1. Introduction
The self-adjoint operators on Hilbert spaces with their numerous applications play an important part in the operator theory. The bounds research for self-adjoint operators is a very useful area of this theory. There is no better inequality in bounds examination than Jensen's inequality. It is an extensively used inequality in various fields of mathematics.
Let be a real interval of any type. A continuous function is said to be operator convex if
holds for each and every pair of self-adjoint operators and (acting) on an infinite dimensional Hilbert space with spectra in (the ordering is defined by setting if is positive semi-definite).
Let be an operator convex function defined on an interval
Ch. Davis [1] proved
where is a unital completely positive linear mapping from a -algebra to linear operators on a Hilbert space and is a self-adjoint element in with spectrum in Subsequently M. D. Choi [2] noted that it is enough to assume that is unital and positive. In fact, the restriction of to the commutative -algebra generated by is automatically completely positive by a theorem of Stinespring.
F. Hansen and G. K. Pedersen [3] proved a Jensen type inequality
for operator convex functions defined on an interval (with and and self-adjoint operators with spectra in assuming that The restriction on the interval and the requirement was subsequently removed by B. Mond and J. Pečarić in [4], cf. also [5].
The inequality (▭) is in fact just a reformulation of (▭) although this was not noticed at the time. It is nevertheless important to note that the proof given in [3] and thus the statement of the theorem, when restricted to matrices, holds for the much richer class of matrix convex functions. Hansen and Pedersen used (▭) to obtain elementary operations on functions, which leave invariant the class of operator monotone functions. These results then served as the basis for a new proof of Löwner's theorem applying convexity theory and Krein-Milman's theorem.
B. Mond and J. Pečarić [6] proved the inequality
for operator convex functions defined on an interval where are unital positive linear mappings, are self-adjoint operators with spectra in and are are non-negative real numbers with sum one.
Also, B. Mond, J. Pečarić, T. Furuta et al. [6], [7], [8], [9], [10], [11] observed conversed of some special case of Jensen's inequality. So in [10] presented the following generalized converse of a Schwarz inequality (▭)
for convex functions defined on an interval , , where is a real valued continuous function on , is a real valued function defined on , matrix non-decreasing in , , , is a unital positive linear mapping and is a Hermitian matrix with spectrum contained in .
There are a lot of new research on the classical Jensen inequality (▭) and its reverse inequalities. For example, J.I. Fujii et all. in [12], [13] expressed these inequalities by externally dividing points.
2. Classic results
In this section we present a form of Jensen's inequality which contains (▭), (▭) and (▭) as special cases. Since the inequality in (▭) was the motivating step for obtaining converses of Jensen's inequality using the so-called Mond-Pečarić method, we also give some results pertaining to converse inequalities in the new formulation.
We recall some definitions. Let be a locally compact Hausdorff space
and let be a -algebra of operators on some
Hilbert space We say that a field of
operators in is continuous if the function is norm continuous on If in addition is a Radon
measure on and the function is integrable,
then we can form
for every linear functional in the norm dual .
Assume furthermore that there is a field
of positive linear mappings from to another -algebra of operators on a Hilbert space . We recall that a linear mapping is said to be a positive mapping if for all . We say that such
a field is continuous if the function is
continuous for every Let the -algebras
include the identity operators and the function
be integrable with for some positive
scalar . Specially, if
we say that a
Let be the -algebra of all bounded linear operators on a Hilbert space . We define bounds of an operator by
for . If denotes the spectrum of , then .
For an operator we define operators , , by
Obviously, if is self-adjoint, then and (called positive and negative parts of ).
2.1. Jensen's inequality with operator convexity
Firstly, we give a general formulation of Jensen's operator inequality for a unital field of positive linear mappings (see [14]).
holds for every bounded continuous field of self-adjoint elements in with spectra contained in
We first note that the function is continuous and bounded, hence integrable with respect to the bounded Radon measure Furthermore, the integral is an element in the multiplier algebra acting on We may organize the set of bounded continuous functions on with values in as a normed involutive algebra by applying the point-wise operations and setting
and it is not difficult to verify that the norm is already complete and satisfy the -identity. In fact, this is a standard construction in -algebra theory. It follows that . We then consider the mapping
defined by setting
and note that it is a unital positive linear map. Setting we use inequality (▭) to obtain
but this is just the statement of the theorem.
2.2. Converses of Jensen's inequality
In the present context we may obtain results of the Li-Mathias type cf. Chapter 3[15] and [16], [17].
holds for every operator convex function on such that and for every operator concave function on such that .
We prove only RHS of (▭). Let be operator concave function on such that for every . By using the functional calculus, it follows that for every . Applying the positive linear mappings and integrating, we obtain
Furthermore, replacing by in Theorem ▭, we obtain , which gives . Since , then using operator monotonicity of we obtain
Applying RHS of (▭) for a convex function (or LHS of (▭) for a concave function ) we obtain the following generalization of (▭).
