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Research article

Some operator mean inequalities for sector matrices

  • Received: 26 January 2022 Revised: 04 March 2022 Accepted: 16 March 2022 Published: 31 March 2022
  • MSC : 15A45, 47A63

  • In this article, we obtain some operator mean inequalities of sectorial matrices involving operator monotone functions. Among other results, it is shown that if A,BMn(C) are such that W(A),W(B)Sα, f,g,hm are such that g(1)=h(1)=t for some t(0,1) and 0<mInA,BMIn, then

    (Φ(f(A))σhΦ(f(B)))sec4(α)KΦ(f(AσgB)),

    where M,m are scalars and m is the collection of all operator monotone function φ:(0,)(0,) satisfying φ(1)=1. Moreover, we refine a norm inequality of sectorial matrices involving positive linear maps, which is a result of Bedrani, Kittaneh and Sababheh.

    Citation: Chaojun Yang. Some operator mean inequalities for sector matrices[J]. AIMS Mathematics, 2022, 7(6): 10778-10789. doi: 10.3934/math.2022602

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  • In this article, we obtain some operator mean inequalities of sectorial matrices involving operator monotone functions. Among other results, it is shown that if A,BMn(C) are such that W(A),W(B)Sα, f,g,hm are such that g(1)=h(1)=t for some t(0,1) and 0<mInA,BMIn, then

    (Φ(f(A))σhΦ(f(B)))sec4(α)KΦ(f(AσgB)),

    where M,m are scalars and m is the collection of all operator monotone function φ:(0,)(0,) satisfying φ(1)=1. Moreover, we refine a norm inequality of sectorial matrices involving positive linear maps, which is a result of Bedrani, Kittaneh and Sababheh.



    Let B(H) denote the C algebra of all bounded linear operators acting on a Hilbert space H. When the dimension of H is finite, we identify B(H) with Mn(C), denoting the set of n×n complex matrices. I denotes the identity operator in B(H), while In denotes the identity matrix in Mn(C). For AMn(C), the conjugate transpose of A is denoted by A, and the matrices A=12(A+A) and A=12i(AA) are called the real part and imaginary part of A, respectively ([6,p.6] and [12,p.7]). Moreover, A is called accretive if A>0. For two Hermitian matrices A,BMn(C), we write AB (resp. A>B) if AB is positive semidefinite(resp. positive definite). A linear map Φ:Mn(C)Mk(C) is called positive if it maps positive semi-definite matrices in Mn(C) to positive semi-definite matrices in Mk(C) and is said to be unital if it maps the identity matrix in Mn(C) to the identity matrix in Mk(C). We reserve M,m for scalars.

    The operator norm of AMn(C) is defined by

    A=max{|Ax,y|:x,yCn,x=y=1}.

    AMn(C) is contractive if A1. Let ||||u denote any unitarily invariant norm on Mn(C), which satisfies ||UAV||u=||A||u for any unitary matrices U,VMn(C) and all AMn(C).

    For α[0,π2), Sα denotes the sectorial region in the complex plane as follows:

    Sα={zC:z>0,|z|(z)tanα}.

    If W(A)S0, then A is positive definite, and if W(A),W(B)Sα for some α[0,π2), then W(A+B)Sα, A is nonsingular and (A) is positive definite. Moreover, W(A)Sα implies W(XAX)Sα for any nonzero n×m matrix X, thus W(A1)Sα. Recently, Tan and Chen [20] also proved that for any positive linear map Φ, W(A)Sα implies that W(Φ(A))Sα. Recent developments on sectorial matrices can be found in [3,4,9,10,16,18,22,23].

    The numerical range of AMn(C) is defined by

    W(A)={Ax,x:xCn,x=1}.

    The numerical radius of A is defined by ω(A)=sup{|λ|:λW(A)}. We note that if A0, then ω(A)=A. The following inequality holds true

    ω(A)ω(A)A (1.1)

    for AMn(C).

    For two positive definite matrices A,BMn(C) and 0t1, the weighted geometric mean, weighted harmonic mean and weighted arithmetic mean are defined respectively as follows:

    AtB=A12(A12BA12)tA12,
    A!tB=((1t)A1+tB1)1,
    AtB=(1t)A+tB.

