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Open Mathematics

formerly Central European Journal of Mathematics

Editor-in-Chief: Gianazza, Ugo / Vespri, Vincenzo

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Volume 16, Issue 1


Volume 13 (2015)

On further refinements for Young inequalities

Shigeru Furuichi
  • Corresponding author
  • Department of Information Science, College of Humanities and Sciences, Nihon University, 3-25-40, Sakurajyousui, Setagaya-ku, Tokyo, 156-8550, Japan
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/ Hamid Reza Moradi
Published Online: 2018-12-27 | DOI: https://doi.org/10.1515/math-2018-0115


In this paper sharp results on operator Young’s inequality are obtained. We first obtain sharp multiplicative refinements and reverses for the operator Young’s inequality. Secondly, we give an additive result, which improves a well-known inequality due to Tominaga. We also provide some estimates for the difference A1/2(A−1/2BA−1/2)vA1/2-{(1-v)A + vB} for v∉[ 0,1].

Keywords: Operator inequality; Young inequality; Weighted arithmetic and geometric mean; Positive operator

MSC 2010: 47A63; 26D07; 47A60

1 Introduction

This note lies in the scope of operator inequalities. We assume that the reader is familiar with the continuous functional calculus and the Kubo-Ando theory [1].

It is to be understood throughout the paper that the capital letters present bounded linear operators acting on a Hilbert space 𝓗. A is positive (written A ≥ 0) in case 〈Ax,x〉 ≥ 0 for all x ∈ 𝓗 also an operator A is said to be strictly positive (denoted by A > 0) if A is positive and invertible. If A and B are self-adjoint, we write BA in case BA ≥ 0. As usual, by I we denote the identity operator.

The weighted arithmetic mean ∇v, geometric mean ♯v, and harmonic mean !v, for v ∈ [0, 1] and a,b > 0, are defined as follows:


If v = 12, we denote the arithmetic, geometric, and harmonic means, respectively, by ∇, ♯ and !, for the simplicity. Like the scalar cases, the operator arithmetic mean, the operator geometric mean, and the operator harmonic mean for A,B > 0 can be stated in the following form:


The celebrated arithmetic-geometric-harmonic-mean inequalities for scalars assert that if a,b > 0, then


Generalization of the inequalities (1) to operators can be seen as follows: If A,B > 0, then


The last inequality above is called the operator Young inequality. During the past years, several refinements and reverses were given for Young’s inequality, see for example [2,3,4].

Zuo et al. showed in [5, Theorem 7] that the following inequality holds:


whenever 0 < mIBmI < MIAMI or 0 < mIAmI < MIBMI. As the authors mentioned in [5], the inequality (2) improves the following refinement of Young’s inequality involving Specht St=t1t1elogt1t1t>0,t1 (see [6, Theorem 2]),


Under the above assumptions, Dragomir proved in [7, Corollary 1] that


We remark that there is no relationship between two constants K(h,2)r and expv1v2h12 in general.

In [3, 8] we proved some sharp multiplicative reverses of Young’s inequality. In this brief note, as the continuation of our previous works, we establish sharp bounds for the arithmetic, geometric and harmonic mean inequalities. Moreover, we shall show some additive-type refinements and reverses of Young’s inequality. We will formulate our new results in a more general setting, namely the sandwich assumption sABtA (0 < st). Additionally, we present some Young type inequalities for the wider range of v; i.e., v ∉ [0, 1].

2 Main results

In our previous work [8], we gave new sharp inequalities for reverse Young inequalities. In this section we firstly give new sharp inequalities for Young inequalities, as limited cases in the first inequalities both (i) and (ii) of the following theorem.

Theorem 2.1

Let A,B > 0 such that sABtA for some scalars 0 < st and let fv(x) (1v)+vxxvforx>0, and v ∈ [0, 1].

  1. If t ≤ 1, then fv(t) Av BAvBfv(s) AvB.

  2. If s ≥ 1, then fv(s) AvBAvBfv(t)AvB.


Since fv(x) = v(1–v)(x–1)xv-1, fv(x) is monotone decreasing for 0 < x ≤ 1 and monotone increasing for x ≥ 1.

  1. For the case 0 < sxt ≤ 1, we have fv(t) ≤ fv(x) ≤ fv(s), which implies fv(t) AvBAv Bfv(s) Av B by the standard functional calculus.□

  2. For the case 1 ≤ sxt, we have fv(s) ≤ fv(x) ≤ fv(t) which implies fv(s) Av BAv Bfv(t)Av B by the standard functional calculus.

Remark 2.2

It is worth emphasizing that each assertion in Theorem 2.1 implies the other one. For instance, assume that the assertion (ii) holds, i.e.,


Let t ≤ 1, then 11t1x1s. Hence (3) ensures that




Now, by replacing v by 1–v we get


which means


In the same spirit, we can derive (ii) from (i).

Corollary 2.3

Let A, B > 0, m, m′, M, M′ > 0, and v ∈ [0, 1].

  1. If 0 < mIAmI < MI ≤ B ≤ MI, then


  2. If 0 < mIBmI < MIAMI, then



We use again the function fv(x)=(1v)+vxxvin this proof.

