Sharp estimates of noncommutative Bochner-Riesz means on two-dimensional quantum tori
Abstract.
In this paper, we establish the full boundedness of noncommutative Bochner-Riesz means on two-dimensional quantum tori, which completely resolves an open problem raised in [7] in the sense of the convergence for two dimensions. The main ingredients are sharp estimates of noncommutative Kakeya maximal functions and geometric estimates in the plane. We make the most of noncommutative theories of maximal/square functions, together with microlocal decompositions in both proofs of sharper estimates of Kakeya maximal functions and Bochner-Riesz means.
Key words and phrases:
Noncommutative space, Bochner-Riesz means, Quantum tori, Kakeya maximal operator, Fourier series, Square function, Rotational algebras2010 Mathematics Subject Classification:
Primary 46L52, 46L51, Secondary 46B15, 42B251. Introduction and main results
Inspired by operator algebras, harmonic analysis, noncommutative geometry and quantum probability, noncommutative harmonic analysis has rapidly developed recently (see e.g. [4, 7, 15, 16, 22, 27, 28, 35, 36, 38, 40, 60, 61]). The purpose of this paper is to study the noncommutative Bochner-Riesz means. We start by introducing the classical Bochner-Riesz means in Euclidean spaces.
It is well-known that the boundedness and convergence of Bochner-Riesz means are among the most important problems in harmonic analysis. The study of Bochner-Riesz means can also be regarded as making precise the sense in which the Fourier inversion formula holds. Recall that the Bochner-Riesz means on the usual torus are defined by
(1.1) |
where , , and . The central topic of Bochner-Riesz means is to seek the optimal range of such that converges to in some sense. In particular, the problem of the convergence turns out to show is a uniform Fourier multiplier in , which can be formulated as the so called Bochner-Riesz conjecture as follows (see e.g. [47]).
Conjecture.
Suppose and . Then we have
One can also define the Bochner-Riesz means on by
(1.2) |
where is the Fourier transform of on . By the standard transference technique (see e.g. [17]), the uniform boundedness of in on is equivalent to that of on . Because of this equivalence, in modern literature, researchers prefer to study the Bochner-Riesz means on .
The study of Bochner-Riesz means originated from S. Bochner [1]. The necessity of the conditions of and in the Bochner-Riesz conjecture was given by C. Herz [20]. In dimension two, this conjecture has been completely resolved by L. Carleson and P. Sjölin [6], independently later by C. Fefferman [14], L. Hörmander [24] and A. Córdoba [10]. When dimension , the Bochner-Riesz conjecture is still open. We refer to some substantial progress in [3, 19, 31, 52, 53] and the references therein.
Concerning the pointwise convergence of , it is natural to investigate the maximal Bochner-Riesz means defined by . It is conjectured that is bounded on for and (see [51]), where the range of is different from that of the Bochner-Riesz conjecture. It is clear that the study of is hander than that of . Up to now, this maximal Bochner-Riesz conjecture is even open for two dimensions. For some important progress, we refer the reader to [5, 33, 51] in the two-dimensional case and [31, 32, 46] for higher dimensions.
It should be pointed out that the study of Bochner-Riesz means is also quite related to several conjectures in harmonic analysis: Fourier restriction conjecture, local smoothing conjecture, maximal Kakeya function conjecture and Kakeya set conjecture (see e.g. [50]). To investigate the Bochner-Riesz conjecture, except some fundamental theories of maximal operators, Calderón-Zygmund operators, oscillatory integral operators, etc, researchers in harmonic analysis have invented many new and deep tools: bilinear or multilinear Fourier restriction (see [3, 31, 53]), incident geometry (see [2, 58]), decoupling and polynomial partitioning (see [19, 33]) in the last two decades. These new methods not only greatly improve the ranges of and in the study of Bochner-Riesz means, but also open new promising research directions in harmonic analysis.
On the other hand, many useful theories in harmonic analysis, such as Littlewood-Paley-Stein square functions, Hardy-Littlewood maximal operators, duality of -BMO, Calderón-Zygmund operators and multiplier operators, have been successfully transferred to the noncommutative setting (see e.g. [4, 21, 23, 36, 37, 40, 62]). Motivated by the development of this noncommutative harmonic analysis, the noncommutative Bochner-Riesz means on quantum tori have been investigated partially by Z. Chen, Q. Xu and Z. Yin [7] with limited indexes of and . Due to the lack of commutativity, the study of noncommutative Bochner-Riesz means seems to be more challenging. For example, Z. Chen, Q. Xu and Z. Yin [7] established the boundedness of the maximal Bochner-Riesz means on the space over quantum tori for , which is an analogue of a classical result by E. M. Stein [46], but with a much more technical proof. Compared with the fruitful theories of commutative Bochner-Riesz means, the noncommutative Bochner-Riesz means deserve to be investigated further. This leads to a natural question that whether we can transfer the modern and powerful tools mentioned before into the noncommutative setting and apply them to studying noncommutative Bochner-Riesz means. Since the study of two-dimensional Bochner-Riesz means is relatively simple (note the Bochner-Riesz conjecture is resolved in this case), in this paper we focus on two dimensions and our main purpose is to obtain the full boundedness of noncommutative Bochner-Riesz means on quantum tori by developing a new tool—the noncommutative Kakeya maximal function.