    In particular, when t=12, we denote the geometric mean, harmonic mean and arithmetic mean by AB, A!B and AB, respectively. Another interesting operator mean is the Heron mean, which is defined by Ft(A,B)=t(AB)+(1t)(AB) for positive definite matrices A,BMn(C) and 0t1. The weighted arithmetic-geometric-harmonic mean inequalities states that

    A!tBAtBAtB. (1.2)

    For two accretive matrices A,BMn(C), Drury [9] defined the geometric mean of A and B as follows

    AB=(2π0(tA+t1B)1dtt)1. (1.3)

    This new geometric mean defined by (1.3) possesses some similar properties compared to the geometric mean of positive matrices. For instance, AB=BA, (AB)1=A1B1. Moreover, if A,BMn(C) with W(A),W(B)Sα, then W(AB)Sα.

    Later, Raissouli, Moslehian and Furuichi [19] defined the following weighted geometric mean of two accretive matrices A,BMn(C),

    AλB=sinλππ0tλ1(A1+tB1)1dtt, (1.4)

    where λ[0,1]. If λ=12, then the formula (1.4) coincides with the formula (1.3).

    We say a real valued continuous function f:(0,)(0,) operator monotone (increasing) if for any two positive operators A,B, AB implies f(A)f(B). If f(A)f(B) whenever AB>0, we say f is operator monotone decreasing.

    For the sake of convenience, we will need the following notation.

    m={f(x),wheref:(0,)(0,)is an operator monotone function withf(1)=1}.

    Lately, Bedrani, Kittaneh and Sababheh [3] defined a more general operator mean for two accretive matrices A,BMn(C),

    AσgB=10((1s)A1+sB1)1dvg(s), (1.5)

    where g: (0,)(0,) is an operator monotone function with g(1)=1 and vg is the probability measure characterizing σg. We note that !tσgt for positive matrices if gm are such that g(1)=t for some t(0,1).

    In the same paper, they also characterize the operator monotone function for an accretive matrix: let AMn(C) be accretive and fm,

    f(A)=10((1s)I+sA1)1dvf(s), (1.6)

    where vf is the probability measure satisfying f(x)=10((1s)+sx1)1dvf(s). This is because AσgB=A12g(A12BA12)A12 for accretive matrices A,B.

    Ando [1] proved that if A,BMn(C) are positive definite, then for any positive linear map Φ,

    Φ(AσfB)Φ(A)σfΦ(B). (1.7)

    Ando's formula (1.7) is known as a matrix Hölder inequality.

    The famous Choi's inequality [5,p.41] states that if Φ is a positive unital linear map and A>0, then

    Φt(A)Φ(At),t[1,0]. (1.8)
    Φt(A)Φ(At),t[0,1]. (1.9)

    A general situation of inequality (1.9) is the following one[1]:

    Φ(f(A))f(Φ(A)),fis operator monotone. (1.10)

    In a recent paper[13], The authors obtained some inequalities involving operator monotone (increasing) functions and operator monotone decreasing functions for positive operators: Let AB(H) be such that 0<mIA,BMI, !tσh,σht and t[0,1]. Then for every positive unital linear map Φ,

    Φ(f(A))σhΦ(f(B))KΦ(f(AσhB)), (1.11)
    g(Φ(AσhB))K(g(Φ(A))σhg(Φ(B))), (1.12)
    (g(Φ(A))σhg(Φ(B)))Kg(Φ(AσhB)), (1.13)

    here the operator means σh,σh are defined for positive semidefinite matrices, f:(0,)(0,) is operator monotone and g:(0,)(0,) is operator monotone decreasing, K denotes the Kantorovich constant K(Mm)=(M+m)24Mm throughout the paper. Since (1.11)–(1.13) are inequalities for positive operator, whether we can obtain the accretive version of these inequalities partially triggers the motivation of this article.

    From [2] we know that for a continuous nonnegative function f on (0,), f is operator monotone if and only if 1f(or f1) is operator monotone decreasing. Thus we can treat f1 as operator monotone decreasing function when f is an operator monotone function.

