for any p > 0, 2.8) f L p c M # λ f Lp 0 < λ 1/2). As we shall see below Corollary 4.2), it is enough to assume here that f + ) = 0. On one hand it seems that 2.8) is an improvement of the Fefferman Stein inequality 2.3) since we easily have that M # λ fx) 2 f # x). On λ the other hand, B. Jawerth and A. Torchinsky [28] showed that f # is essentially the HardyLittlewood maximal function of M # λ f: for any x R n, 2.9) c 1 MM # λ fx) f # x) c 2 MM # λ fx) this result with λ = 1/2 one can find in [34]). It follows from this that inequalities 2.3) and 2.8) are equivalent for p > 1. Inequalities 2.9) show that the local sharp maximal function M # λ f is much smaller than f #. This advantage is invisible in the unweighted L p spaces. However, as soon as the weighted inequalities are concerned, the use of M # λ f usually leads to much more precise results. As a typical example, consider Coifman s inequality [6] saying that if w A, then a singular integral operator T satisfies 2.10) T f L p w) c Mf L p w) 0 < p < ). It is well known that both inequalities 2.3) and 2.8) hold if we replace the L p norm by the L p w)norm for w A we shall prove this fact in Theorem 4.6 below). Further, it was shown in [28] that 2.11) M # λ T f)x) cmfx). Combining this with the weighted Strömberg s inequality 2.8), we immediately obtain 2.10). Next, observe that 2.11) along with 2.9) yields an improvement of 2.4): T f) # x) cmmfx).
6 6 ANDREI K. LERNER But even this improved version combined with the weighted Fefferman Stein inequality 2.3) gives only 2.10) with MMf instead of Mf on the righthand side. 3. The main decomposition result 3.1. On theorems of C. Fefferman and L. Carleson. Denote R n+1 + = R n 0, ). Given a cube R n, set = {y, t) R n+1 + : y, 0 < t < l)}, where l) denotes the side length of. We say that σ is a Carleson measure on R n+1 + if σ Cσ) sup ) R n <, where σ is the total variation of σ. Let K be a positive function with K = 1 and such that R n c Kx) 1 + x. n+1 Write K t x) = t n Kx/t), t > 0. The famous duality theorem by C. Fefferman [18, 20] says that BMOR n ) is the dual space of H 1 R n ). This result has several equivalent formulations. One of them is the following see [4] and [22, p. 272]): if f BMOR n ) with compact support, then there is g L and there is a Carleson measure σ such that 3.1) fx) = gx) + R n+1 + K t x y)dσy, t), where g L c f BMO and Cσ) c f BMO. L. Carleson [4] gave a direct and constructive proof of 3.1) providing a new proof of the H 1 BMO duality On theorems of J. Garnett and P. Jones, and N. Fuii. We say that I R is a dyadic interval if I is of the form, +1 ) for some 2 k 2 k integers and k. A dyadic cube R n is a Cartesian product of n dyadic intervals of equal lengths. Let D be the set of all dyadic cubes in R n. Given a cube 0, denote by D 0 ) the set of all dyadic cubes with respect to 0 that is, they are formed by repeated subdivision of 0 and each of its descendants into 2 n congruent subcubes). J. Garnett and P. Jones [23] obtained the following dyadic version of Carleson s theorem: given f BMO and a cube 0, there is g L