Quantum tori are also known as noncommutative tori or rotational algebras (see [44]). One can regard quantum tori as analogues of usual tori. Quantum tori are basic examples in operator algebras (see [11]) and are interesting objects in noncommutative geometry which have been extensively studied (see e.g. [8, 44, 54]). The research of analysis on quantum tori was started in [45, 56, 57] and the first systematic work of harmonic analysis on quantum tori was given later in [7]. For recent work related to quantum tori in the direction of noncommutative analysis, we refer to see [27, 29, 34, 43, 60, 61] and the references therein.
To illustrate our main results, we should give the definition of quantum torus. Suppose that , is a real skew symmetric matrix. The -dimensional noncommutative torus is a universal -algebra generated by unitary operators satisfying the following commutation relation:
A well-known fact is that admits a faithful tracial state . Define the weak -closure of in the GNS representation of . We call the -dimensional quantum torus. The state also extends to a normal faithful state on , which will be denoted again by . Notice that when , and . Thus quantum torus is a deformation of classical torus . Let be the noncommutative space associated to pairs with the norm given by .
In the following, we consider the Bochner-Riesz means on quantum tori which are defined by
(1.3) |
where , and . A fundamental problem raised in [7, Page 762] is that in which sense the Bochner-Riesz means converge back to . In this paper we consider this problem in two-dimensional case and state our main results as follows.
Theorem 1.1.
Suppose and . Let be the Bochner-Riesz means defined in (1.3) for . Then we have
Consequently for , converges to in as .
This theorem is in fact a noncommutative version of the two-dimensional Bochner-Riesz conjecture. Thus we completely resolve an open problem raised in [7] in the sense of the convergence for two dimensions. In the following, we briefly introduce the strategy used in the proof of Theorem 1.1.
Notice that is fully noncommutative and its analysis seems to be rather difficult. Nevertheless there is a clever trick that transfers the problem of multiplier operator on quantum tori to the operator-valued setting on usual tori (see [7]). Hence using this method, the boundedness of Bochner-Riesz means on quantum tori can be reduced to that of the operator-valued Bochner-Riesz means on usual tori (see Theorem 5.1). Next we use the noncommutative transference of multiplier (see Theorem 5.4), we can transfer the study of the operator-valued Bochner-Riesz means on to that on , in which case we can do analysis based on some known noncommutative theories of harmonic analysis. However to establish the full boundedness of two-dimensional operator-valued Bochner-Riesz means on , the previous noncommutative theories may not be sufficient and some new tools in harmonic analysis related to the geometry of Euclidean spaces should be brought in.
Our main new tool is the noncommutative Kakeya maximal function. Define the Kakeya average operator by
where is a rectangle centered at the origin with arbitrary orientation and eccentricity (see Section 3 for its definition). As aforementioned, the study of the Kakeya maximal function is another important problem in harmonic analysis related to Bochner-Riesz means (see e.g. [59]). Notice that the study of noncommutative Kakeya maximal functions is more difficult since it can not be defined directly. It is easy to see that could be dominated by the Hardy-Littlewood average operator with bound . This implies that the noncommutative Kakeya maximal operator is bounded with norm . In this paper, we shall establish its sharp norm— (see Theorem 3.1), which is crucial to our study of noncommutative Bochner-Riesz means. To the best knowledge of the author, it is the first time that a sharp estimate of the noncommutative Kakeya maximal function is obtained in noncommutative analysis. The proof here is quite technical and our strategy is the microlocal decomposition, together with theories of the Fourier transform and noncommutative square/maximal functions.
Below we sketch out the proof of the boundedness of the operator-valued Bochner-Riesz means on (i.e. Theorem 4.1). To get the full boundedness of Bochner-Riesz means, by the duality and the noncommutative analytic interpolation theorem (see the appendix), it suffices to show the result for the case . We first make a dyadic decomposition: and matters are reduced to proving the norm of has enough decay in . We next make a microlocal decomposition: where the support of each lies in a small piece (denoted by ) of annulus with the major direction . Notice that the norm of has an expression
If the major directions of these pieces are closed to each other (i.e. ), then the above term is bounded by a column square function norm . If , then we need a very important geometric observation: is finite overlapped. With this geometric estimate, the norm of is bounded by a row square function norm . Consequently we use both column and row square function norms to control the norm of , which is consistent with the theory of noncommutative square functions. To estimate this column/row square functions, we should do more analysis for the kernel of . Roughly speaking, a key fact in our proof is that can be bounded by a sum of Kakeya average operators s where orientations of s are just in a fixed direction—the major direction of . By the dual theory between and , our estimates for noncommutative square functions can be reduced to that of Kakeya maximal functions, which will be systematically studied in Section 3.
The methods above heavily rely on the geometry of the plane. For the higher dimensional case, to get some nontrivial boundedness of Bochner-Riesz means, some more new tools in harmonic analysis should be transferred to the noncommutative setting. We hope to work this problem in the future.
This paper is organized as follows. First we give some preliminaries of noncommutative spaces, noncommutative maximal/square functions and related lemmas in Section 2. In Section 3, we investigate the noncommutative Kakeya maximal function and establish its sharper estimate there. In Section 4, we obtain the full boundedness of the operator-valued Bochner-Riesz means on . The proof is based on sharper estimates of noncommutative Kakeya maximal functions and a square function inequality studied in the previous sections. Section 5 is devoted to the study of Bochner-Riesz means on quantum tori. In this section, we first establish the full estimates of the operator-valued Bochner-Riesz means on usual tori and then transfer this result to that on two-dimensional quantum tori (i.e. Theorem 1.1). Finally for the reader’s convenience, we give a proof of the noncommutative analytic interpolation theorem in the appendix which may be known to experts.
