Abstract
It is well known that the Hilbert matrix \({\mathrm {H}}\) is bounded on weighted Bergman spaces \(A^p_\alpha \) if and only if \(1<\alpha +2<p\) with the conjectured norm \(\pi /\sin \frac{(\alpha +2)\pi }{p}\). The conjecture was confirmed in the case when \(\alpha =0\) and also in the case when \(\alpha >0\) and \(p\ge 2(\alpha +2)\), which reduces the conjecture in the case when \(\alpha >0\) to the interval \(\alpha +2<p<2(\alpha +2)\). In the remaining case when \(-1<\alpha <0\) and \(p>\alpha +2\) there has been no progress so far in proving the conjecture, moreover, there is no even an explicit upper bound for the norm of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \). In this paper we obtain results which are better than known related to the validity of the mentioned conjecture in the case when \(\alpha >0\) and \(\alpha +2<p<2(\alpha +2)\). On the other hand, we also provide for the first time an explicit upper bound for the norm of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \) in the case when \(-1<\alpha <0\) and \(p>\alpha +2\).
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1 Introduction
The Hilbert matrix \({\mathrm {H}}\) and its action on the space \(\ell ^2\) consisting of square summable sequences was first studied in [11], where Magnus described the spectrum of the Hilbert matrix. Thereafter Diamantopoulos and Siskakis in [3, 4] begin to study the action of the Hilbert matrix on Hardy and Bergman spaces, which can be seen as the beginning of studying of the Hilbert matrix as an operator on spaces of holomorphic functions. They obtained some partial results concerning the questions of boundedness and exact norm of the Hilbert matrix on Hardy and Bergman spaces, which have been improved in [5] by Dostanić, Jevtić and Vukotić. We note also that Aleman, Montes-Rodríguez and Sarafoleanu provide a closed formula for the eigenvalues of the Hilbert matrix in a more general context (see [1]). Following the above results, it was known that Hilbert matrix \({\mathrm {H}}\) is bounded on Bergman space \(A^p\) if and only if \(2<p<\infty \) and
when \(4\le p<\infty \). It was also conjectured that previous equality remains valid in the remaining case when \(2<p<4\). This conjecture was actually proven in [2], where the new method based on the new way to use monotonicity of the integral means was introduced (see also [9]).
The starting point for studying the boundedness of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \) was paper [6] by Galanopoulos, Girela, Peláez and Siskakis, where the corresponding partial results were obtained. A complete characterization of the boundedness of the Hilbert matrix \({\mathrm {H}}\) on the spaces \(A^p_\alpha \) is given in [7], where it is proved
On the other hand, the preceding result opened the way to the question of the exact norm of the Hilbert matrix acting on the weighted Bergman spaces. In [8] it was proved that
and it was conjectured that this lower bound is the exact norm of the Hilbert matrix. This implies that it is necessary to have the following upper bound
to prove mentioned conjecture. The conjecture was confirmed [8] in the case when \(\alpha \ge 0\) and \(p\ge 2(\alpha +2)\), which reduces the conjecture in the case \(\alpha \ge 0\) to the interval \(\alpha +2<p<2(\alpha +2)\). When \(\alpha =0\) this was completely solved in [2] (see also [9]). Very recently, Lindström, Miihkinen and Wikman in [10] confirmed the conjecture in the case \(\alpha >0\) when
Among other things in this paper, we improved the previous result by confirming the conjecture in the case \(\alpha >0\) when
On the other hand, we note that in the case \(-1<\alpha <0\) there has been no progress so far in proving the conjecture, moreover, there is no even an explicit upper bound for the norm of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \). Finally, in this paper we also provide an explicit upper bound for the norm of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \) in the case \(-1<\alpha <0\) when \(p>\alpha +2\).