7 LOCAL MEAN OSCILLATION DECOMPOSITION 7 with g L 2 f BMO and there exists a sequence { k } D 0 ), and a sequence a k of real numbers such that for a.e. x 0, fx) f 0 = gx) + k a k χ k x) and for each D 0 ), k a k k c f BMO. If we replace R n+1 + by its discrete subset {p = c, l)), D}, where c is the center of, and consider on this subset the measure σ having mass a k k at p k, then we get a correspondence between the GarnettJones and Carleson theorems. The abovementioned results deal with decompositions of BMOfunctions. A remarkable observation of N. Fuii [21] is that almost the same proof as in [23] yields actually a decomposition of an arbitrary locally integrable function: given a cube, 3.2) fx) f = gx) + a ) ν χ ν x) for a.e. x. =1 Here gx) cf # x), where f # x) is the FeffermanStein sharp function relative to, and 3.3) a ) ν c sup Ωf; ). k 3.3. A decomposition in terms of local mean oscillations. It was mentioned by N. Fuii [21] without the proof that replacing f in 3.2) by a median value m f ), one can obtain a similar decomposition but with the local sharp maximal function instead of f # x). Indeed, following [21], we get a variant of 3.2) with a control of g by M # λ f and with 3.3) replaced by a ν ) c sup ω λ f; ). k Our key result stated below says that such a variant can be further improved with a control of a ) ν it terms of single local mean oscillations. As we shall see below, this point is crucial for many important applications. If D 0 ) and 0, we denote by its dyadic parent, that is, the unique cube from D 0 ) containing and such that = 2 n. ν
8 8 ANDREI K. LERNER For x 0 set M #,d λ; 0 fx) = sup ω λ f; ), x D 0 ) where the supremum is taken over all dyadic cubes with respect to 0 containing the point x. The following theorem was proved in [39]. Theorem 3.1. Let f be a measurable function on R n and let 0 be a fixed cube. Then there exists a possibly empty) collection of cubes k D 0 ) such that i) for a.e. x 0, fx) m f 0 ) 2M #,d 1/4; 0 fx) + 2 k=1 ω 1 2 n+2 f; k )χ k x); ii) for each fixed k the cubes k are pairwise disoint; iii) if Ω k = k, then Ω k+1 Ω k ; iv) Ω k+1 k 1 2 k. Observe that properties ii)iv) here are the same as those of cubes obtained from the classical CalderónZygmund decomposition and indeed, the cubes k in Theorem 3.1 are also obtained from a similar stoppingtime process). In particular, we shall use below the following standard trick. Let E k = k \ Ω k+1. It follows from the properties ii) iv) of Theorem 3.1 that E k k /2 and the sets E k are pairwise disoint. Proof of Theorem 3.1. We divide the proof into several parts. The 1st part. We claim that there exists a possibly empty) collection of pairwise disoint cubes { 1 } D 0 ) such that 3.4) and 3.5) f m f 0 ) = g 1 + where 3.6) g 1 x) M #,d 1/4; 0 fx) and the numbers α,1 satisfy α,1 χ 1 + f m f 1 ))χ 1, for a.e. x 0 \ 1 3.7) a,1 ω 1/2 n+1f; 1 ) + ω 1/4 f; 0 ).