Notation. Throughout this paper, the letter stands for a positive finite constant which is independent of the essential variables, not necessarily the same one in each occurrence. means for some constant . By the notation we mean that the constant depends on the parameter . means that and . For any measurable set , we denote the Lebesgue measure by . denotes the set of all nonnegative integers and with -tuples product. For and , . Set . , denotes the integer part of . We use LHS to represent left hand side of an expression. Given a function on , the Fourier transform of is defined by . For a function on , define (or ) and (or ) the Fourier transform and the inversion Fourier transform of by
2. Preliminaries and some lemmas
In this section, we introduce some basic knowledge of noncommutative harmonic analysis including noncommutative spaces, maximal functions, square functions and many operator-valued inequalities which are useful in this paper.
2.1. Noncommutative -spaces
Let be a semifinite von Neumann algebra equipped with a normal semifinite faithful (n.s.f. in short) trace . Denote by the positive part of and let be the set of all whose support projections have finite trace. Let be the linear span of , then is a weak dense -subalgebra of . Consider . For any , and we set
where is the modulus of . Define the noncommutative space associated with by the completion of and set it as . For convenience, if , we define equipped with the operator norm . Let denote the positive part of . A lot of basic properties of classical spaces, such as Minkowski’s inequality, Hölder’s inequality, dual property, real and complex interpolation, have been transferred to this noncommutative setting. In particular, the following monotone properties are frequently used in this paper: for and ,
(2.1) |
(2.2) |
For more about noncommutative spaces, we refer to the very detailed introduction in the survey article [42] or the book [62].
In this paper, we are interested in the noncommutative space on the tensor von Neumann algebra . Set the tensor trace . Define the noncommutative space associated with pairs . Notice that is isometric to the Bochner space on with values in .
2.2. Noncommutative maximal functions
It is difficult to define a noncommutative maximal function straightforwardly since two general elements in a von Neumann algebra may not be comparable. This obstacle can be overcome by defining the maximal norm directly. We adopt the definition of the noncommutative maximal norm introduced by G. Pisier [41] and M. Junge [26].
Definition 2.1 ().
We define the space of all sequences in which admits a factorization of the following form: there exist and a bounded sequence in such that , . The norm of in is given by
where the infimum is taken over all factorizations of as above.
If is a sequence of positive elements, then if and only if there exists a positive element such that , and
(2.3) |
Similarly if is a sequence of self-adjoint elements, then if and only if there exists a positive element such that , and
(2.4) |
More generally, if is an index set, we define as the space of all in that can be factorized as
Then the norm of is defined by
It was shown in [30] that if and only if and moreover in this case, the norm is equal to the above supremum.
We will often use to represent . However we point out that is just a notation since makes no sense in the noncommutative setting.
To study the dual property of the above spaces , we need to introduce another space.
Definition 2.2 ().
Define as the space of all sequences in which could be factorized as
for two families and in such that and . is equipped with the norm
where the infimun is taken over all decompositions of as above.
It is not difficult to see that if for all , if and only if (see e.g. [62]). In such a case, we have the following equality
We introduce the following basic duality theorem of , which has been established by M. Junge and Q. Xu in [30].
Lemma 2.3.
(i). Suppose . Let be the conjugate index: . Then the dual space of is . The element acts on as follows
(ii). Suppose . For any , we have
Moreover if is positive, then
2.3. Noncommutative square functions
To define the noncommutative square function, we should first introduce the so-called column and row function spaces. Let be a finite sequence in where . Define
Definition 2.4 ().
We define the spaces as follows:
-
(i).
If , equipped with the intersection norm:
-
(ii).
If , equipped with the sum norm:
where the infimun is taken over all decompositions with and in .
It is easy to see that . Next we introduce some inequalities for . The first one is Hölder type inequality whose proof can be found in [62].
Lemma 2.5.
Let be such that . Then for any and ,
The second one is the noncommutative Khintchine inequality for the Rademacher sequence as follows.
Lemma 2.6 (see [62]).
Let and be a finite sequence in . Then
where is a Rademacher sequence on a probability space .
We also require some convexity inequalities for the operator-valued function in this paper. The following one is Cauchy-Schwarz type inequality which can found in [36, Page 9]).
Lemma 2.7.
Let be a measure space. Suppose that is a weak- integrable function and is an integrable function. Then
(2.5) |
where is understood as the partial order in the positive cone of .
Finally we introduce the following vector-valued Plancherel theorem which will be mostly used in square function estimates: Let , then we have
(2.6) |
which is a consequence of the fact is a Hilbert space. Such vector-valued Plancherel theorem is sufficient in most part of our proof though sometimes we need a more general operator-valued Parseval’s relation: for , we have
(2.7) |
3. Noncommutative Kakeya maximal functions
In this section, we study the boundedness of noncommutative Kakeya maximal functions. Before that we give several definitions and lemmas. We only consider . Set and . Denote the noncommutative space associated with pairs .
The main preliminaries of noncommutative maximal functions have been given in Subsection 2.2. We introduce the noncommutative Kakeya maximal function as follows. Define the eccentricity of a rectangle by the ratio of the length of its long side to that of its short side. Let be a positive integer. Define the set as rectangles in the plane of arbitrary orientation whose center is the origin and eccentricity is . For , we define the Kakeya average operator as follows
(3.1) |
where is a rectangle belonging to . We are mainly interested in the maximal norm of noncommutative Kakeya average operator, since it is a crucial estimate in the study of noncommutative Bochner-Riesz means.