    In [3], the authors gave an comparison for sector matrices: Let A,BMn with W(A),W(B)Sα and 0<mIn(A),(B)MIn. If g,hm are such that g(1)=h(1)=t for some t(0,1), then for every positive unital linear map Φ,

    Φ((AσgB))Φ1((AσhB))sec6(α)K. (1.14)

    Very recently, the authors in [11] gave the definition of Heron mean of sector matrices A,BMn(C)(in particular, positive definite matrices): Ft(A,B)=t(AB)+(1t)(AB), t[0,1]. They also gave numerical radius inequalities for Heron mean of two sector matrices: Let A,BMn(C) be such that W(A),W(B)Sα and t(0,1). Then

    cos2t+2(α)ω(AB)ω(Ft(A,B))sec4(α)(1tsin2(α)ω(AB). (1.15)

    In this paper, we intend to give some refinements of inequalities (1.11)–(1.15). Furthermore, we shall present more operator mean inequalities for sector matrices.

    We begin this section with several lemmas which will be necessary for achieving our goals.

    Lemma 2.1. (see [3]) Let AMn(C) with W(A)Sα. If fm, then

    f(A)(f(A))sec2(α)f(A).

    Lemma 2.2. (see [3,14,19,21]) Let A,BMn(C) be such that W(A),W(B)Sα and fm. Then

    AσfB(AσfB)sec2(α)(AσfB).

    Lemma 2.3. (see [4]) Let AMn be such that W(A)Sα. Then

    cos(α)ω(A)ω(A)ω(A).

    The following lemma is a well-known result.

    Lemma 2.4. (see [13], Lemma 2.2) If f:(0,)(0,) is operator monotone, then f(αt)αf(t) for α1. The inequality is reversed when 0α1.

    Lemma 2.5. (see [24]) Let AMn(C) with W(A)Sα and let u be any unitarily invariant norm on Mn(C). Then

    cos(α)AuAuAu.

    Lemma 2.6. (see [10,15]) Let AMn(C) with W(A)Sα. Then

    (A1)1Asec2(α)(A1).

    Lemma 2.7. (see [7]) Let A,BMn(C) be positive semidefinite. Then

    AB14A+B2.

    Theorem 2.1. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If f,g,hm are such that g(1)=h(1)=t for some t(0,1), then for every positive unital linear map Φ,

    (Φ(f(A))σhΦ(f(B)))sec4(α)KΦ(f(AσgB)).

    Proof. We have the following chain of inequalities

    (Φ(f(A))σhΦ(f(B)))sec2(α)Φ(f(A))σhΦ(f(B))(by Lemma 2.2)sec4(α)Φ(f(A))σhΦ(f(B))(by Lemma 2.1)sec4(α)KΦ(f(AσgB))(by inequality (1.11))sec4(α)KΦ(f((AσgB)))(by Lemma 2.2)sec4(α)KΦ(f(AσgB)),(by Lemma 2.1)

    which completes the proof.

    Note that when A,B0 in Theorem 2.1, we get inequality (1.11).

    Theorem 2.2. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If f,gm are such that g(1)=t for some t(0,1), then

    f(A)σgf(B)uAσgBusec5(α)Kf(AσgB)AσgBu.

    Proof. Compute

    f(A)σgf(B)uAσgBusec(α)(f(A)σgf(B))uAσgBu(by Lemma 2.5)sec5(α)K(f(AσgB))uAσgBu(by Theorem 2.1)sec5(α)Kf(AσgB)uAσgBu(by Lemma 2.5)sec5(α)Kf(AσgB)AσgBu,

    which completes the proof.

    Theorem 2.3. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If f,g,hm are such that g(1)=h(1)=t for some t(0,1), then for every positive unital linear map Φ,

    f1(Φ(AσgB))sec4(α)K(f1(Φ(A))σhf1(Φ(B))).

    Proof. We have

    f1(Φ(AσgB))(f(Φ(AτtB)))1(by Lemma 2.6)(f((Φ(AσgB)))1(by Lemma 2.1)(f(Φ(AσgB)))1(by Lemma 2.2)Kf1(Φ(A))σhf1(Φ(B))(by inequality (1.12))sec2(α)K1f(Φ(A))σh1f(Φ(B))(by Lemma 2.1)sec4(α)Kf1(Φ(A))σhf1(Φ(B))(by Lemma 2.6)sec4(α)K(f1(Φ(A))σhf1(Φ(B))),(by Lemma 2.2)

    which completes the proof.