9 LOCAL MEAN OSCILLATION DECOMPOSITION 9 Set f 1 x) = fx) m f 0 ) and E 1 = {x 0 : f 1 x) > ω 1/4 f; 0 )}. We may assume that E 1 > 0 since otherwise we trivially have fx) m f 0 ) ω 1/4 f; 0 ) M #,d 1/4; 0 fx) for a.e. x 0 and so the collection { 1 } is empty). Let m 0 f 1 x) = sup m f1 ), D 0 ),x and consider Ω 1 = {x 0 : m 0 f 1 x) > ω 1/4 f; 0 )}. Observe that by 2.5) and by Chebyshev s inequality m f ) fx) 2 fy) fx) dy. From this, by Lebesgue s differentiation theorem we get that for a.e. x R n, lim m f ) = fx). 0, x Hence, m 0 f 1 x) f 1 x) for a.e. x, and therefore Ω 1 E 1 > 0. For each x Ω 1 there exists a cube x D 0 ) containing x and such that m f1 x ) > ω 1/4 f; 0 ). Note that x 0 since m f1 0 ) = 0. Therefore, choosing the maximal dyadic cubes exactly as in the classical CalderónZygmund decomposition), we get that Ω 1 = 1, where 1 are pairwise disoint cubes from D 0 ) such that 3.8) m f1 1 ) > ω 1/4 f; 0 ) and It follows from 3.8) that Hence, m f1 1 ) ω 1/4 f; 0 ). f 1 χ 0 ) 0 /4) < f 1 χ 1 ) 1 /2). {x 1 : f 1 x) > f 1 χ 0 ) 0 /4)} 1 /2, and thus {x 1 : f 1 x) > f 1 χ 0 ) 0 /4)} {x 0 : f 1 x) > f 1 χ 0 ) 0 /4)} 0 /4,
10 10 ANDREI K. LERNER which proves 3.4) here we have used the well known property of the rearrangement saying that µ f f t)) t, where µ f is the distribution function of f). Further, observe that m f1 1 ) = m f 1 ) m f 0 ). Hence we can write f m f 0 ) = f 1 χ 0 \Ω 1 + m f1 1 )χ 1 + f m f 1 ))χ 1, which yields 3.5) with g 1 = f 1 χ 0 \Ω 1 and α,1 = m f1 1 ). Since m 0 f 1 x) f 1 x) a.e., we obviously have 3.6). Next, α,1 m f1 1 ) m f1 1 ) + m f1 1 ) f m f 1 ))χ 1 ) 1 /2) + ω 1/4 f; 0 ) ω 1/2 n+1f; 1 ) + ω 1/4 f; 0 ), which gives 3.7), and hence our claim is proved. The 2nd part. Observe that each function f m f 1 ) has the same behavior on 1 that f m f 0 ) has on 0. Therefore we can repeat the process for any 1, and continue by induction. Denote by k the cubes obtained at kth stage. Let Ω k = k and f i,k x) = fx) m f k 1 i ). Denote I 1,k = {i : Ω k k 1 i = } and I 2,k = {i : Ω k k 1 i }. Assume that i I 2,k. Setting we have Ω i,k = {x k 1 i J i,k = { : k k 1 i }, : m f k 1 i,k )x) > ω 1/4 f; k 1 i )} = Ji,k k, i and the numbers α i),k = m f i,k k ), similarly to 3.7), satisfy 3.9) α i),k ω 1/2 n+1f; k ) + ω 1/4 f; k 1 i ) J i,k ). Further, similarly to 3.4), 3.10) Ω k k 1 i = k 1 2 k 1 i. J i,k We write below how 3.5) will transformed after the first repetition of the above described process. Set ψ 1 = i f m f 1 i ))χ 1 i. We have ψ 1 = f m f 1 i ))χ 1 i + f m f 1 i ))χ 1 i. i I 1,2 i I 2,2
