"A proof that it is true for every interesting solution would shed light on many of the mysteries surrounding the distribution of prime numbers."([10])
1. Introduction
The task is to prove that
where
is the integral operator in the Alcantara-Bode equivalence having the kernel
defined by the fractional part of the ratio
:
The main result (see an earlier formulation in [8], Theorem 1) states: an linear, bounded operator on a separable Hilbert space strict positive on a dense set, is injective.
To make it useful for practical purposes, we consider the dense set as the union of finite dimension subspaces organized in a multi-level (multigrid) structure on which we could define approximations of the linear operator. If on such subspaces the operator approximations are (strict) positive definite, then the operator has not zeros in the dense set and so, we could define the rules for the injectivity based on the relationship between the residuum of the eligible zeros of the operator and the operator positivity parameters on subspaces. When the subspaces are spanned by indicator interval functions having disjoint supports, we could interpret the method obtained as a ’degenerate’ finite element method on a multigrid architecture. As result, the matrix representation of an integral operator on a such subspace is sparse diagonal, whose minimum valued entry is used in the definition of the operator positivity parameter. If such parameter sequence is bounded, the injectivity of the operator is obtained due to an impossible relation between the potential zeros of the operator and the positivity parameters on the approximation subspaces.
2. Two Generic Theorems of Injectivity
Let H be a separable Hilbert space and T be a linear bounded operator on H positive definite on a dense set , . Then T has no zeros in S and its ’eligible’ zeros are all in the difference set , i.e. . The next theorem (see also an earlier version in [8]) proved that if T strict positive definite on the dense set then it has no zeros in the difference set either, obtaining .
Theorem 1. A linear bounded operator T strict positive definite on a dense set of a separable Hilbert space is injective, equivalently .
Proof.
Let’s take in consideration only the set of eligible zeros that are on the unit sphere without restricting the generality, once for an element
and for
both are or both are not in
. The set
is dense if its closure coincides with
H. Then, if
, for every
there exists
such that
. Then
Consider
w an eligible element from the unit sphere,
.
Given , there exists at least one element in the dense set such that holds. Follows from (2), taking : ∣ 1 - showing that, for any choices of the sequence approximating w, , the sequence with .
If T is a linear bounded operator on H strict positive on S, then there exists such that , .
Suppose that there exists
a zero of
and consider a sequence of approximations of
w,
that, as we showed, is converging in norm to 1. From the positivity of
T on the dense set
S, follows:
With c=
, we obtain
. Then,
with
, in contradiction with its convergence to 1. Or, this happen for any choice of the sequence of approximations of
w, verifying
, when
. Thus
, valid for any
, proving the theorem because no zeros of
T there are in
S either.
Suppose that the dense set S is the result of a union of a family F of finite dimension subspaces: . It is not mandatory but will ease our proofs considering that the subspaces are including: . In fact, that happen with the family of indicator interval functions in by halving the mesh of the partitions of the domain (0,1): .
Observation 1. Let be the normed residuum of the eligible element after its orthogonal projection on . Then, with .
Proof.
Given , from the density of the set S in H there exists verifying , as per the observations made above in the proof of the Theorem 1. Let be the coarsest subspace, i.e. with the smallest dimension, from the family of subspaces containing . Because the best approximation of u in is its orthogonal projection, we obtain
,
inequality valid for every , proving our assertion. □
For T a linear bounded operator strict positive on each subspace , there exists a sequence of positivity parameters such that . Being strict positive definite on every finite dimension subspace of the family, the operator has no zeros in the family subspaces and, its zeros if there are, are in the difference set . Denoting the orthogonal projection of an eligible u onto there exists due to the density of S, such that for any n and, .
Let be an generic Hilbert-Schmidt integral operator on a separable Hilbert space H. Because a such operator is compact, it can be approximated by finite rank integral operators. If is an orthogonal projection operator, then the finite rank approximations of our operator denoted by , verifies for .
A sufficient condition for an Hilbert-Schmidt integral operator to verify the generic injectivity theorem is given below.
Theorem 2. Let be an Hilbert-Schmidt integral operator on a separable Hilbert space and the dense set be the union of the finite dimension subspaces . If the positivity parameters of finite rank approximations on a dense family of including subspaces is inferior bounded, i.e. there exists such that , then is injective, equivalently its null space is .
Proof.
Let be the integral operator on H and its sequence of finite rank operator approximations on the family F of subspaces. Suppose and there exists such that where are the positivity parameters of the finite rank approximations , , satisfying . We will split the proof in two parts: one, showing that the operator has no zeros in the dense set and next, it is itself strict positive definite on the dense set verifying the requests of the Theorem 1.
A) If there exists a zero of T in then it should be in one of the subspaces of F, i.e. there exists , such that . Then:
i.e. for the zeros of T in the dense set, . Because T is an Hilbert-Schmidt operator, it is compact, so with . Follows: with , that is a contradiction, showing that .