1.1 Basic Notation
Let \({\mathrm {D}}\left( z_0,r\right) =\left\{ z\in \mathbb {C}:\left| z-z_0\right| <r \right\} \) be the open Euclidean disc of radius \(r>0\) centered at the point \(z_0\) in the complex plane \(\mathbb {C}\). Let also \(\mathcal {H}(\mathbb {D})\) be the space of all holomorphic functions in the open unit disc \(\mathbb {D}={\mathrm {D}}(0,1)\). An annulus centered at the point \(z_0\) in the complex plane is defined as follows \({\mathrm {A}}(z_0,r,R)=\left\{ z\in \mathbb {C}: r<\left| z-z_0\right| <R\right\} \) where \(r<R\). The Euclidean area measure on the complex plane will be denoted by \({\mathrm {dm}}\), that is
Given a function f holomorphic in the unit disc \(\mathbb {D}\), then for \(0<p<\infty \) and \(0<r<1\), we consider its integral means of order p defined in the following way
It is well known that \(r\mapsto {\mathrm {M}}_p(r,f)\) is an nondecreasing function. This is a simple consequence of the subharmonicity of \(|f|^p\). The Beta function is defined by
where a and b are real numbers such that \(a>0\) and \(b>0\). If \(0<a<1\) then we will use the following well known formula
1.2 Hilbert Matrix and Weighted Bergman Spaces
The Hilbert matrix is an infinite matrix
If \(f(z)=\sum _{n=0}^\infty a_nz^n\) is a holomorphic function in the unit disc \(\mathbb {D}\), that is \(f\in \mathcal {H}(\mathbb {D})\), then the Hilbert matrix can be viewed as an operator on spaces of holomorphic functions in the following way
For \(0<p<\infty \) and \(\alpha >-1\) the weighted Bergman space is defined as follows
We note that if \(\alpha =0\) then \(A^p=A^p_0\) are standard unweighted Bergman spaces. It is well known (see [3, 4, 8]) that if a function f belongs to weighted Bergman space \(A^p_\alpha \) then we have
where
Recall that the Hilbert matrix \({\mathrm {H}}\) is bounded on weighted Bergman space \(A^p_\alpha \) if and only if \(1<\alpha +2<p\). In that case, by following [8], from the continuous version of Minkowski inequality we have estimate
and
where
In the rest of the paper we will use the following function
where \(0<t<1\). It is easy to check that
Therefore we conclude
The previous formula is valid for all \(1<\alpha +2<p\) and it will be used in the last section of this paper. On the other hand, following [8] in the special case when \(\alpha >0\) we obtain
By combining (1.2) and (1.3) we get
1.3 The Functions \(\Psi _\alpha \) and \(\Phi _\alpha \)
Let \(\alpha >0\). Then we define the functions \(\Psi _\alpha \) and \(\Phi _\alpha \) as follows
and
where \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). We note that these functions will play a crucial role in our paper. Next we obtain
for \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). Therefore
for every \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). This leads that function \(\Psi _\alpha '\) is increasing on interval \(\left( \alpha +2, 2(\alpha +2)\right) \). On the other hand, we find
Based on the above considerations we can conclude that it is valid
for every \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). Since
we have
for every \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). By straightforward calculations we also derive
for \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). Function \(\Phi _\alpha ''\) is increasing on interval \(\left( \alpha +2, 2(\alpha +2)\right) \) which implies
for every \(x\in \left( \alpha +2, 2(\alpha +2)\right) \). Hence function \(\Phi _\alpha '\) is also increasing on interval \(\left( \alpha +2, 2(\alpha +2)\right) \). This leads to
where \(x\in \left( \alpha +2, 2(\alpha +2)\right) \), whence it follows that \(\Phi _\alpha \) is an increasing function on interval \(\left( \alpha +2, 2(\alpha +2)\right) \). Then
This means that function \(\Phi _\alpha \) has a unique zero \(\alpha _0\) on the interval \(\left( \alpha +2, 2(\alpha +2)\right) \). Moreover, we get \(\Phi _\alpha <0\) on \(\left( \alpha +2, \alpha _0\right) \) and \(\Phi _\alpha >0\) on \(\left( \alpha _0, 2(\alpha +2)\right) \). The previous notation will be used in the rest of the paper.
1.4 The Main Results
Let \(\alpha >0\) and let \(\alpha _0\) be a unique zero of the function \(\Phi _\alpha \) on the interval \(\left( \alpha +2, 2(\alpha +2)\right) \). We are now ready to state the main results of the paper.
Theorem 1.1
Let \(\alpha >0\) and \(\alpha _0\le p<2(\alpha +2)\). Then \(\displaystyle \left\| {\mathrm {H}}\right\| _{A^p_\alpha \rightarrow A^p_\alpha }=\frac{\pi }{\sin \frac{(\alpha +2)\pi }{p}}\).