11 LOCAL MEAN OSCILLATION DECOMPOSITION 11 Next, i I 2,2 = i I 2,2 f m f 1 i ))χ 1 i \Ω i,2 + i I 2,2 f m f 1 i ))χ Ω 2 i, and we use that α i),2 = m f 2 ) m f 1 i )) f m f 1 i ))χ Ω 2 i = f m f 1 i ))χ 2 i I 2,2 i I 2,2 J i,2 =,2 χ 2 + α i) i I 2,2 J i,2 i I 2,2 J i,2 f m f 2 ))χ 2 Combining the previous equations along with 3.5), we get f m f 0 ) = g 1 + g 2 + α,1 χ 1 +,2 χ 2 + ψ 2, where and g 2 = i I 1,2 f m f 1 i ))χ 1 i + ψ 2 = i I 2,2 α i) i I 2,2 J i,2 i I 2,2 f m f 1 i ))χ 1 i \Ω i,2 J i,2 f m f 2 ))χ 2. Similarly, after k 1)th repetition of the process we obtain that k k fx) m f 0 ) = g ν + α i),ν χ νx) + ψ kx), ν=1 ν=1 J i,ν where g k = f i,k χ k 1 i i I 1,k i I 2,ν x) + f i,k χ k 1 i i I 2,k \Ω i,k x) and ψ k x) = f mf k ) ) χ k x) i I 2,k J i,k so, by our notation, i I 2,1 J i,1 α i),1 χ 1x) α,1χ 1 x)). By 3.10), Ω k Ω k 1 /2, and hence Ω k 0 /2 k. Since the support of ψ k is Ω k we obtain that ψ k 0 a.e. as k. Therefore, for a.e. x 0, fx) m f 0 ) = g ν +,ν χ νx) ν=1 S 1 x) + S 2 x). α i) ν=1 i I 2,ν J i,ν
12 12 ANDREI K. LERNER The 3rd part. It is easy to see that the supports of g ν are pairwise disoint and for any ν and for a.e. x 0, Therefore, Next, we write 3.11) S 2 x) = By 3.7), α,1 χ 1 x) g ν x) M #,d 1/4; 0 fx). S 1 x) M #,d 1/4; 0 fx) a.e. in 0. α,1 χ 1 x) + α i) ν=2 i I 2,ν J i,ν,ν χ ν x). ω 1/2 n+1f; 1 )χ 1 x) + ω 1/4 f; 0 ). Applying 3.9), we get that the second term on the righthand side of 3.11) is bounded by ω 1/2 n+1f; ) ν ) + ω 1/4 f; ν 1 i ) χ ν x) ν=2 i I 2,ν J i,ν ω 1/2 n+1f; ν )χ ν x) + ν=2 ω 1/4 f; ν 1 i ν=2 i )χ ν 1x). Combining this with the previous estimate yields S 2 x) ω1/2 n+1f; ν ) + ω 1/4 f; ν ) ) χ ν x) + ω 1/4f; 0 ) 2 ν=1 ω 1/2 n+2f; ν )χ ν x) + M # 1/4; 0 fx), ν=1 which along with the estimate for S 1 completes the proof. 4. Applications of Theorem 3.1 to M # λ f and BMO By a weight we mean a nonnegative locally integrable function. We start with the following result. Theorem 4.1. For any weight w, cube, and a measurable function f, 4.1) f m f ) wdx 6 M # λ; fx)δ M M # λ; fx)1 δ w ) x)dx, where a constant λ depends only on n, and 0 < δ 1. i
13 LOCAL MEAN OSCILLATION DECOMPOSITION 13 Proof. Applying Theorem 3.1 with = 0 yields f m f 0 ) w dx 2 M # 1/4; 0 fx)w dx ω 1 f; k 2 n+2 ) w. k, k Since we have ω 1 f; k 2 n+2 ) inf M # x k λ n; 0 fx) λ n = 1/2 n+2 ), k, 2 k, ω 1 f; k 2 n+2 ) w k k, E k M # λ n ; 0 f ) δ ) 1 k inf M # k λ n; 0 f ) w k k M # λ n ; 0 f ) 1 δ w 2 M # λ n ; 0 f ) δ M0 M # λ n ; 0 f) 1 δ w ) dx k, E k 2 M # λ n; 0 f ) δ M0 M # λ n; 0 f) 1 δ w ) dx. 0 Also, M # 1/4; 0 fx)w dx M # 1/4; 0 fx) δ M 0 M # 1/4; 0 fx) 1 δ w ) x)dx. 0 0 Combining the obtained estimates completes the proof. Theorem 4.1 implies easily both the JohnNirenbergJohnStrömberg and the FeffermanSteinStrömberg inequalities, namely, we have the following. Corollary 4.2. Let 0 < λ λ n. i) For any f BMO and any cube, α ) 4.2) {x : fx) m f ) > α} 2 exp ; c n f BMOλ ii) For any measurable f with f + ) = 0 and for all p > 0, 4.3) f L p c M # λ f L p. Proof. Theorem 4.1 with δ = 1 along with Stein s L log L characterization [50] yields f m f ) wdx 6 f BMOλ M w c f BMOλ w L log L).