Let us first give a trivial bound of its norm. Recall that the Hardy-Littlewood average operator is defined by
where is a cube in with center zero and arbitrary orientation. For any rectangle , there exists a cube such that and equals to the length of long side of . Consider as a positive function in . Then . Using the noncommutative Hardy-Littlewood maximal operator is of weak type (see [36]), we get the Kakeya maximal operator is of weak type with bound . Applying the noncommutative Marcinkiewicz interpolation theorem in [30], together with the fact that the maximal operator of is of , we get that the maximal operator of is of strong type with bound . However this bound is quite rough and not sufficient for our later application. The following improved bound is our main result in this section.
Theorem 3.1.
Let be the Kakeya average operator defined in (3.1). Then for , we have
Combining the noncommutative Marcinkiewicz interpolation theorem (see [30]), together with a trivial weak type bound and a strong bound of , we immediately get the following corollary.
Corollary 3.2.
Let be defined in (3.1). Then for any , we have
It should be pointed out that the bound in Theorem 3.1 is sharp even in the commutative case, see [18, Proposition 5.3.4]. A. Córdoba [9] first obtained the boundedness of the Kakeya maximal function on with norm . The sharp bound was later established by J. O. Strömberg [49] where he used several estimates of distribution functions and some geometric constructions. S. Wainger [55] also obtained the sharp bound without a proof but he mentioned that the idea given by A. Nagel, E. M. Stein, S. Wainger [39] can be modified to his setting. It is well-known that the distribution function is difficult to deal with in the noncommutative setting (for example the weak boundedness problem is a challenge problem). Hence the method from J. O. Strömberg [49] may be difficult to be applied in the noncommutative setting. The strategies used in our proof below are the Fourier transform, square and maximal function theories and the microlocal decomposition, which are mainly motivated by [39] and [55].
Before giving the proof of Theorem 3.1, we introduce the noncommutative directional Hardy-Littlewood average operator defined by
(3.2) |
where is a unit vector in . By using the standard method of rotation, the definition of maximal norm in (2.3) and the fact one dimensional noncommutative Hardy-Littlewood maximal operator is of strong type for (see [36]), the author and his collaborators recently established the following result in [21, Lemma 6.3].
Lemma 3.3.
Let be a unit vector. Define in (3.2). Let . Then we have
Now we are in a position to prove Theorem 3.1.
Proof of Theorem 3.1.
Let us start with several reductions. Without loss of generality, we suppose that is positive since the general case just follows by decomposing as linear combination of four positive functions.
To prove our estimate, it suffices to consider the case . In fact, assume that we show this theorem for , we can prove the general case for arbitrary as follows. For any positive integer , there exists a positive integer such that , i.e. . Then for any , by enlarging the long side of such that its eccentricity increases to , we get a new rectangle . Then Therefore we get
Similar to that in the commutative case, by symmetry and rotation, we only need to control the average over those rectangles that have eccentricity , but whose major axes make angles with the -axis such that (see e.g. Section 3.11, Chapter X in [47]). We abuse notation and still define as those preceding rectangles.
After these reductions, below we smooth the average operator. Set and let . Choose a nonnegative, radially decreasing and smooth function such that if and . Define . To prove our theorem, it is sufficient to consider the average operator
Indeed, since , by some elementary geometric observation, for any with the major direction where for some , there exists such that
where the constant is independent of . On the other hand, for , , there exists with the major direction such that ,
Therefore by the definition of positive maximal norm in (2.3), we get
Notice that there are two averages for two different directions in the operator . Our next goal is to reduce it to one average with the help of the directional Hardy-Littlewood maximal operator. By our choice of , it is easy to see that
where is the directional Hardy-Littlewood average operator defined in (3.2) and is defined as
Therefore by the boundedness of maximal operator of in Lemma 3.3, to prove our theorem, it suffices to show
(3.3) |
Next we reduce the study of to its lacunary case . For any , there exists such . Then we get
where the second inequality just follows from the radially decreasing property of . Hence we only need to consider the lacunary operator . At present time, we conclude that the proof of our main theorem is reduced to show
(3.4) |
Let . In the following, we will establish a key inequality
(3.5) |
with the constant independent of . Notice that when , , where and is the noncommutative directional Hardy-Littlewood average operator in (3.2). Using the boundedness of maximal in Lemma 3.3, we get
Then it is easy to see that the required estimate (3.4) just follows from (3.5) with an induction argument.
The rest of this section is devoted to the proof of (3.5). For convenience, set . Define where is a constant independent of such that are disjoint from each other. Notice that s are equally distributed in or (see Figure 1 later). We split as and which are defined by
Recall that . Since is positive in , by the duality (see (ii) in Lemma 2.3), there exists a positive sequence with norm such that
where
We consider the first term . Notice that for every , we have
(3.6) |
Recall that is positive in . Then by the duality (see (ii) in Lemma 2.3), the definition of in (2.3) and the preceding equality (3.6), we get
which is exact the second term in right side of (3.5).
Now we turn to . To finish the proof of (3.5), we only need to show that is controlled by . By making a dilation, it is easy to check that for ,
(3.7) |
Therefore we see that the terms related to even in the sum of equal to zero. Applying (3.6) and (3.7) again, we rewrite the odd terms in as follows
Let us consider firstly. Using the duality in (ii) of Lemma 2.3, we get
Recall . Let be the unit vector in the direction along , i.e. . Then it is straightforward to verify that for a positive function ,
where the right side of the above inequality is the directional Hardy-Littlewood average operator defined in (3.2). Now using the boundedness of maximal operator of in Lemma 3.3, we get for any positive function ,
(3.8) |
Consequently (3.8) holds for any by decomposing it as linear combination of four positive functions.