An immediate consequence we obtain the following result.
Corollary 1.1
Let \(\alpha >0\) and
Then
Proof
It is enough to prove that
Namely, the previous inequality implies
whence by Theorem 1.1 it follows the required conclusion. We can split the function \(\Phi _\alpha \) into two parts
where we denoted
and
Note that
So it is enough to prove
or equivalently
where \(a=\alpha +2\). This leads to
whence after squaring we get the following equivalent form
Since
it is enough to prove
which after some calculations reduces to
The last inequality is true, since
This completes the proof. \(\square \)
Remark 1.1
Note that Corollary 1.1 improves the last best known result recently obtained by Lindström, Miihkinen and Wikman in [10], where they get the same conclusion under the assumptions \(\alpha >0\) and
which was discussed earlier. \(\square \)
On the other hand, let
Then by straightforward calculations we obtain
which implies that \(\beta <\alpha _0\). In the case when \(\alpha >0\) and \(\alpha +2<p\le \beta \) we obtain the following partial result.
Theorem 1.2
Let \(\alpha >0\), \(\alpha +2<p\le \alpha +2+\sqrt{(\alpha +2)^2-(\alpha +2)}\) and suppose that the following condition holds
where we denoted
for \(0<t<1\). Then
Remark 1.2
We note that condition (1.5) is not always satisfied under the given conditions even when \(p/2-(\alpha +2)+1>0\), that is \(p>2\alpha +2\), which actually allows the convergence of the integral \(\xi _{p,\alpha }(0)\). Namely a calculation involving Mathematica shows that when \(\alpha =1\) then \(\beta \approx 5.449\) and \(\alpha _0\approx 5.487\) and also for
we have
On the other hand, if \(\alpha =1\) and \(\alpha +2<2\alpha +2<p=5.2<\beta <\alpha _0\) then
which allows the application of Theorem 1.2 in some cases where it is not possible to apply Theorem 1.1. We also have
and since \(\sqrt{2}-1/2\approx 0.914\) (actually \(\sqrt{2}-1/2> 0.914\)) we can write
From (1.6) we can conclude that there remains a small gap between \(\beta \) and \(\alpha _0\) to which we cannot apply the above Theorem 1.1 and Theorem 1.2. \(\diamond \)
Finally, in the case when
for the first time we obtain an explicit upper bound for the norm of the Hilbert matrix \({\mathrm {H}}\) on weighted Bergman spaces \(A^p_\alpha \). Namely, we have the following result.
Theorem 1.3
Let \(-1<\alpha <0\) and \(p>\alpha +2\).
-
(i)
If \(p\ge 2(\alpha +2)\) then
$$\begin{aligned} \left\| {\mathrm {H}}\right\| _{A^p_\alpha \rightarrow A^p_\alpha }\le 2^\frac{\alpha +2}{p}\frac{\pi }{\sin \frac{(\alpha +2)\pi }{p}}. \end{aligned}$$ -
(ii)
If \(\alpha +2<p<2(\alpha +2)\) then
$$\begin{aligned} \left\| {\mathrm {H}}\right\| _{A^p_\alpha \rightarrow A^p_\alpha }\le 2^\frac{\alpha +2}{p}\left( 1+2^{\frac{2(\alpha +2)}{p}-1}\right) \frac{\pi }{\sin \frac{(\alpha +2)\pi }{p}}. \end{aligned}$$
In the rest of the paper, we present the proofs of Theorem 1.1, Theorem 1.2, and Theorem 1.3.
2 Preliminaries
Let \(\alpha >0\) and \(\alpha +2<p<2(\alpha +2)\). We consider functions
where \(0<t<1\) as in the statement of Theorem 1.2. For \(s\in [0,1]\) we denote
As we will see later it is of interest to examine under what conditions the function \(F_{p,\alpha }\) is nonpositive on the segment [0, 1]. Let also
Then
Therefore
where we denote
We find
Hence
where
or equivalently
By differentiation we obtain
where
or
Next we can write
where we denote
Finally we obtain
and
Let
Note that
We denote the discriminant of the quadratic equation \(L_{p,\alpha }(s)=0\) by \(D_{p,\alpha }\). Then
or
Equivalently, we get
In view of Sect. 1.3 we have
where we used the fact that \(\alpha +2<p<2(\alpha +2)\) and inequality (1.4). This means that discriminant \(D_{p,\alpha }\) has the same sign as the factor
We actually have
Now we are ready to state our first preliminary result.