14 14 ANDREI K. LERNER From this, by the expl)l log L duality [1, p. 243], f m f ) expl) c f BMOλ, which is equivalent to 4.2). Further, if f + ) = 0, then m f ) 0 when tends to R n. Hence, letting R n in Theorem 4.1 with δ = 1, we get 4.4) fx) wdx 6 M # λ fx)mwdx R n R n observe that this inequality was proved by means of different ideas in [35]). From this, using the L p boundedness of M and the L p L p duality, we get 4.3) for p > 1. The case p = 1 follows immediately if we take w 1. Further, if 0 < r < 1, we have ω λ f r ; ) 2 f r m f ) r )χ ) λ ) 2ω λ f; ) r, which implies M # λ f r )x) 2M # λ fx)r. Combining this estimate with the proved case p = 1, we obtain 4.3) for 0 < p < 1. Remark 4.3. Observe that our approach does not allow to obtain the sharp JohnStrömberg exponent λ = 1/2 in Corollary 4.2. On the other hand, from point of view of most applications, it is enough to have 4.2) and 4.3) for some λ depending on n. Remark 4.4. It follows from the definition of the rearrangement that f + ) = 0 if and only if for any α > 0 cf., [36, Prop. 2.1]). {x R n : fx) > α} < Remark 4.5. Theorem 4.1 contains also a part of JawerthTorchinsky inequality 2.9). Indeed, by 4.1) with δ = 1 and w 1, fx) f dx 2 fx) m f ) dx 12 M # λ fx)dx, which yields the righthand side of 2.9). We now extend 4.3) to the L p w)norms with w A. Recall first several definitions. We say that a weight w satisfies the A p, 1 < p <, condition if ) ) p w Ap sup w dx w 1 p 1 dx,
15 LOCAL MEAN OSCILLATION DECOMPOSITION 15 1 p< where the supremum is taken over all cubes R n. In the case p = 1 we say that w is an A 1 weight if there is a finite constant c such that Mwx) c wx) a.e. Denote A = A p. There are several equivalent characterizations of A see [7]). In particular, w A if and only if there exist constants c, ε > 0 such that for any cube R n and for any measurable subset E, ) ε we) E 4.5) w) c we use a notation we) = wx)dx). Also, the Lebesgue measure E and the wmeasure here can be reversed, namely, w A if and only if there exist constants c, δ > 0 such that for any cube R n and for any measurable subset E, ) δ E we) 4.6) c. w) Theorem 4.6. Let w A. Then for any measurable f satisfying f + ) = 0 and for all p > 0, f L p w) c M # λ f L p w) 0 < λ λ n ). Proof. As in the previous proof, it is enough to prove the theorem for p 1. Applying Theorem 3.1, we have f m f 0 ) L p 0,w) 2 M # 1/4 f L p w) + 2 ω 1 2 n+2 )χ k L p w). It suffices to show that the second term here is bounded by M # λ f L p w). Then letting 0 R n will complete the proof. Set E k = Ω k \ Ω k+1 we use the notation from Theorem 3.1). Then k=1 Therefore ω 1 2 n+2 f; k )χ k = k=1 k=1 l=0 k, ω 1 f; k 2 n+2 )χ k L p w) k, l=0 ω 1 2 n+2 f; k )χ Ek+l k ω 1 2 n+2 f; k )χ Ek+l k L p w).