Observe that may not be positive. So we can not apply the maximal norm in (2.3). Recall that for any , we can decompose it as linear combination of two self-adjoint elements:
Hence we can write . Then utilizing Minkowski’s inequality, we get
We first consider the real part. Notice that . Then by Minkowski’s inequality and (3.8), we get
Rewrite this estimate via the equivalent definition of in (2.4), we obtain that there exists such that for each ,
Then by setting , we see that for each , we have because of which is just by an elementary inequality (2.2). Moreover we get
where in the third equality we use vector-valued Plancherel’s theorem (2.6), the last inequality just follows from are disjoint from each other and vector-valued Plancherel’s theorem (2.6) again. Thus we prove that
By applying the similar argument to the imaginary part, we could also get
Combining these estimates of real and imaginary parts, we obtain the desired estimate of .
For the term , using the similar argument as we have done in the proof of , we also get that is bounded by .
At last we turn to the term . We first introduce an inequality as follows:
(3.9) |
This inequality could be verified by writing as the polar decomposition and using Cauchy-Schwarz’s inequality,
For simplicity, we define . Then by the above inequality (3.9) and Cauchy-Schwarz’s inequality, we have
where in the last inequality we apply the dual property (ii) in Lemma 2.3.
We first consider the part . Our goal is to show that
(3.10) |
The strategy here is to use a square function to control the maximal function, which has been appeared in the proof of . In fact applying an equivalent norm of in (2.3), monotone properties in (2.2) and (2.1), we have
It is straightforward to show that . Then utilizing vector-valued Plancherel’s theorem (2.6) and the definitions of , , we get that
To prove (3.10), again by vector-valued Plancherel’s theorem (2.6), we only need to show the multiplier above is bounded, i.e.
(3.11) |
holds uniformly for . Fix . It suffices to consider the sum of such that which means that
where . Such lower estimates may be not enough to prove (3.11). In the following, we obtain some better lower estimates via some geometric observations of the plane. Denote . Then by using the mean value formula and Cauchy-Schwarz’s inequality, we see that
Let denote the orthogonal unit vector of in . Then we observe that s, where , are equally distributed with distance in the plane or (see Figure 1 below).

Notice that the geometric illustration of is the distance between the point and the line along the direction . Recall that is a fixed unit vector. By the equally distributed property of , we can separate the set into at most subsets such that each has cardinality less than some absolute constant and for each ,
This fact can be easily seen from the geometry in Figure 1. Therefore by the above inequality, for any , , we get . Since is a Schwartz function, so is smooth and rapidly decays at infinity. We finally conclude that
which proves (3.10). For the term , we can also obtain
by using the same argument if observing that
Combining these estimates of and , we get is majorized by which ends the proof this theorem. ∎
4. Bochner-Riesz means on
In this section, we study the operator-valued Bochner-Riesz means on , where throughout this section. The main tools are noncommutative Kakeya maximal functions which have been investigated in the previous section. Our main result can be stated as follows.
Theorem 4.1.
Let and . Then for the Bochner-Riesz means given in (1.2), set , we have
(4.1) |
Consequently for , converges to in as .
Before giving the proof, let us start with some definitions and lemmas. We first define the following Fourier multiplier on for convenience.
Definition 4.2.
We say is an Fourier multiplier if the operator defined by
extends to a bounded operator on , where is the class of Schwartz functions on and is the linear span of all whose support projections have finite trace defined in Subsection 2.1. Denote by the space of all multipliers and the multiplier norm.
Notice that for , the convolution kernel associated to is integrable over with the bound (see e.g. [18, Proposition 5.2.2]). Then we immediately get the following lemma.
Lemma 4.3.
Let . If , then for all , we have
Next we introduce a noncommutative Littlewood-Paley-Rubio de Francia’s square function inequality for equal intervals whose proof can be found in [25]. This inequality is also a key step in our study of Bochner-Riesz means.
Lemma 4.4.
Set . Let s be intervals of equal length with disjoint interior, and . Define . Then for all , we have
Now we begin to prove Theorem 4.1.
Proof of Theorem 4.1.
We first point out the norm convergence in is a direct consequence of (4.1). In fact for any , i.e. with and , converges to in as . Then by the density argument and the second inequality in (4.1), we could get for every , converges to in . So in our proof below, it is sufficient to consider (4.1). Since the multiplier in is invariant under the dilation:
we only need to consider the first inequality in (4.1). Throughout the proof, we suppose that is a complex number with . When , the estimate just follows from vector-valued Plancherel’s theorem (2.6). By the duality, it is enough to show (4.1) holds for .