Lemma 2.1
Let \(\alpha >0\) and \(\alpha _0\le p<2(\alpha +2)\). Then \(F_{p,\alpha }(s)\le 0\) for all \(s\in [0,1]\).
Proof
Since \(\alpha _0\le p<2(\alpha +2)\) we have (see Sect. 1.3) that
which implies
On the other hand, since \(D_{p,\alpha }\) is a discriminant of a quadratic function \(L_{p,\alpha }\) given by (2.6) we can conclude that
By using Eq. (2.5) we get
which in turn implies that \(E_{p,\alpha }\) is nonincreasing function on [0, 1]. By Eq. (2.4) we obtain
Hence
Also
which leads to
Combining (2.7) and (2.8) we obtain
As we have already concluded that the function \(E_{p,\alpha }(s)\) is nonincreasing on [0, 1] we derive that there exists \(s_0\in (0,1)\) such that
From (2.3) we find that
Therefore the function \(G_{p,\alpha }\) is nondecreasing on \(\left[ 0,s_0\right] \) and nonincreasing on \(\left[ s_0,1\right] \). So we have
for all \(s\in [0,1]\). Since (see (2.2))
we get \(G_{p,\alpha }\ge 0\) on [0, 1]. From (2.1) we find \(F_{p,\alpha }'\ge 0\) on [0, 1] which implies that \(F_{p,\alpha }\) is nondecreasing function on [0, 1]. Finally
for all \(s\in [0,1]\). Since
we conclude that
for all \(s\in [0,1]\). This finishes the proof. \(\square \)
We need also the following preliminary result which will be used later.
Lemma 2.2
Let \(\alpha >0\), \(\alpha +2<p\le \beta =\alpha +2+\sqrt{(\alpha +2)^2-(\alpha +2)}\) and suppose that the following condition holds
Then \(F_{p,\alpha }(s)\le 0\) for all \(s\in [0,1]\).
Proof
Note that given condition
is actually equivalent to
In view of Sect. 1.3 we have
which implies
We also notice that
where we denote
The roots of the quadratic equation \(L_{p,\alpha }(s)=0\) are given by
Then
We also have
that is
From (2.10) and (2.11) we find
which leads to
Therefore
and
for \(s\in [0,1]\). It is also easy to see that
and
where we used the fact that \(p>\alpha +2>\alpha +2-\sqrt{(\alpha +2)^2-(\alpha +2)}\). Then we can consider the following two cases.
Case \(\varvec{\alpha +2<p<\beta }\) In this case from (2.14) we obtain that \(A_{p,\alpha }>0\). Hence
which implies \(\sqrt{D_{p,\alpha }}>-C_{p,\alpha }\) and \(\sqrt{D_{p,\alpha }}>C_{p,\alpha }\). Therefore
and by using (2.12) we have
Recall that \(L_{p,\alpha }(s)=-\left( s-x_{p,\alpha }\right) \left( s-X_{p,\alpha }\right) \) for \(s\in [0,1]\) (see (2.13)). So we get
By using (2.5) we have
We can conclude that function \(E_{p,\alpha }\) is nondecreasing on \(\left[ 0,X_{p,\alpha }\right] \) and nonincreasing on \(\left[ X_{p,\alpha },1\right] \). Therefore
We recall that (see (2.7))
which leads to
where we used the fact that \(A_{p,\alpha }>0\) in this case. Next we claim \(E_{p,\alpha }\left( X_{p,\alpha }\right) >0\). Assume to the contrary that \(E_{p,\alpha }\left( X_{p,\alpha }\right) \le 0\). This implies that \(E_{p,\alpha }(s)\le 0\) for all \(s\in [0,1]\). From (2.3) we get \(G_{p,\alpha }'\le 0\) on [0, 1]. Hence function \(G_{p,\alpha }\) is nonincreasing on [0, 1]. Since
we find that \(G_{p,\alpha }\equiv 0\) on [0, 1] which in turn implies \(G_{p,\alpha }'\equiv 0\) on [0, 1]. This leads to \(E_{p,\alpha }\equiv 0\) on [0, 1] (see again (2.3)). This is in a contradiction with (2.7), because formula (2.7) implies that function \(E_{p,\alpha }\) cannot be identically equal to zero on [0, 1]. In this way we have proved that
We have already proved that \(E_{p,\alpha }(0)=E_{p,\alpha }(1)<0\) and that \(E_{p,\alpha }\) is nondecreasing on \(\left[ 0,X_{p,\alpha }\right] \) and nonincreasing on \(\left[ X_{p,\alpha },1\right] \). Thus there exists \(s_1\in \left( 0,X_{p,\alpha }\right) \) such that