In the dual case (when is concave) the opposite inequalities hold in (▭) with instead of .
We prove only the convex case. For convex the inequality holds for every . Thus, by putting in (▭) we obtain (▭). Numerous applications of the previous theorem can be given (see [15]). Applying Theorem ▭ for the function and , we obtain the following generalization of Theorem 2.4[15].
where
If furthermore is strictly convex differentiable, then the constant can be written more precisely as
where
In the dual case (when is concave and is strictly concave differentiable) the opposite inequalities hold in (▭) with instead of with the opposite condition while determining .
3. Inequalities with conditions on spectra
In this section we present Jensens's operator inequality for real valued continuous convex functions with conditions on the spectra of the operators. A discrete version of this result is given in [18]. Also, we obtain generalized converses of Jensen's inequality under the same conditions.
Operator convexity plays an essential role in (▭). In fact, the inequality (▭) will be false if we replace an operator convex function by a general convex function. For example, M.D. Choi in Remark 2.6[2] considered the function which is convex but not operator convex. He demonstrated that it is sufficient to put , so we have the matrix case as follows. Let be the contraction mapping . If then and no relation between and under the operator order.
If
then
Given the above, there is no relation between and under the operator order. We observe that in the above case the following stands and , , , i.e.
(see Fig. 1.a).

Figure 1.
Spectral conditions for a convex function f
If
then
So we have that an inequality of type (▭) now is valid. In the above case the following stands and , , , i.e.
(see Fig. 1.b).
3.1. Jensen's inequality without operator convexity
It is no coincidence that the inequality (▭) is valid in Example ▭-II). In the following theorem we prove a general result when Jensen's operator inequality (▭) holds for convex functions.
where and , , are the bounds of the self-adjoint operator , then
holds for every continuous convex function provided that the interval contains all .
If is concave, then the reverse inequality is valid in (▭).
We prove only the case when is a convex function. If we denote and , then and , . It follows . Therefore .
but since is convex on and since , then
Since then by using functional calculus, it follows from (▭)
On the other hand, since , , then by using functional calculus, it follows from (▭)
Applying a positive linear mapping and summing, we obtain
since . Combining the two inequalities (▭) and (▭), we have the desired inequality (▭).
where is the subdifferential of . Since , , then by using functional calculus, applying a positive linear mapping and summing, we obtain from (▭)
Since it follows
which is the desired inequality (▭). Putting for every , where is a real number, we obtain the following obvious corollary of Theorem ▭.
where and , , are the bounds of the self-adjoint operator , then
holds for every continuous convex function provided that the interval contains all .
3.2. Converses of Jensen's inequality with conditions on spectra
Using the condition on spectra we obtain the following extension of Theorem ▭.
and , , are functions such that , is convex, is bounded and operator monotone in the first variable, then
In the dual case (when is concave) the opposite inequalities hold in (▭) by replacing and with and , respectively.
We prove only LHS of (▭). It follows from (▭) (compare it to (▭))
since .
By using operator monotonicity of
we obtain
Putting or in Theorem ▭, we obtain the next corollary.
and is convex, then for any
If additionally on , then
In the dual case (when is concave) the opposite inequalities hold in (▭) by replacing and with and , respectively. If additionally on , then the opposite inequalities also hold in (▭) by replacing and with and , respectively.
4. Refined Jensen's inequality
In this section we present a refinement of Jensen's inequality for real valued continuous convex functions given in Theorem ▭. A discrete version of this result is given in [19].
To obtain our result we need the following two lemmas.
These results follows from Theorem 1, p. 717[20].
holds for every continuous convex resp. concave function , where
We prove only the convex case. It follows from (▭) that
for every such that . For any we can write
Then by using (▭) for and we obtain
since
Finally we use the continuous functional calculus for a self-adjoint operator : and on implies ; and implies . Then by using (▭) we obtain the desired inequality (▭).
where and , , be the bounds of the operator and
If is a continuous convex resp. concave function provided that the interval contains all , then
resp.
holds, where
and , , , are arbitrary numbers.
We prove only the convex case. Since is the self-adjoint elements such that and is convex on , then by Lemma ▭ we obtain
where and are defined by (▭).
But since is convex on and implies , then
Applying a positive linear mapping , integrating and adding , we obtain
since . Combining the two inequalities (▭) and (▭), we have LHS of (▭). Since and , then we have RHS of (▭).
If and , then the inequality (▭) holds, but is not defined (see Example ▭ I) and II)).

Figure 2.
Refinement for two operators and a convex function f
We put which is convex but not operator convex in (▭). Also, we define mappings as follows: , (then ).
and its improvement
since , We remark that in this case and is not defined.