We first make a dyadic decomposition of the multiplier. To do that, we choose a smooth function supported in and a smooth function supported in such that
Using this equality, we can decompose the multiplier as follows
(4.2) |
Below we give some observations of Fourier multipliers and . It is easy to see that is a smooth function with compact support, hence the multiplier lies in for all . Notice that each function is also smooth, radial and supported in a small annulus:
Therefore each also lies in for , but its bound may depend on . To sum over the series in (4.2), it is crucial to determine exactly the bound of multiplier in . Our main goal in this proof is to show that for each ,
(4.3) |
Suppose we have (4.3) for the moment. Then summing over the series in (4.2) with these estimates in (4.3), we get
Applying the noncommutative Riesz-Thorin interpolation theorem (see [62]), we get (4.1) for . Next we use the analytic interpolation theorem (see Theorem A.1 in the appendix) to show the remaining part. Let be a small constant (for example less than ). Then
where the second inequality just follows from Lemma 4.3. Define a new operator by
To apply Theorem A.1, we should verify the hypothesis of Theorem A.1. It is easy to see that is an analytic family of linear operators with admissible growth and
Let and satisfy and . Set and . Then applying Theorem A.1, we get
where is a finite constant defined in Theorem A.1. This immediately implies our required estimate (4.1) since and .
Now we turn to prove (4.3). Fix in the rest of proof. To estimate the norm of the Fourier multiplier , we need an additional decomposition (the called microlocal decomposition) of that takes into the radial nature of . We usually identify the plane as complex plane by . The reason to do this is that the expression in can be easily understood in the geometric point (note that is length of and is an argument). Next we define sectorial arcs as follows:
for all . We choose a smooth function such that for , for and holds for all . Define
It should be pointed out that is a function about variable . Then by our construction of , we see that
where if is even and if is odd. By some elementary calculations, it is not difficult to get that
(4.4) |
Next we split all into five subsets whose supports satisfy the following conditions:
-
(a).
-
(b).
-
(c).
-
(d).
-
(e).
The support intersects
We first observe that there are only at most eight s in the case (e). In such a case, it is straightforward to get that
(4.5) |
as we will see below (which will be pointed out in our later proof). By symmetry, we only need to concentrate on the case (a). Denote the index set . For each , define a Fourier multiplier operator by
Our purpose below is to show satisfies (4.3), i.e.
(4.6) |
By decomposing as linear combination of four positive functions, we may suppose that is positive. In the following we should separate the sum of into two parts,
(4.7) |
For the term , the sum of is taking over which is finite. By Hölder’s inequality of the square function in Lemma 2.5, we get
For the term , using vector-valued Plancherel’s theorem (2.6), we get
Since is positive, it is easy to see where we use the notation . Then we have
where . Applying these support conditions, we rewrite the above integral of as
Next using the convexity operator inequality (2.5), this term is bounded by
Before proceeding our proof further, we need the following geometric estimate.
Lemma 4.5.
There exists a constant independent of and such that
Remark 4.6.
The geometric estimate of this lemma is different from the classical commutative one stated in [10]. The main difference is that there is no involution of in the commutative case because of if is a complex number. This yields a geometric estimate in the form which is simpler than that of Lemma 4.5. In fact, all s are contained in and the pieces s are well distributed. However in the noncommutative setting, for an element , we have . Our argument above leads to the geometric estimate . Notice stays in an oppositive direction of , i.e. . These pieces s may accumulate near the origin if and are close enough, which can be easily seen in view of geometric observation. Hence if is close to the origin, may be infinite. This is the reason why we split the sum of into two parts in (4.7). Luckily we can show is finite overlapped if .
The proof of Lemma 4.5 will be given later. Applying this geometric estimate, we get is bounded by
where in the first equality we use vector-value’s Plancherel theorem (2.6) and the third equality follows from the tracial property of : . Combining these estimates of and , together with (4.7), we get
(4.8) |
This kind of estimate is consistent with the estimate of square functions in noncommutative analysis in the sense that we should use both row and column square functions to control the norm for (see Subsection 2.3).
Now we should study carefully the multiplier . Consider firstly. Note that is supported in a rectangle parallel to axes with side length and (along the -axis and -axis, respectively). Roughly speaking in such a rectangle . In fact by some straightforward calculations, we get the smooth function satisfies
(4.9) |
for all positive integers and which is an analogue of (4.4). We can rewrite (4.9) as follows
With these estimates and using integration by parts, we obtain that
(4.10) |
Let and be the unit vectors corresponding the directions and , respectively. According our definition, where . By a rotation, we see that
(4.11) |
Hence combining with (4.10), we have
which immediately implies that
(4.12) |
Here we point out that (4.5) follows from (4.12). Obviously all the above estimates hold for since .
We turn to give some geometric observations of the support of . Let be the projection of the support of . If the support of lies in the upper half plane of (i.e. ), then we see
Similarly if the support of lies in the lower half plane of (i.e. ), then
Since is a fixed integer, the sets s are almost disjoint for different because is only joint with and . Next our goal is to construct congruent strips containing . If we set as a strip centered at with width , i.e.
Then . For any , , define the strips as follows
Note that has width and each must be contained in one of for some and in view of some simple geometric observation of . We say and define . Let . According the definition of , we see
Now we come back to the estimate in (4.8). We first consider the column square function. Using the convexity operator inequality (2.5) and the uniform boundedness of in (4.12), we get
Plugging the above inequality into the column square function in (4.8) and applying the monotone property (2.1), we get
where in the last equality we use the duality and the supremum is taken over all positive in with norm less than one. Continue the above estimate, we obtain
where the first inequality follows from the duality in Lemma 2.3. If we can prove the following two estimates:
(4.13) |
(4.14) |
then we finally get that
which is the required estimate of (4.6). For the row square function, we can use the similar method to obtain the desired estimate
In fact, . Then repeating these arguments for the column square function above, we see the proof is reduced to the following two inequalities:
(4.15) |
(4.16) |
Below we give the proofs of (4.13), (4.15) and (4.14), (4.16). We first consider (4.13) and (4.15). Recall (4.10), is integrable over and satisfies
By making a change of variables, we immediately get
where . Notice that a general function is obtained from by a rotation (see (4.11)). Therefore we get
where is a rectangle with principal axes along the directions and with half side length and , respectively. Since is positive, we see that
where should be understood as partial order in the positive cone of . For convenience, we set . Notice that the Kakeya average operator defined in (3.1). Now using the estimate of the Kakeya maximal function in Theorem 3.1, we get
which is the just required estimate of (4.13). The proof of (4.15) is similar, we omit the details here.