B) Now, from the convergence to zero of the sequence there exists a compactness parameter verifying corresponding to a subspace . The compactness parameter depends only on the Hilbert-Schmidt operator, so is independent from any .
Given there exists a subspace . If then from the including property of the subspaces of the family, . Follows for :
where . Then, with we obtain the strict positivity of the operator on the dense set S: for very .
Thus , by applying Theorem 1. □
Observation. The integral operator in (1) is a Hilbert-Schmidt on ([2]) and so, compact. Taking the dense family as the union of the finite dimension subspaces spanned by the indicator interval functions of the semi-open disjoint intervals of length h in (0,1), we showed in section 5.A) (Theorem 3) that using a finite rank discretization like in [5], the positivity parameters of the finite rank operator approximations are all constant (10), where is the Euler-Mascheroni constant. So, the integral operator in (1) is injective. Thus, by Alcantara-Bode equivalence RH holds. For ones interested only in the proof of RH, the rest of the article could be skipped.
3. The Associated Methods
Our hypothesis in the previous theorem has been the existence of a bound for the finite rank operator positivity parameters. But, an linear,bounded operator strict positive definite on every finite dimension subspace of the family, has no zeros in the family subspaces and, with or without a bound of the positivity parameters, its zeros if there are, should be in the difference set .
Then, we have to take in consideration the case in which the sequence converges to zero and, another case when instead of the finite rank operator approximations we will take simply, the restrictions of the linear bounded operator on the finite dimension subspaces .
The relationship between the residuum on finite dimension subspaces of the eligible zeros and the operator positivity parameters on these subspaces is exploited in defining the methods for investigation of its injectivity: the finite rank operator approximations and the operator restrictions methods.
Lemma 1. (Corollary of the Theorem 2) Let T have its sequence of the finite rank operator approximations be strict positive on the subspaces : , where for . Then T is injective.
Proof. For , having the not null orthogonal projections , from Observation 1 we have its residuum sequence on the approximation subspaces .
If , we obtain:
.
Then:
where and . The inequality is violated from an , meaning, , for any zero of T in E. Once T has no zeros in the dense set, . □
Lemma 2. (Injectivity Criteria) Let T be a linear bounded operator strict positive on each subspace , , . Suppose that and for every .
If then T is injective.
Proof. Suppose that there exists , . Then, from the strict positivity of T on the subspaces (see (3)):
then, from
where , we obtain a contradiction. Thus, for any . Follows: . □
Note. With these two lemmas, we have an unitary view on the methods through the relationship between the residuum on finite dimension subspaces of the eligible zeros and the corresponding operator positivity parameters. Moreover, if there exists such that for , then in Lemma 2 we could remove the involvement of the adjoint operator approximations observing that or from:
and the injectivity of the operator is coming by replacing the parameter with the operator or its adjoint norm. So, we could see Lemma 1 as a particular case of Lemma 2. With these lemmas, we also fixed a flaw in the injectivity criteria introduced in [1], mentioning that at that time we did not have the generic theorem of injectivity (Theorem 1) that has been introduced later ([8]).
4. Dense Sets in
The intervals of equal lengths , nh = 1, together with define for a partition of (0,1), k=1,n, .
Consider the interval indicator functions having the supports these intervals (k=1,n)
The family
F of finite dimensional subspaces
that are the linear spans of interval indicator functions of the h-partitions defined by (4) with disjoint supports,
, built on a multi-level structure, are including
by halving the mesh h. In fact, due to (4) any
is embedded in
by
for any
, k=1,n, nh=1 (or 2nh/2=1). So,
where
. The family
F will be used for finite rank approximations as in [5].
Let be the set of open intervals that differ from the semi-open intervals of the defined partitions only by the end-points . Then, denoting with the interval indicator functions, in , for . Let observe that for any partition of size h, the points in which are the right endpoints in the partition of the interval (0,1) and, their collection is of the Lebesgue measure zero. Thus, for any kernel function because any pair is orthogonal because of their disjoint supports , we have: for .
Then )(y). So, denoting , for k=1,n, nh=1, we obtain
=
=
Denoting by the family of the finite dimension subspaces that are linear span of indicator open-interval functions we have: is dense if and only if S is dense.
Proof. Suppose that is dense, well known in literature. If there exists such that then
, meaning f is orthogonal to any element from the dense set and should be zero. Thus, S is dense. In the same manner, supposing dense we obtain S dense. □.
Now, because any pair is orthogonal because of their disjoint supports , given an integral operator on its matrix representation on the subspaces and generated by the families of the corresponding indicator interval functions are both sparse diagonal matrices coincides having the diagonal entries the only difference consisting in the orthonormality factor introduced with the finite rank approximations, as we will see later: .
5. RH Holds
The integral operator defined in (1) having the kernel function continuous everywhere on excepting a set of measure Lebesgue zero - it is a countable set of unidimensional lines in of the form y = kx, k - is a linear, bounded, Hilbert-Schmidt operator ([2]) and so, compact.
