1. Introduction
Mathematical inequalities are vital tools in mathematics, supporting results in analysis, geometry, and operator theory [
1,
2,
3,
4,
5]. They offer bounds and relationships that drive theoretical and applied advances, as seen in studies of Schwarz, Bessel, and Selberg inequalities [
6,
7]. This study, motivated by the role of inequalities in linking mathematical concepts, presents a new proof of Selberg’s inequality and explores extensions to enrich inequality theory [
8,
9].
In 1821, Augustin-Louis Cauchy introduced an inequality for real numbers [
10]:
with equality if and only if there exists
such that
for each
. In 1859, V. Y. Bunyakovsky gave its integral form [
11]. Later, H. A. Schwarz extended it to inner-product spaces, known as Schwarz’s inequality.
Let
be a complex Hilbert space with inner product
and norm
. The Cauchy–Bunyakovsky–Schwarz inequality (CBSI) states
for all
, with equality if and only if there exists
such that
. This inequality is widely used in mathematics [
7].
Many extensions of the CBSI exist. In [
12], M. L. Buzano proved an extension called Buzano’s inequality (BuI):
Lemma 1 ([
12,
13,
14])
. For any , the following holds:If is linearly independent, equality in (1) holds for if and only if for some scalar α, where . If is linearly dependent, equality holds for for some scalar α. For more on the CBSI and its extensions, see [
7,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24].
Another inequality related to the CBSI is the well-known Bessel’s inequality (BeI). For any orthonormal vectors
in
and any
[
4]
Selberg’s inequality (SI), a generalization of BeI, was introduced by A. Selberg [
4]. For vectors
with
for all
, it states
Furuta described the equality case in [
25]: equality holds if and only if
for complex scalars
, with
or
and
for
.
The paper is organized as follows. In
Section 2, we recall the necessary background and present a new proof of Selberg’s inequality (see (
2)), by deriving an operator-norm estimate for the associated Selberg operator acting on a Hilbert space. In
Section 3, we develop several alternative lower and upper bounds for the left-hand side of (
2).
Section 4 is devoted to applications of our main estimates to two classical results: de Bruijn’s inequality and Bohr’s inequality. Finally, in
Section 5, we offer a brief digression toward a vector-space generalization, extending Selberg’s framework to bilinear functionals on abstract vector spaces.
2. A New Proof of Selberg’s Inequality
In this section, we assume that
is a complex, infinite-dimensional Hilbert space. The
-algebra of all bounded linear operators on
is denoted by
, equipped with the usual operator norm, defined for each
by
Given an operator
, its adjoint is denoted by
, and the identity operator on
is denoted by
I. An operator
T is said to be self-adjoint if
. In particular, a positive operator is a self-adjoint operator that satisfies
for all
; we write
in this case. Moreover, for self-adjoint operators
T and
S, we write
if
, that is, if
is a positive operator. It is well known that if
T is a self-adjoint operator, then
Lemma 2. Let such that , then the operator Cauchy–Bunyakovsky–Schwarz inequality holds:for any . Additionally, we can derive the following consequence:which holds for any positive operator T and . Proposition 1. Let be a self-adjoint operator such that there exists a positive number Cfor any , then Proof. From the inequality (
3), we have that
or equivalent as
T is a self-adjoint operator, such that
Taking the supremun over all
with
, we obtain
Then, we conclude that □
For the subsequent discussion, it is important to recall that the expression represents a rank one operator defined by , where x, y, and z are vectors in the space . Now, we introduce the Selberg operator defined as follows:
Definition 1. Given a subset of nonzero vectors in the space , the Selberg operator is defined by We now offer a novel derivation of (SI), which also illustrates the optimality of certain norm estimates for positive operators. The approach is based on the properties of the operator together with Proposition 1, yielding a concise and elegant argument.
Theorem 1. Let be a subset of nonzero vectors in the Hilbert space . Then, the following inequality holds:for every . Proof. Using the Selberg operator, we can rewrite (SI) in the form
for any
.
To establish (SI), it is, therefore, sufficient to show that the Selberg operator associated with
is a positive contraction; that is,
for any subset
consisting of nonzero vectors.
Observe that the positivity of the Selberg operator is immediate since it is defined as a sum of positive operators.
On the other hand, for any
, we have
Note that for non-negative real numbers
and
for all
, the following identity holds:
In particular, if we consider the quantities
and
defined by
then we obtain
By applying (
5) to inequality (
4), we obtain
Using Proposition 1, we conclude that
. Since
is a positive operator, we have
and, therefore,
for all
, which completes the proof. □
Remark 1. It is immediately evident that the classical Cauchy–Bunyakovsky–Schwarz inequality (CBSI) in an inner product space can be derived from the Selberg inequality (SI). However, from the previous proof, we observe that the converse also holds: the CBSI implies the SI. In conclusion, both inequalities are equivalent and can be derived from one another. This equivalence was previously observed in [26] [Theorem 23], although established there using a completely different argument. 4. Applications: Refinements of de Bruijn’s and Bohr’s Inequalities
In this section, we highlight the strength and significance of the inequality—and its generalization—recently established by some of the authors of this work. In particular, we show that this result enables the recovery of a refined version of the Cauchy–Schwarz inequality, originally introduced by de Bruijn in 1960 [
30].