and there exists \(s_2\in \left( X_{p,\alpha },1\right) \) such that
So we obtain
By using (2.3) we find
Therefore function \(G_{p,\alpha }\) is nonincreasing on \(\left[ 0,s_1\right] \), nondecreasing on \(\left[ s_1,s_2\right] \) and nonincreasing on \(\left[ s_2,1\right] \). Since \(G_{p,\alpha }(0)=G_{p,\alpha }(1)=0\) there exists \(s_3\in \left[ s_1,s_2\right] \) such that
From (2.1) we can conclude that
Hence function \(F_{p,\alpha }\) is nonincreasing on \(\left[ 0,s_3\right] \) and nondecreasing on \(\left[ s_3,1\right] \). This implies that
for all \(s\in [0,1]\). By (2.9) we have \(F_{p,\alpha }(0)\le 0\) and since \(F_{p,\alpha }(1)=0\) we finally conclude that \(F_{p,\alpha }(s)\le 0\) for all \(s\in [0,1]\).
Case \(\varvec{p=\beta }\) It remains for us to consider what is happening in this case. From (2.14) we find that \(A_{p,\alpha }=0\). Hence we have \(D_{p,\alpha }=C_{p,\alpha }^2+4A_{p,\alpha }=C_{p,\alpha }^2\) and
which implies \(\sqrt{D_{p,\alpha }}=-C_{p,\alpha }\). Therefore
and by using (2.12) again we get
Since \(L_{p,\alpha }(s)=-\left( s-x_{p,\alpha }\right) \left( s-X_{p,\alpha }\right) \) for \(s\in [0,1]\) (see (2.13)) we find that
and by using (2.5) we have
Therefore we can conclude that function \(E_{p,\alpha }\) is nondecreasing on \(\left[ 0,X_{p,\alpha }\right] \) and nonincreasing on \(\left[ X_{p,\alpha },1\right] \). Recall that (see (2.7))
and since
we obtain
Let
It is easy to check that
because of \(\alpha +2>2\). Then
which implies that
Since \(1/2<c<2-\sqrt{2}\) we have
Therefore
We have also already proved that function \(E_{p,\alpha }\) is nondecreasing on \(\left[ 0,X_{p,\alpha }\right] \) and nonincreasing on \(\left[ X_{p,\alpha },1\right] \). Thus there exists \(S\in \left( X_{p,\alpha },1\right) \) such that
Then from (2.3) we obtain that
Hence the function \(G_{p,\alpha }\) is nondecreasing on \(\left[ 0,S\right] \) and nonincreasing on \(\left[ S,1\right] \). So we conclude that
for all \(s\in [0,1]\). On the other hand, since (see (2.2))
we obtain \(G_{p,\alpha }\ge 0\) on [0, 1]. Then from (2.1) we find \(F_{p,\alpha }'\ge 0\) on [0, 1] which implies that \(F_{p,\alpha }\) is nondecreasing function on [0, 1]. Therefore \(F_{p,\alpha }(s)\le F_{p,\alpha }(1)\) for all \(s\in [0,1]\). Since
we have that \(F_{p,\alpha }(s)\le 0\) for all \(s\in [0,1]\). On the other hand, note that in this case it was not necessary to further assume at the beginning that inequality (2.9) is valid. This completes the proof. \(\square \)
Remark 2.1
It will be interesting to see what happens in the case when \(\beta<p<\alpha _0\). Then we can apply the same procedure as in the proof of Lemma 2.2. Namely, in this case from (2.14) we conclude that \(A_{p,\alpha }<0\). Therefore from (2.7) we obtain
On the other hand, we have
and \(D_{p,\alpha }=C_{p,\alpha }^2+4A_{p,\alpha }<C_{p,\alpha }^2\) which implies \(\sqrt{D_{p,\alpha }}<-C_{p,\alpha }\). Hence
and by using (2.12) we get
This already complicates the determination of the sign of the quadratic function \(L_{p,\alpha }(s)\) on the interval [0, 1] and proceeding further similarly as in the proof of Lemma 2.2, it turns out that it is not easy to conclude under which conditions the function \(F_{p,\alpha }(s)\) is nonpositive on the interval [0, 1] in all possible cases. \(\diamond \)