16 16 ANDREI K. LERNER Further, k, ω 1 2 n+2 f; k )χ Ek+l k p L p w) = k, ω 1 2 n+2 f; k ) p we k+l k ) By properties ii)iv) of Theorem 3.1 we have E k+l k Ω k+l k 2 l k. From this and from 4.5) and 4.6), we k+l k ) c2 lε w k ) c2 lε we k ). Therefore, ω 1 f; k 2 n+2 ) p we k+l k ) c2 lε k, k, infm # k λ n f) p we k ) c2 lε M # λ n f p L p w). Combining the obtained estimates, we get ω 1 f; k 2 n+2 )χ Ek+l k L p w) c 2 lε/p M # λ n f L p w) k, l=0 l=0 which completes the proof. c M # λ n f L p w), A different proof of Theorem 4.6 can be found in [33]. 5. Applications of Theorem 3.1 to sharp weighted inequalities It is well known that most of the classical operators in harmonic analysis are bounded on L p w) for w A p. The question about the sharp L p w) operator norm of a given operator in terms of w Ap has been a subect of intense research during the last decade. The first sharp result in this direction was obtained by S. Buckley [3] who showed that the HardyLittlewood maximal operator M satisfies 5.1) M L p w) cn, p) w 1 p 1 A p 1 < p < ), 1 and the exponent is sharp for any p > 1. p 1 It turned out that for singular integrals the question is much more complicated. Very recently this problem has been solved due to efforts of many mathematicians. To be more precise, we have that any CalderónZygmund operator T satisfies 5.2) T L p w) ct, n, p) w max1, 1 p 1 ) A p 1 < p < ).
17 LOCAL MEAN OSCILLATION DECOMPOSITION 17 Further, for a large class of LittlewoodPaley operators S, 5.3) S L p w) ct, n, p) w max 1 2, 1 p 1 ) A p 1 < p < ). The exponents in 5.2) in 5.3) are best possible for any p > 1. Inequality 5.2) was first proved by S. Petermichl [45, 46] for the Hilbert and Riesz transforms and by S. Petermichl and S. Volberg [48] for the AhlforsBeurling operator. The proofs in [45, 46, 48] are based on the socalled Haar shift operators combined with the Bellman function technique. A unified approach to the above results was given by M. Lacey, S. Petermichl and M. Reguera [32], who proved 5.2) for a general class of dyadic shifts ; their proof employed a twoweight T b theorem for such shifts due to F. Nazarov, S. Treil and S. Volberg [41]. The proof in [32] was essentially simplified by D. CruzUribe, J. Martell and C. Pérez [12]; as the main tool they used Theorem 3.1. Very soon after that, C. Pérez, S. Treil and A. Volberg [43] showed that for general CalderónZygmund operators the problem is reduced to proving the corresponding weaktype estimate. Based on this work, T. Hytönen et al. [26] solved 5.2) for CalderónZygmund operators with sufficiently smooth kernels. Inequality 5.2) in full generality was proved by T. Hytönen [25] see also the subsequent work [27]). The history of 5.3) in brief is the following. First it was proved for 1 < p 2 for the dyadic square function by S. Hukovic, S. Treil and A. Volberg [24], and, independently by J. Wittwer [56]. Also, 5.3) in the case 1 < p 2 was proved by J. Wittwer [57] for the continuous square function. In [12], D. CruzUribe, J. Martell and C. Pérez proved 5.3) for the dyadic square function for any p > 1; the key tool was again Theorem 3.1. Soon after that, the author [39] showed that 5.3) holds for the intrinsic square function, establishing by this 5.3) for essentially any square function. Our goal is to describe below the key points from [12] and [39]. But first we mention the following very useful tool commonly used in these questions Extrapolation. The famous extrapolation theorem of J. Rubio de Francia [49] says that if a sublinear operator T is bounded on L p 0 w) for any w A p0, then it is bounded on L p w) for any p > 1 for all w A p. In [15], O. Dragičević et al. found the sharp dependence of the corresponding norms on w Ap in this theorem. Very recently, a different and much simplified proof of this result was given by J. Duoandikoetxea [17]. We shall use the following version from [17].