We begin by recalling a result that serves as a simultaneous extension of both the Selberg and Buzano inequalities, obtained by Fujii et al. [
14] [Theorem 2.3]. Let
be a collection of nonzero vectors in a Hilbert space
, and let
be vectors orthogonal to each element of
; that is,
for all
. Under these assumptions, the following inequality holds for all
:
where the constant
is defined by
Now, we derive a refinement of de Bruijn’s inequality. To this end, we begin by presenting a preparatory result that will play a key role in establishing a refined version of de Bruijn’s inequality. This auxiliary statement, which builds on additional orthogonality assumptions, provides a sharper variant of (CBSI).
Lemma 3. Let be elements of a Hilbert space such that and . Let be a collection of nonzero vectors in satisfying for all . Then, the following inequality holds: Furthermore, if the set is linearly independent, the equalityis satisfied for if and only if for some scalar α, where . Conversely, if is linearly dependent, the equality in (17) holds for if and only if for some scalar α. Proof. Using the hypothesis, we conclude that
Finally, we obtain the equality in the previous inequality if and only if we have the equality in Buzano’s inequality. Then, we complete the proof from Lemma 1. □
We present a new proof of de Bruijn’s inequality, together with a refinement based on the preceding result.
Corollary 3. Let be a sequence of real numbers and a sequence of complex numbers. Suppose that is a collection of nonzero vectors in such that Then, the following inequality holds: Moreover, equalityholds if and only if there exists such that for all , and . Proof. We consider
as a Hilbert space equipped with the standard inner product
where
and
are elements of
.
Let
,
, and
be vectors in
. Then, it holds that
and the inner products satisfy
Now, we obtain
and for each
,
as well as
Substituting all of this into inequality (
16), we obtain
On the other hand, by Lemma 3, we conclude that the equality (
18) holds if and only if
for some scalar
, where
, if the set
is linearly independent. Conversely, if
is linearly dependent, the equality in (
18) holds if and only if
for some scalar
.
We will consider the following cases to obtain a clearer characterization of the de Bruijn equality.
Suppose that
is linearly dependent. Then, the equality in (
18) holds if and only if
for some scalar
.
Since
, for each
, we obtain
which implies that
.
Moreover, the inner product of
with itself yields
In conclusion, taking
satisfies the desired condition for the equality in (
18) to hold in the case where
is linearly dependent.
We assume that
is linearly independent. Thus, for any
, we have
then
and this implies,
From the linear indepedence of the set
, we obtain that
and
where
Let
with
. From the equality (
19), we obtain
this means that
.
Finally, we conclude that
and this completes the proof.
□
One of the earliest and most celebrated estimates in complex analysis is Bohr’s inequality [
31]. It asserts that whenever
and
satisfy
then
Moreover, equality in (
20) occurs precisely when
.
In a natural extension to
n terms, Archbold [
32] showed that if
and positive weights
satisfy
, then
Building on these classical results, we have recently obtained (via de Bruijn’s inequality) a sharper bound that refines (
21) (see [
33] [Theorem 1]). As a direct consequence of our new Corollary, no further proof is required to establish the following statement:
Corollary 4. Let be a sequence of complex numbers and be a sequence of positive numbers such that . Suppose that is a collection of nonzero vectors in such thatThen, Proof. Let us begin by noting that
Now, by replacing each
with
and each
with
, we are effectively under the assumptions of Corollary 3. Furthermore, since
, it follows that for any
,
□
5. A Critical Note on the Selberg Inequality Involving Bilinear Functionals
A natural idea in extending classical inequalities from inner product spaces to more general contexts is to consider replacing the inner product with a bilinear functional. In particular, one might attempt to generalize the Selberg inequality by formulating it in terms of a bilinear functional, possibly subject to additional assumptions such as boundedness, symmetry, or positivity. However, since many of the key inequalities in Hilbert spaces are deeply rooted in the specific properties of the inner product—such as conjugate symmetry and positive definiteness—this type of generalization is not straightforward and warrants a critical examination.
Recently, some authors have proposed a generalization of the Selberg inequality within this framework by extending its formulation to the setting of bilinear functionals. While the motivation behind such an extension is understandable, we shall show that the proposed inequality does not hold in full generality, and, in fact, its validity can be critically questioned under the assumptions given.
To that end, we begin by recalling the basic notions involved in such formulations (see [
2] [Section 4.3]).
Definition 2. A bilinear functional φ on a complex vector space E is a function that satisfies linearity in the first argument and conjugate linearity in the second argument. More precisely, for any scalars and vectors , the following holds:
- 1.
.
- 2.
.
Furthermore,
- 3.
φ is called symmetric if for all .
- 4.
φ is called positive if for any
Let us recall the result recently obtained by Izadi et al. regarding the Selberg-type inequality in the context of a vector space endowed with a bilinear functional; see [
34] [Theorem 3.1].