    Note that when A,B0 in Theorem 2.3, we get inequality (1.12).

    Theorem 2.4. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If f,g,hm are such that g(1)=h(1)=t for some t(0,1), then for every positive unital linear map Φ,

    (f1(Φ(A))σhf1(Φ(B)))sec8(α)Kf1(Φ(AσgB)).

    Proof. Compute

    (f1(Φ(A))σhf1(Φ(B)))sec2(α)(f1(Φ(A)))σh(f1(Φ(B)))(by Lemma 2.2)sec2(α)1(f(Φ(A)))σh1(f(Φ(B)))(by Lemma 2.6)sec2(α)f1((Φ(A)))σhf1((Φ(B)))(by Lemma 2.1)sec2(α)Kf1(Φ(AσgB))(by inequality (1.2))sec2(α)Kf1(cos2(α)Φ((AσgB)))(by Lemma 2.2)sec4(α)Kf1(Φ((AσgB)))(by Lemma 2.4)sec6(α)K1(f(Φ(AσgB)))(by Lemma 2.1)sec8(α)Kf1(Φ(AσgB)),(by Lemma 2.6)

    which completes the proof.

    Note that when A,B0 in Theorem 2.4, we get inequality (1.2).

    Theorem 2.5. Let AMn(C) be such that W(A)Sα and fm. Then for any positive unital linear map Φ,

    f(Φ(AA))cos2(α)(Φf(A)).

    Proof. Compute

    f(Φ(AA))=f(Φ((AA)))Φf((AA))(by inequality (1.10))Φf(AA)(by Lemma 2.2)=Φf(A)cos2(α)(Φf(A)),(by Lemma 2.1)

    which completes the proof.

    Corollary 2.1. Let AMn(C) be accretive. Then

    AAA.

    Corollary 2.2. Let AMn(C) be contractive. Then

    InAA(InA)(In+A)(In+A)(InA).

    In particular, if A=U is unitary, then 0(UU)(UU).

    In [17], the authors obtained that (InAB)(InBA)(InAA)(InBB) for contractions A,BMn(C). Imposing Φ on both sides implies Φ((InAB)(InBA))Φ((InAA)(InBB)). We note that a stronger result holds Φ((InAB)(InBA))Φ(InAA)Φ(InBB).

    Theorem 2.6. Let AMn(C) be such that W(A)Sα and fm. Then for any positive unital linear map Φ,

    f1(Φ(AA))sec4(α)(Φf1(A)).

    Proof. We have

    f1(Φ(AA))Φ1(f(AA))(by inequality (1.10))Φ(f1(AA))(by inequality (1.8))Φ(f1(A))(by Corollary 2.1)sec2(α)Φ(1f(A))(by Lemma 2.1)sec4(α)(Φf1(A)),(by Lemma 2.6)

    which completes the proof.

    Theorem 2.7. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If fm and t(0,1), then for every positive unital linear map Φ,

    (Φ(f(A!tB)))sec4(α)(f(Φ(A))!tf(Φ(B))).

    Proof. Compute

    (Φ(f(A!tB)))sec2(α)Φf((A!tB))(by Lemma 2.1)sec2(α)Φf(sec2(α)A!tB)(by Lemma 2.2)sec4(α)Φf(A!tB)(by Lemma 2.4)sec4(α)f(Φ(A!tB))(by inequality (1.10))sec4(α)f(Φ(A)!tΦ(B))(by inequality (1.7))=sec4(α)f((Φ(A))!t(Φ(B)))sec4(α)f((Φ(A)))!tf((Φ(B)))(by Theorem 4 in [8])sec4(α)f(Φ(A))!tf(Φ(B))(by Lemma 2.1)sec4(α)(f(Φ(A))!tf(Φ(B))),(by Lemma 2.2)

    which completes the proof.

    Theorem 2.8. Let A,BMn(C) be such that W(A),W(B)Sα and 0<mInA,BMIn. If fm and t(0,1), then

    f1(AtB)sec4(α)(f1(A)!tf1(B)).

    Proof. Compute

    f1(AtB)(f(AtB))1(by Lemma 2.6)f1(AtB)(by Lemma 2.1)f1(A)!tf1(B)(by Remark 2.6 in [2])sec2(α)1(f(A))!t1(f(B))(by Lemma 2.1)sec4(α)f1(A)!tf1(B)(by Lemma 2.6)sec4(α)(f1(A)!tf1(B)),(by Lemma 2.2)

    which completes the proof.