18 18 ANDREI K. LERNER Theorem 5.1. Assume that for some family of pairs of nonnegative functions f, g), for some p 0 [1, ), and for all w A p0 we have g L p 0 w) cn w Ap0 ) f L p 0 w), where N is an increasing function and the constant c does not depend on w. Then for all 1 < p < and all w A p we have p max1, 0 1 g L p w) c 1 Nc 2 w A p p 1 ) ) f L p w). Observe that by extrapolation, it is enough to prove 5.2) for p = 2; similarly, it is enough to prove 5.3) for p = The key result. The main idea found in [12] can be described as follows. Theorem 5.2. Assume that for some family of pairs of nonnegative functions f, g) with g + ) = 0 we have 1 ) r 5.4) ω λ g r ; ) c f dx γ for any dyadic cube R n, where r, γ 1, and the constant c does not depend on. Then for any 1 < p <, g L p w) c w max 1 r, 1 A p γ where the constant c does not depend on w. p 1 ) f L p w), Proof. Let 0 be a dyadic cube with respect to R n. Then any cube dyadic with respect to 0 will be also dyadic with respect to R n. Applying condition 5.4) along with Theorem 3.1, we get that for a.e. x 0, where gx) r m g r 0 ) 1/r c Mfx) + A 3γ,r fx) ), A γ,r fx) =,k ) 1/r 1 rχ f dx) γ k x) k γ k we have used that γ 3γ). Therefore, the question is reduced to showing the corresponding bounds for Mf and A γ,r f. For M this is Buckley s estimate 5.1). For the sake of completeness we give here a short proof of 5.1) found recently in [38]. It is interesting to note that very similar ideas will be used in order to bound the operator A γ,r.
19 LOCAL MEAN OSCILLATION DECOMPOSITION 19 Denote by M c w the weighted centered maximal operator, that is, Mwfx) c 1 = sup fy) wy)dy, x w) where the supremum is taken over all cubes centered at x. If w 1, we drop the subscript w. Denote A p ) = w)σ3) p 1 / p, where σ = w 1 p 1. Then { 1 f = A p ) 1 p 1 1 w) σ3) { 3 np w 1 p 1 1 A p w) ) } 1 p 1 p 1 f M c σfσ 1 ) p 1 dx From this and from the fact that Mfx) 2 n M c fx) we get Mfx) 2 n 3 np w 1 p 1 A p } 1 p 1. Mw c M c σ fσ 1 ) p 1 w 1) x) 1 p 1. It is well known that by the Besicovitch covering theorem, M c w L p w and M c σ L p σ are bounded uniformly in w. Therefore, from the previous estimate we get Mf L p w) 2 n 3 np w 1 p 1 A p M w Mσ fσ 1 ) p 1 w 1) 1 c w 1 p 1 A p M σ fσ 1 ) L p σ) c w 1 which completes the proof of 5.1). We turn now to showing that for any 1 < p <, A γ,r f L p 0,w) cp, γ, n) w max 1 r, 1 A p p 1 L p w) p 1 A p f L p w), p 1 ) f L p w). By Theorem 5.1, it suffices to prove this estimate for p = r + 1. By duality, this is equivalent to that for any h 0 with h L r+1 w) = 1, A γ,r f) r hw dx = 1 ) r 0 γ k k, f hw γ k k c w Ar+1 f r L r+1 w).
20 20 ANDREI K. LERNER Denote A r+1 ) = w)w 1/r )) r. Then r+1 1 ) r γ k f hw ca r+1 3γ k ) γ k k 1 ) r 1 w 1/r 3γ k ) f γ k w3γ k ) c w Ar+1 M c w fw 1/r ) r Mwh c dx. 1/r E k γ k ) hw E k Therefore exactly as above we use the boundedness of the weighted centered maximal function), 1 ) r γ k f hw k, γ k c w Ar+1 R n M c w 1/r fw 1/r ) r M c wh dx k c w Ar+1 M c w 1/r fw 1/r ) r L r+1 w 1/r ) M c wh L r+1 w) c w Ar+1 f r L r+1 w), and we are done. Combining the estimates for M and A γ,r, we get 5.5) g r m g r 0 ) 1/r L p 0,w) c w max 1 r, 1 A p p 1 ) f L p w). Now, the finish of the proof is standard. Denote by R n i, 1 i 2 n, the ndimensional quadrants in R n, that is, the sets I ± I ± I ±, where I + = [0, ) and I =, 0). For each i, 1 i 2 n, and for each N > 0 let N,i be the dyadic cube adacent to the origin of side length 2 N that is contained in R n i. In 5.5) with 0 = N,i we let N. Observe that m g r N,i ) g N,i /2) r 0 as N. Hence, by Fatou s lemma, we get g L p R n i,w) c w max 1 r, 1 Summing over 1 i 2 n completes the proof. A p p 1 ) f L p w). Remark 5.3. The proof actually shows the following dependence of the constant on γ and r: g L p w) cγ n r w max 1 r, 1 A p p 1 ) f L p w).