3 Proofs of Theorem 1.1 and Theorem 1.2
Let us first consider the case when \(\alpha >0\) and \(\alpha +2<p<2(\alpha +2)\). Later we will focus on the special cases when \(\alpha _0\le p<2(\alpha +2)\) or \(\alpha +2<p\le \beta \) as in the statements of Theorem 1.1 or Theorem 1.2, respectively. Let \(f\in A^p_\alpha \). In view of (1.1) we have the corresponding lower bound, so we need to prove
We will use the technique developed in the paper [2]. Denote
for \(0\le r<1\). Of course, functions \(\varphi \) and \(\chi \) depend on the choice of the initial function f which we assume to be fixed in the considerations that follow. Then \(\varphi \) is nondecreasing and differentiable function on the interval (0, 1), which implies that function \(\chi \) is also nondecreasing and differentiable on (0, 1). Therefore
for \(0\le r<1\). As shown in Sect. 1.2 we know that
and
where
Note that it is valid
We denote
Consequently
or equivalently
On the other hand
Because of (3.3), (3.4) and (3.5), we can conclude that (3.1) holds if the following inequality is true
where
and
Note that \(I_{p,\alpha }(t)\) and \(J_\alpha \) also depend on the function \(\varphi \), that is on the function f that was initially selected. We obtain
where we used the well known fact that \(x^\gamma -y^\gamma \le \gamma y^{\gamma -1}(x-y)\) for \(x\ge 0\), \(y\ge 0\) and \(\gamma \in (0,1)\) as well as the fact that it is valid \(1/p\in (0,1)\) because of \(p>\alpha +2>2\). Thus we have that (3.6) holds if the following inequality is true
or
or equivalently
where we denoted
and
and
Then by using a change of variable \(\rho =r^2\) we get
On the other hand by using Fubini theorem we obtain
and by using change of variable \(s=u/(2-u)\) we get
or equivalently
This implies that
or
Similarly we have
which leads to
or equivalently
Based on the foregoing considerations we can conclude
Finally to obtain (3.7) it is enough to prove that
Note also that \(\varphi (0)=2|f(0)|^p\). So we can conclude the following. In the case when \(\alpha >0\) and \(\alpha +2<p<2(\alpha +2)\) if
then it is valid inequality (3.1). Now we are ready to prove Theorem 1.1.
Proof of Theorem 1.1
Let \(f\in A^p_\alpha \) where \(\alpha >0\) and \(\alpha _0\le p<2(\alpha +2)\). In view of (1.1) it is enough to prove that inequality (3.1) is valid. By using Lemma 2.1 we have that
for all \(u\in [0,1]\). From (3.2) we conclude that
Combining (3.9) and (3.10) we obtain
which leads that inequality (3.8) is valid. This implies that inequality (3.1) is also valid, which completes the proof. \(\square \)
Next we will use the previously presented results as well as Lemma 2.2 from Sect. 2. Thus we are ready to prove Theorem 1.2.
Proof of Theorem 1.2
Let \(f\in A^p_\alpha \) where \(\alpha >0\) and \(\alpha +2<p\le \beta \). We can use Lemma 2.2, because we know that under the assumptions of Theorem 1.2 the following condition is satisfied
Therefore
for all \(u\in [0,1]\). Since \(\chi '\ge 0\) we derive that
which implies validity of the inequality (3.1). This finishes the proof. \(\square \)
4 Proof of Theorem 1.3
In this section we consider the case when \(-1<\alpha <0\) and \(p>\alpha +2\). Let also \(f\in A^p_\alpha \). As we showed in Sect. 1.2 we have
and
where
Let
Note that \(\eta _t(\mathbb {D})={\mathrm {D}}_t\subset \mathbb {D}\). We will also use the following well known result, which is a consequence of Littlewood Subordination Principle (see Chapter 11 in [12]).