We turn to the proofs of (4.14) and (4.16). Recall the strips
which is defined for and . These strips have width and each belongs to one of them, which we call .
The family may have duplicate sets, so we split it into subfamilies by placing into different subfamilies if the indices and are different. Thus we write the set as where elements in each are different.
We next observe that the multiplier operator
satisfies where is the identity operator in variable and is an operator with the multiplier . Now using Lemma 4.4, we get for ,
Specially the case is our required estimate for (4.14) and (4.16). Now we prove (4.14) and (4.16) for one . Since , the full forms of (4.14) and (4.16) just follow from Minkowski’s inequality. ∎
In the remain part of this section, we turn to Lemma 4.5. This lemma is stated in [13, Exercise 3.4] without a proof. For the sake of self-containment, we give a proof here.
Proof of Lemma 4.5.
We only need to show that for each integer , the following estimate
holds. If is finite, there exist only finite many pairs of sets depending on and this lemma is trivial. Therefore we can assume that is a large integer. Set . Then is sufficient small. For simplicity, denote the set by . Elements of have the form
where and . We first give some geometric observations of . Set
(4.17) |
then it is easy to see that the direction of is along . Next we rewrite as follows
By some elementary calculations, we further get the second term above equals to
Combining this equality, we see that equals
where
On the other hand, utilizing the following equality
we see that has the same direction as . Thus, is perpendicular to . Before proceeding further, we need the following inequalities which will be frequently used in later manipulations:
(4.18) |
By the first and second inequalities in (4.18), it is straightforward to verify that the error term satisfies
We therefore conclude that contains in a rectangle centered at with half-length
in the direction along since is sufficient small and half-width
in the direction along since . Moreover a disk centered at with radius .
Our next goal is to show that for a fixed with , there exist only finite pairs with such that . Once we prove this fact, the geometric estimate in Lemma 4.5 immediately follows from it. If , then . Therefore if these two sets intersect, we get
(4.19) |
In the following we should give a lower bound for . Before that we need a fundamental inequality which could be found in [18, Exercise 5.2.2]:
(4.20) |
By some elementary calculations and using the inequality (4.20) with (iii) of (4.18), we get a lower bound as follows
where we use our hypothesis that all the supports of are contained in (i.e. ). Thus combining the above estimate and (4.19), we obtain
(4.21) |
However (4.21) is not enough to show that the number of is finite. In the following, we give more exact information of lower and upper bound of .
According our condition, and . Without loss of generality, we suppose that . Then by (4.21), we get
This implies in view of the identity (4.17) and (i), (iii) of (4.18).
Next we see that the rectangle is centered at point with a distance to the origin . Recall that has half-length in the direction and in the direction has half-width (see Figure 2 below). This implies that is far from the origin . In fact, by (iii) of (4.18),
Similar properties also hold for . Since intersects , then intersects . Note that the angle between and is (see Figure 2 below).

Then the distance of and has an upper bound
On the other hand, the distance of and has the following lower bound
where we use (iii) of (4.18). The upper and lower estimates, together with our hypothesis , , finally yield that
(4.22) |
Combining (4.22) and (4.21), we get that , . Hence we prove that for a fixed , there exist only finite pairs such that , which completes our proof. ∎
5. Bochner-Riesz means on quantum tori
In this section, our goal is to establish the full boundedness of Bochner-Riesz means on two-dimensional quantum tori, i.e. Theorem 1.1. We first establish the corresponding results on usual torus based on Theorem 4.1 in Section 4.
5.1. Bochner-Riesz means on usual tori
Recall that the -torus is defined as . We often set as the cube with opposite sides identified. The function on can be regarded as an -periodic function on in every coordinate. Haar measure on is the restriction of Lebesgue measure to which is still denoted by .
Our previous main theorem of Bochner-Riesz means in Section 4 is in the frame of the tensor von Neumann algebra . To extend our main result to the fully noncommutative quantum torus, we should first transfer them to the setting of the tensor von Neumann algebra .
Given a function , define the Bochner-Riesz means by (1.1). By the transference method (see Theorem 5.4 later), we can formulate the noncommutative Bochner-Riesz conjecture on tori with ranges of indexes and the same as that in the commutative case in the introduction. Our main result in this subsection is stated as follows.
Theorem 5.1.
To prove Theorem 5.1, we should introduce some definitions and lemmas.
Definition 5.2.
For , a bounded function on taking values in is called regulated at the point if
The function is called regulated if it is regulated at every .
The above definition of regulated function was first appeared in [12]. Next we introduce the Fourier multiplier on .
Definition 5.3.
Given a bounded function , we say is a Fourier multiplier on if the operator defined by
where and , extends to a bounded operator on . The space of all these multipliers is denoted by . For simplicity, we denote the norm of multiplier by .
Theorem 5.4.
Let be a regulated function which lies in for some . Then the sequence belongs to and more precisely
Moreover for all , the sequence lies in and
Proof.