Statement. Let E be a vector space. Then, for all and nonzero vectors , the inequalityholds. Equality occurs if and only ifand for each pair , , However, it is important to point out that both the statement and the proof presented by the authors in [
34] closely follow an argument originally due to Furuta [
25], without due acknowledgement. More significantly, there are several issues in the formulation and justification of the inequality as stated.
To begin with, if one assumes that
E is an inner product space and that
, then the inequality stated in (
23) does not align with the classical formulation of Selberg’s inequality. While part of the discrepancy can be attributed to typographical errors—such as the omission of modulus signs or squared terms in the expression—there are also more fundamental issues arising from the structural properties of the bilinear functional
, which we now examine.
In addition, for inequality (
23) to be meaningful and for both sides to be directly comparable, all involved terms must be real numbers. This, in particular, implies that the bilinear functional
must be symmetric; see [
2] [Theorem 4.3.9].
Moreover, upon examining the proof provided in [
34], one notices that the authors begin by assuming that
for all
; that is, they implicitly assume that
is a positive (or positive semi-definite) bilinear form.
In light of these observations, the correct version of the result—both in mathematical substance and logical accuracy—requires that be a symmetric and positive bilinear form. The properly stated inequality is presented below. Its proof follows from the original argument given by Furuta or from the approach proposed by Izadi et al., with the necessary corrections and clarifications incorporated.
Theorem 5. Let E be a vector space, and let φ be a symmetric, positive bilinear functional on E. Suppose is a finite collection of vectors such that for any . Then, for all , Proof. Let
be arbitrary complex coefficients. Then, we consider the following quadratic form:
By applying the triangle inequality and estimating the last double sum in absolute value, we obtain
In the second inequality, we used the following well-known identity: for any finite sequence of complex (or real) numbers
and any symmetric matrix
with non-negative real entries (i.e.,
for all
), it holds that
This is a valid definition since, by assumption, there exists at least one pair with , so at least one denominator is positive.
Substituting this choice into the inequality, we find
Consequently, we conclude the desired inequality:
This finishes the proof. □
We now emphasize that the equality condition stated in [
34] [Theorem 3.1] does not necessarily hold.
Example 1. Consider the sesquilinear form φ, defined byand let , where However, this example does not satisfy the characterization of equality claimed in (23), which states that the equalityholds if and only if x can be written as a linear combinationand for each pair , with , either In this case, although is a linear combination of and with coefficients , , we findwhich violates the non-negativity condition. Therefore, this example shows that the equality in (23) may hold even when the stated necessary and sufficient conditions fail. This illustrates that the characterization claimed in [34] [Theorem 3.1] does not hold in general. Moreover, since the form φ is positive but not positive definite, one can find a nonzero vector x outside of the linear span of such that the equality still holds. For instance, consideri.e., the vector having 1 in every odd-indexed position and 0 elsewhere. Clearly, since it has nonzero entries beyond positions 1 and 2. Moreover, since all the even-indexed entries of x vanish, we have Hence,but . This confirms that in the presence of a nontrivial kernel of φ, the equality can hold even when x is not in the span of the given family. Before proceeding with an refinement of the Selberg inequality (SI) to the setting of bilinear functionals, let us first recall some classical results that hold in this context. For the reader’s convenience, we include the proof of one such result.
Lemma 4. Let E be a vector space, and let φ be a symmetric, positive, bilinear functional on E. Then, for any , the following holds:
Proof. For inequality (1), we refer the reader to [
2] [4.12, Exercise 5].
We prove only part (2). First, observe that if , then the inequality holds trivially. Indeed, by (1), this implies , and hence both sides of the inequality vanish.
Thus, we may assume
and define
. Then,
□
It is worth noting that the inequalities in Lemma 4 extend both the classical (CBSI) and (BuI) to the framework of a vector space endowed with a bilinear functional, subject to the conditions stated therein.
We conclude this article by presenting a simultaneous extension of the classical Buzano and Selberg inequalities in the context of bilinear functionals. This result is obtained by adapting the general strategy developed in [
14]. For conciseness, and since the proof follows closely the ideas therein, we omit the details.
Proposition 2. Let E be a vector space and φ a semi-inner product defined by E, such that for any and with for any and . Then, for all , we havewhere Remark 3. Finally, we would like to emphasize that our previous results for symmetric, positive bilinear functional are not fruitless generalizations of the inner product case but generating some interesting results for operators in Hilbert space.
Consider the self-adjoint operator P such that in the operator order of . Define by We observe that φ is a symmetric, positive bilinear functional on
From the second inequality in Lemma 4, we obtain the following generalized version of Buzano’s inequality:for all This is a sharp inequality since for , we recapture the classical Buzano result. Now, if we take instead of y, , we obtainfor all or, equivalently,for all Further, if we take the supremum over and observe thatandthen we obtain the following vector norm inequalityfor all This is a kind of vector norm operator version of Buzano’s inequality. Moreover, if we take the supremum over then we obtain the norm operator inequalitywhich, in the case that givesnamely,