Then, it could be approximated by projections on the finite dimension subspaces (see also [3]) of the .
A. Finite rank operator approximations.
Below, we follow the steps from [5] for defining the orthogonal projection of the integral operator
by finite rank integral operators considering the dense set
S the union of the including finite dimension subspaces spanned by indicator semi-open interval functions (4) as follows. The orthogonal projections of the kernel function are performed by the finite rank integral operators ([5], pg. 986) whose kernel functions are:
As result, the integral operator projection on
,
has the kernel function ([5])
that is a sum of kernel pieces with disjoint supports in which
are taken to be 0 for
as a consequence of the property of the basis: any pair from the basis on the subspace
is orthogonal due to their disjoint supports. Thus, the matrix representation of the finite rank operator approximation
is a sparse diagonal matrix
, where
From
, like in [1] for
,
The values of the entries
are given in ([1]):
for
, where
is the Euler-Mascheroni constant.
The sequence
is monotone decreasing for
and converges to 0.5 for k
. Then:
. Follows:
Theorem 3. The Riemann Hypothesis holds.
Proof.
From (10), the positivity parameters of the finite rank operator approximations on the dense family F are inferior bounded, obtaining from Theorem 2 or Lemma 1 that . Invoking the Alcantara-Bode’s equivalence, the Riemann Hypothesis holds. □
B. Operator restrictions on subspaces. Using this method, we will consider the the dense set of indicator open interval functions .
Having the convergence to zero of the residuum, see Observation 1, next step is to compute the positivity parameters of our operator on the approximation subspaces. For this, we have to evaluate the inner product between and where is the not null orthogonal projection of an eligible .
Denoting with the orthogonal projection onto , then:
holds. Or,
With the basis
on the linear span
the matrix representation of the integral operator
is a sparse diagonal because the orthogonality of the basis elements is a consequence of the disjoint supports between any pair
:
. Then, the matrix
has the diagonal entries
given by (9).
In fact, applying (11), as per
=
. So,
that we already knew, valued in (9). Follows for
:
again and, we will define
observing that .
The value of the positivity parameter of the operator defined on , remains unchanged for any as per following estimations: let then applying (11) to in order to evaluate the inner product as we will do now:
.
So, we are able to compute the inner product in :
,
Thus, for :
. Or,
that becomes:
. Then, we have to evaluate
.
We could observe that is strict positive definite on any but, on S it is only positive definite. For investigating the injectivity, we should involve the adjoint operator whose kernel function is defined by
. Then for ,
,
a formula obtained from the property for . Then
.
Because is valued in [0,1), for every :
and,
. Taking
, follows:
With these estimations of the positivity and injectivity parameters, we have the following result applying the Injectivity Criteria.
Theorem 4. (Injectivity Criteria.) The Hilbert-Schmidt operator defined in (1) has its restrictions on the approximation subspaces spanned by indicator open-interval functions with the injectivity parameters sequence inferior bounded. Consequently, is injective and RH holds due to the Alcantara-Bode equivalence.
Proof.
Because is a constant (see (14)) for any , Lemma 2 could be applied in order to have . That means, half from equivalent formulation of the Alcantara-Bode is true so, the other half should be true i.e.: the Riemann Hypothesis holds. □
Appendix A. The Associated Numerical Methods
Resuming, for T linear, bounded operator on the separable Hilbert space H strict positive on the dense set , suppose that is an eligible zero of T with .
Then the relation on involving its not null orthogonal projection , defines the inequalities corresponding to the methods for investigation of the injectivity of T.
- a)
-
Corollary ([8]). If , then the following inequality holds:
.
- b)
-
Injectivity Criteria ([1]). If we evaluate the parameters from:
. Defining the following relation holds: .
When or are bounded inferior by a constant, from results valid for any and so, .
So, given an linear, bounded integral operator on , the computational effort consists in evaluating the diagonal entries (7) in the matrix representations in order to determine the entry with the minimum value . As we observed, given a level the entries in the matrix representations have the same values no matter the open, semi-open or closed subintervals of size h spanning the finite dimension subspaces that, the sets are all dense in H. So, the decision about the method to choose depends on the existence of a bound for the sequence of positivity parameters .
We will reiterate that, if the operator positivity is unknown, then we could replace it with its Hermitian that is non negative definite on H and both have the same null space.
The dense set of the indicator semi-open intervals functions has been used in [5]. In [6] the authors considered the dense set of the indicator closed intervals functions, without the normalisation factor making the method of finite rank discretization coincides with the restriction method. Obviously, a such family of subspaces is dense, proving it like we done before. In both articles, the authors have been dealing with the decay rate of convergence to zero of the Hermitian integral operators eigenvalues having the kernels like the Mercer kernels ([6]).
In computing the values of the diagonal matrix entries, we used the observation: for the fractional part made by Beurling ([4]), whose equivalent formulation has been used in [2].
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