The proof of this theorem is quite similar to that in the commutative case (see e.g. the proof of Theorem 4.3.7 in [17]), so we omit the details of the proof here. ∎
5.2. Bochner-Riesz means on quantum tori
In this subsection, we finally consider the Bochner-Riesz means on two-dimensional quantum tori and prove our main results Theorem 1.1. We begin by introducing some notation.
Suppose that , is a real skew symmetric matrix. The -dimensional noncommutative torus is a universal -algebra generated by unitary operators satisfying the following commutation relation:
By the unitary property of s, if we multiply in both left and right sides of the above equality, we get
For a multi-index and , we define . We call
(5.1) |
is a polynomial in if the sum in (5.1) is finite, i.e. holds only for finite multi-indexes. Let be the involution algebra of all such polynomials. Then is dense in . A well-known fact is that admits a faithful tracial state such that if and only if where (see e.g. [44]). Hence for any polynomial with form (5.1), we can define
Define the weak -closure of in the GNS representation of . We call the -dimensional quantum torus associated to . The state also extends to a normal faithful state on , which will be denoted again by . Notice that when , and . Thus quantum torus is a deformation of classical torus .
Let be the noncommutative space associated with . Using is a state and Hölder’s inequality, we see that for . For any , there exists a formal Fourier series
where is called the Fourier coefficient of . Analogous to the classical analysis, a fundamental problem here is that when the Fourier series converges to . In the following, we consider the most important Bochner-Riesz means on quantum tori which is defined by
(5.2) |
The Bochner-Riesz means on quantum tori was firstly studied by Z. Chen, Q. Xu and Z. Yin [7]. A fundamental problem raised in [7, Page 762] is that in which senses converge back to . We consider the convergence here. In fact similar to that of the commutative case, one can formulate the following problem of quantum Bochner-Riesz means.
Conjecture.
Suppose and . Consider the Bochner-Riesz means defined in (5.2), then we have
The main result here is to show that the preceding conjecture holds for two dimensions, i.e. Theorem 1.1. For the reader’s convenience, we restate this theorem as follows.
Theorem 5.5.
Suppose and . Let the Bochner-Riesz means be defined in (5.2) for . Then we have
Consequently for , converges to in as .
The proof is based on a transference technique which is a standard method. Consider the tensor von Neumann algebra equipped with the tensor trace . Let be the noncommutative space associated with . Observe that
where the space on the right hand side is the Bochner space on with values in .
For every , we define as
which is an isomorphism of . It is easy to see that for any . Hence is trace preserving. Therefore it extends to an isometry on for , i.e.
(5.3) |
The following transference method has been showed by Z. Chen, Q. Xu and Z. Yin in [7, Proposition 2.1 & Corollary 2.2].
Lemma 5.6.
For any , the function is continuous from to (with respect to the weak -topology for ). Moreover and for . Thus, is an isometric embedding from to .
Proof of Theorem 5.5.
The proof just follows from Theorem 5.1 and Lemma 5.6. In fact, by the density argument, it suffices to consider as a polynomial . Define in Lemma 5.6. Then and by Lemma 5.6. Using Theorem 5.1, we get
(5.4) |
On the other hand, it is easy to see . According the definition of Bochner-Riesz means,
This, together with (5.3) and (5.4), implies the desired estimate in Theorem 5.5. The convergence follows from the standard limiting argument. ∎
Appendix A Interpolation of analytic families of operators on noncommutative spaces
In this appendix, we state precisely an analytic interpolation theorem which may be known to experts. Let be the linear span of all whose support projections have finite trace. Suppose that is a linear operator mapping to itself for every in the closed strip . We say the family is analytic if the function
is analytic in the open strip and continuous on for any functions and in . Moreover we say the analytic family is of admissible growth if there exists a constant such that
for all . Now we can state the following analytic interpolation theorem.
Theorem A.1.
Suppose that is an analytic family of linear operators of admissible growth. Let and assume that are positive functions on such that
(A.1) |
for and some . Let satisfy and . Suppose that
(A.2) |
hold for all . Then for any , we have
where for ,
To prove this theorem, we need an extension of the three lines theorem which could be found in [48, Page 206, Lemma 4.2].
Lemma A.2.
Suppose that is analytic on the open strip and continuous on its closure such that
for some . Then for any , we have
Proof of Theorem A.1.
The proof is quite similar to that in the commutative case. Let with polar decompositions and . Without loss of generality, we may suppose that . By the duality, to prove our theorem, it suffices to show
For , define and where the continuous functional calculus is defined by complex powers of positive operators. By the density argument, we could suppose that and are linear combinations of mutually orthogonal projections of finite trace, i.e.
where s, s are real and s, s are mutually orthogonal basis. Then
Therefore the function is an analytic function on taking values in . Similar properties hold for the function . Define
Then we have
By our assumption, is analytic. Hence is an analytic function satisfying the hypothesis of Lemma A.2. Recall a property of polar decomposition: , then by the continuous functional calculus of , we obtain
(A.3) |
where is a continuous function on . Since
then by (A.3), we get
Therefore we get . Similarly . Hölder’s inequality and our assumption show that for all ,
Similarly for all , . Now applying Lemma A.2 with the preceding two estimates and notice that , we get
which implies the required estimate. ∎
Acknowledgement
The author would like to thank Guixiang Hong for some helpful suggestions when preparing this paper and the referees for their very careful reading and valuable suggestions.
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