In this case is not defined, since . We have
and putting , we obtain , which give the following improvement
so , , , , , and we put , (rounded to four decimal places). We have
and its improvement
(rounded to four decimal places), since , . But, if we put , , then , so we do not have an improvement of Jensen's inequality. Also, if we put , , then , and , which is worse than the above improvement.
Putting for every , where is a real number, we obtain the following obvious corollary of Theorem ▭.
where and , , are the bounds of the operator and
If is a continuous convex resp. concave function provided that the interval contains all , then
holds, where is defined by (▭), and , , , are arbitrary numbers.
5. Extension Jensen's inequality
In this section we present an extension of Jensen's operator inequality for tuples of self-adjoint operators, unital tuples of positive linear mappings and real valued continuous convex functions with conditions on the spectra of the operators.
In a discrete version of Theorem ▭ we prove that Jensen's operator inequality holds for every continuous convex function and for every tuple of self-adjoint operators , for every tuple of positive linear mappings in the case when the interval with bounds of the operator has no intersection points with the interval with bounds of the operator for each , i.e. when for where and , , are the bounds of , and and , , are the bounds of , . It is interesting to consider the case when is valid for several , but not for all . We study it in the following theorem (see [21]).
and one of two equalities
is valid, then
holds for every continuous convex function provided that the interval contains all , . If is concave, then the reverse inequality is valid in (▭).
We prove only the case when is a convex function. Let us denote
It is easy to verify that or or implies .
but since is convex on all and for , then
Since , , it follows from (▭)
Applying a positive linear mapping and summing, we obtain
since . It follows
Similarly to (▭) in the case , , it follows from (▭)
Combining (▭) and (▭) and taking into account that , we obtain
It follows
which gives the desired double inequality (▭).
On the other hand, since is convex on , we have
where is the subdifferential of . Replacing by for , applying and summing, we obtain from (▭) and (▭)
So (▭) holds again. The remaining part of the proof is the same as in the case a).
is valid, then
holds for every continuous convex function .
holds for every continuous convex function .
Indeed, by the assumptions of Theorem ▭ we have
which implies
Also for and hold. So we can apply Theorem ▭ on operators and mappings and obtain the desired inequality.
then
for every . We observe that is not operator convex and since , and .
With respect to Remark ▭, we obtain the following obvious corollary of Theorem ▭.
and one of two equalities
is valid, then
holds for every continuous convex function provided that the interval contains all , .
If is concave, then the reverse inequality is valid in (▭).
As a special case of Corollary ▭ we can obtain a discrete version of Corollary ▭ as follows.
where and , , are the bounds of , then
holds for every continuous convex function provided that the interval contains all .
We prove only the convex case. We define tuple of operators , , by and , . Then , are the bounds of and , are the ones of , . Also, we define tuple of non-negative numbers by and , . Then and by using (▭) we have
Since
then
Taking into account (▭) and (▭), we can apply Corollary ▭ for and , as above, and we get
which gives the desired inequality (▭).
6. Extension of the refined Jensen's inequality
There is an extensive literature devoted to Jensen's inequality concerning different refinements and extensive results, see, for example [22], [23], [24], [25], [26], [27], [28], [29].
In this section we present an extension of the refined Jensen's inequality obtained in Section ▭ and a refinement of the same inequality obtained in Section ▭.
If
and one of two equalities
is valid, then
holds for every continuous convex function provided that the interval contains all , , where
and , , , are arbitrary numbers. If is concave, then the reverse inequality is valid in (▭).
We prove only the convex case. Let us denote
It is easy to verify that or or implies .
Since is convex on and for , it follows from Lemma ▭ that
holds, where and . Applying a positive linear mapping and summing, we obtain
since . It follows that
where .
Additionally, since is convex on all and , , then
It follows
Combining (▭) and (▭) and taking into account that , we obtain
Next, we obtain
which gives the following double inequality
Adding in the above inequalities, we get
Now, we remark that and . (Indeed, since is convex, then , which implies that . Also, since
then
which gives
Consequently, the following inequalities
hold, which with (▭) proves the desired series inequalities (▭).

Figure 3.
An example a convex function and the bounds of four operators
We show an example such that
holds, where and
We define mappings as follows: , . Then and .
Let
Then , , , , , , , , so , , and (rounded to five decimal places). Also,
and
Then
holds (which is consistent with (▭)).
We will choose three pairs of numbers , , as follows
New, we obtain the following improvement of (▭) (see (▭))
Table 1.
Using Theorem ▭ we get the following result.
and
holds for every in the close interval joining and , where and are defined by (▭).
Adding in (▭) and noticing , we obtain
Taking into account the above inequality and the left hand side of (▭) we obtain (▭).
Similarly, subtracting in (▭) we obtain (▭).
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