Lemma 4.1
(see Theorem 11.6 in [12]) If \(\eta :\mathbb {D}\rightarrow \mathbb {D}\) is holomorphic function, \(p>0\) and \(\alpha >-1\) then
for all holomorphic functions f on \(\mathbb {D}\).
After the preliminary results mentioned above, we are now ready to prove Theorem 1.3 from the Sect. 1.4.
Proof of Theorem 1.3
Let \(f\in A^p_\alpha \). Then we consider the following two cases as in the statement of Theorem 1.3.
Case (i) \(\varvec{p\ge 2(\alpha +2)}\) In this case we actually have that \(|w|^{p-2(\alpha +2)}\le 1\) for all \(w\in {\mathrm {D_t}}=\eta _t(\mathbb {D})\). Therefore
After change of variable \(w=\eta _t(z)\) we obtain
Since
by using Lemma 4.1 we obtain
Hence we conclude
or
Note that
for all \(0< t< 1\). This leads to
Finally we obtain
Therefore
Case (ii) \(\varvec{\alpha +2<p<2(\alpha +2)}\) In this case we have
Therefore
This implies that \(\left\| {\mathrm {T}}_tf\right\| _{A^p_\alpha }\) is not greater than
Similar to the Case (i) we get that it is valid
which leads to
Hence we obtain
On the other hand, we have
where we actually used the known fact which states that the following inequality is valid
for all \(x\ge 0\), \(y\ge 0\) and \(\gamma \in (0,1)\) as well as the fact that
because of \(\alpha +2<p<2(\alpha +2)\). So we get
or
From (4.1) and (4.2) we obtain
Since
we find
Finally we obtain
This completes the proof. \(\square \)
References
Aleman, A., Montes-Rodríguez, A., Sarafoleanu, A.: The eigenfunctions of the Hilbert matrix. Constr. Approx. 36, 353–374 (2012)
Božin, V., Karapetrović, B.: Norm of the Hilbert matrix on Bergman spaces. J. Funct. Anal. 274, 525–543 (2018)
Diamantopoulos, E.: Hilbert matrix on Bergman spaces. Ill. J. Math. 48, 1067–1078 (2004)
Diamantopoulos, E., Siskakis, A.G.: Composition operators and the Hilbert matrix. Stud. Math. 140, 191–198 (2000)
Dostanić, M., Jevtić, M., Vukotić, D.: Norm of the Hilbert matrix on Bergman and Hardy spaces and theorem of Nehari type. J. Funct. Anal. 254, 2800–2815 (2008)
Galanopoulos, P., Girela, D., Peláez, J.A., Siskakis, A.G.: Generalized Hilbert operators. Ann. Acad. Sci. Fenn. Math. 39, 231–258 (2014)
Jevtić, M., Karapetrović, B.: Hilbert matrix on spaces of Bergman-type. J. Math. Anal. Appl. 453, 241–254 (2017)
Karapetrović, B.: Norm of the Hilbert matrix operator on the weighted Bergman spaces. Glasgow Math. J. 60, 513–525 (2018)
Lindström, M., Miihkinen, S., Wikman, N.: Norm estimates of weighted composition operators pertaining to the Hilbert matrix. Proc. Am. Math. Soc. 147, 2425–2435 (2019)
Lindström, M., Miihkinen, S., Wikman, N.: On the exact value of the norm of the Hilbert matrix operator on the weighted Bergman spaces, to appear in Ann. Acad. Sci. Fenn. Math. (https://arxiv.org/abs/2001.10476)
Magnus, W.: On the spectrum of Hilbert’s matrix. Am. J. Math. 72, 699–704 (1950)
Zhu, K.: Operator Theory in Function Spaces, Second Edition, Mathematical Surveys and Monographs 138. American Mathematical Society, Providence, RI (2007)
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Karapetrović, B. Hilbert Matrix and Its Norm on Weighted Bergman Spaces. J Geom Anal 31, 5909–5940 (2021). https://doi.org/10.1007/s12220-020-00509-9
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DOI: https://doi.org/10.1007/s12220-020-00509-9