The condition (i) is equivalent to IMmIA12BA12MmI, so that we get fv(Mm)AvBAvBfv(Mm)Av B by putting s=Mmandt=Mm in (ii) of Theorem 2.1.

Similarly, the condition (ii) is equivalent to mMIA12BA12mMII, so that we get fv(mM)AvBAvBfv(mM)Av B by putting s=mMandt=mM of Theorem 2.1.□

Note that the second inequalities in both (i) and (ii) of Theorem 2.1 and Corollary 2.3 are special cases of [8, Theorem A].

Remark 2.4

It is remarkable that the inequalities fv(t) ≤ fv(x) ≤ fv(s) (0 < sxt ≤ 1) given in the proof of Theorem 2.1 are sharp, since the function fv(x) for sxt is continuous. So, all results given from Theorem 2.1 are similarly sharp. As a matter of fact, let A = MI and B = mI, then from LHS of (5), we infer

AvB=(Mvm)I and AvB=(Mvm)I.



To see that the constant mvMmvM in the LHS of (4) can not be improved, we consider A = mI and B = MI, then


By replacing A, B by A–1, B–1, respectively, the refinement and reverse of non-commutative geometric-harmonic mean inequality can be obtained as follows:

Corollary 2.5

Let A, B > 0, m, m′, M, M′ > 0, and v ∈ [0, 1].

  1. If 0 < mIAmI < MIBMI, then


  2. If 0 < mIBmI < MIAMI, then


Now, we give a new sharp reverse inequality for Young’s inequality as an additive-type in the following.

Theorem 2.6

Let A,B > 0 such that sABtA for some scalars 0 < st, and v ∈ [0, 1]. Then


where gv(x )≡ (1–v) + vxxv for sxt.


Straightforward differentiation shows that gv (x) = v(1–v)xv–2 ≥ 0 and gv(x) is continuous on the interval [s,t], so


Therefore, by applying similar arguments as in the proof of Theorem 2.1, we reach the desired inequality (6). This completes the proof of theorem.□

Corollary 2.7

Let A,B > 0 such that mIA,BMI for some scalars 0 < m < M. Then for v ∈ [0, 1],


where ξ=max1MMvmMvm,1mmvMmvM.

Remark 2.8

We claim that if A,B > 0 such that mIA,BMI for some scalars 0 < m < M with h = Mm and v ∈ [0, 1], then


holds, where Lx,y=yxlogylogxxy is the logarithmic mean and the term S(h) refers to the Specht’s ratio. Indeed, we have the inequalities


which were originally proved in [9, Lemma 3.2], thanks to Sh=S1handL1,h=L1,1h. Therefore, our result, Theorem 2.6, improves the well-known result by Tominaga [9, Theorem 3.1],


Since gv(x) is convex, we can not obtain a general result on the lower bound for AvBAvB. However, if we impose the conditions, we can obtain new sharp inequalities for Young inequalities as an additive-type in the first inequalities both (i) and (ii) in the following proposition. (At the same time, of course, we also obtain the upper bounds straightforwardly.)

Proposition 2.9

Let A,B > 0 such that sABtA for some scalars 0 < st, v ∈ [0, 1], and gv is defined as in Theorem 2.6.

  1. If t ≤ 1, then gv(t)AAv BAvBgv(s)A.

  2. If s ≥ 1, then gv(s)AAvBAvBgv(t)A.


It follows from the fact that gv(x) is monotone decreasing for 0 < x ≤ 1 and monotone increasing for x ≥ 1.□

Corollary 2.10

Let A, B > 0, m, m′, M, M′ > 0, and v ∈ [0, 1].

  1. If 0 < mIAmI < MIBMI, then


  2. If 0 < mIBmI < MIAMI, then


In the following we use the notations ▽v and ♮v to distinguish from the operator means ∇v and ♯v:


for v ∉ [0, 1]. Notice that, since A,B > 0, the expressions AvB and AvB are also well-defined.

Remark 2.11

It is known (and easy to show) that for any A,B > 0,


Assume gv(x) is defined as in Theorem 2.6. By an elementary computation we have


Now, in the same way as above we have also for any v ∉ [0, 1]:

  1. If 0 < mIAmIMIBMI, then


    On account of assumptions, we also infer


  2. If 0 < mIBmIMIAMI, then


    On account of assumptions, we also infer


In addition, with the same assumption to Theorem 2.6 except for v ∉ [0, 1], we have


since we have min{gv(s),gv(t)} ≤ gv(x) by gv (x) ≤ 0, for v ∉[0, 1].


The authors thank anonymous referees for giving valuable comments and suggestions to improve our manuscript. The author (S.F.) was partially supported by JSPS KAKENHI Grant Number 16K05257.


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About the article

Received: 2018-07-21

Accepted: 2018-10-18

Published Online: 2018-12-27

Citation Information: Open Mathematics, Volume 16, Issue 1, Pages 1478–1482, ISSN (Online) 2391-5455, DOI: https://doi.org/10.1515/math-2018-0115.

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© 2018 Furuichi and Moradi, published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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