21 LOCAL MEAN OSCILLATION DECOMPOSITION 21 Corollary 5.4. Let T be a linear operator of weak type 1, 1) and such that T fχ R n \ )x) is a constant on for any dyadic cube, where γ. Then for any 1 < p <, T f L p w) c w max1, 1 where the constant c does not depend on w. A p p 1 ) f L p w), Proof. For any dyadic cube we have T fx) = T fχ γ )x)+c. Therefore, ω λ T f; ) 2T f c)χ ) λ ) 2T fχ )) λ ) c f γ. It remains to apply Theorem 5.2 we may assume that f L 1 and then T f) + ) = 0). Remark 5.5. In the next section we will define a general dyadic grid D. It is easy to see that that Theorem 5.2 and hence Corollary 5.4) remains true if we assume that the corresponding conditions hold for any D instead of D. In the next sections we consider applications of the obtained results to weighted estimated of various operators, and, in particular, to estimates 5.2) and 5.3). 6. CalderónZygmund and Haar shift operators We start with a number of definitions. Definition 6.1. A CalderónZygmund operator on R n is an integral operator, bounded on L 2 R n ), and with kernel K satisfying the following conditions: i) Kx, y) c for all x y; x y n ii) there exists 0 < α 1 such that Kx, y) Kx, y) + Ky, x) Ky, x ) c x x α x y n+α, whenever x x < x y /2. Definition 6.2. By a general dyadic grid D we mean a collection of cubes with the following properties: i) for any D its sidelength l) is of the form 2 k, k Z; ii) R {, R, } for any, R D; iii) the cubes of a fixed sidelength 2 k form a partition of R n. Definition 6.3. We say that h is a Haar function on a cube R n if
22 22 ANDREI K. LERNER i) h is a function supported on, and is constant on the children of ; ii) h = 0; We say that h is a generalized Haar function if it is a linear combination of a Haar function on and χ in other words, only condition i) above is satisfied). Definition 6.4. Let m, k N. We say that S is a generalized) Haar shift operator with parameters m, k if Sfx) = S m,k D fx) = D, D,, l )=2 m l),l )=2 k l) f, h where h is a generalized) Haar function on, and h such that h L h L 1. The number maxm, k) is called the complexity of S. h x), is one on It can be easily verified that any Haar shift operator is bounded on L 2 R n ). In the case of a generalized Haar shift operator its L 2 boundedness is required additionally by the definition. The importance of the Haar shift operators comes from the following result, see T. Hytönen [25] and T. Hytönen et al. [27]. Theorem 6.5. Let T be a CalderónZygmund operator which satisfies the standard estimates with α 0, 1]. Then for all bounded and compactly supported functions f and g, 6.1) g, T f = CT, n)e D k,m=0 2 m+k)α/2 g, S m,k D f, where E D is the expectation with respect to a probability measure on the space of all general dyadic grids. Observe that for several classical singular integrals of the form T fx) = P.V.f Kx) a simpler representation was obtained earlier which involves only the Haar shifts of bounded complexity and hence, the finite sum on the righthand side of 6.1)). The known examples include: i) Kx) = 1 the Hilbert transform, see S. Petermichl [44]); x ii) Kx) = x, n 2 the Riesz transform, see S. Petermichl, x n+1 S. Treil and A. Volberg [47]);
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