    Theorem 2.9. Let A,BMn with W(A),W(B)Sα and 0<mIn(A),(B)MIn. If g,hm are such that g(1)=h(1)=t for some t(0,1), then for every positive unital linear map Φ,

    Φ((AσgB))Φ1((AσhB))sec2(α)K. (2.1)

    Proof. From 0<mIn(A),(B)MIn we have

    (1t)(M(A))(mA)A10,

    which is equivalent to

    (1t)(A)+(1t)Mm1(A)(1t)(M+m)In. (2.2)

    Similarly, we have

    t(B)+tMm1(B)t(M+m)In. (2.3)

    Summing up inequalities (2.2) and (2.3), we get

    (AtB)+Mm(1(A)t1(B))(M+m)In. (2.4)

    By computation, we have

    sec2(α)MmΦ((AσgB))Φ1((AσhB))14Φ((AσgB))+sec2(α)MmΦ1((AσhB))2(by Lemma 2.7)14Φ((AσgB))+sec2(α)MmΦ(1(AσhB))2(by inequality (1.8))14Φ((AσgB))+sec2(α)MmΦ((AσhB)1)2(by Lemma 2.2)14Φ((AσgB))+sec2(α)MmΦ((A!tB)1)2=14Φ((AσgB))+sec2(α)MmΦ(1At1B)214sec2(α)Φ((AtB))+sec2(α)MmΦ(1At1B)2(by Theorem 5.2 in [3])=14sec2(α)Φ((AtB)+Mm(1At1B))214sec4(α)(M+m)2.(by inequality (2.4))

    That is,

    Φ((AσgB))Φ1((AσhB))sec2(α)K.

    This completes the proof.

    We remark that Theorem 2.9 is an improvement of inequality (1.14).

    Theorem 2.10. Let A,BMn(C) be such that W(A),W(B)Sα and t(0,1). Then for every positive unital linear map Φ,

    F1t(Φ(A),Φ(B))sec2(α)Ft(Φ(A1),Φ(B1)).

    Proof. We have the following chain of inequalities

    F1t(Φ(A),Φ(B))=(tΦ(A)Φ(B)+(1t)Φ(A)Φ(B))11(tΦ(A)Φ(B)+(1t)Φ(A)Φ(B))(by Lemma 2.6)=(tΦ(A)Φ(B)+(1t)(Φ(A)Φ(B)))1t(Φ(A)Φ(B))1+(1t)1(Φ(A)Φ(B))tΦ((AB)1)+(1t)(Φ(A)Φ(B))1(by Lemma 2.2 and (1.8))=tΦ((AB)1)+(1t)Φ1(A)Φ1(B)tΦ((AB)1)+(1t)Φ(1A)Φ(1B)(by (1.8))tΦ((AB)1)+(1t)sec2(α)Φ(A1)Φ(B1)(by Lemma 2.6)tΦ(1A1B)+(1t)sec2(α)(Φ(A1)Φ(B1))(by Lemma 2.2)tsec2(α)Φ((A1)(B1))+(1t)sec2(α)(Φ(A1)Φ(B1))(by Lemma 2.6)=tsec2(α)(Φ(A1)Φ(B1))+(1t)sec2(α)(Φ(A1)Φ(B1))=sec2(α)Ft(Φ(A1),Φ(B1)),

    which completes the proof.

    We note that by letting Φ(X)=X for every XMn(C) in Theorem 2.10, we get the right hand side of inequalities in Theorem 3 in [11].

    Theorem 2.11. Let A,BMn(C) be such that W(A),W(B)Sα and t(0,1). Then

    cos2t+1(α)ω(AB)ω(Ft(A,B))sec3(α)(1tsin2(α)ω(AB).

    Proof. Compute

    ω(AB)AB(by inequality (1.1))sec(α)(AB)(by Lemma 2.5)sec2t+1(α)Ft(A,B)(by Theorem 1 in [11])=sec2t+1(α)ω(Ft(A,B))sec2t+1(α)ω(Ft(A,B))(by inequality (1.1))

    and

    ω(Ft(A,B))Ft(A,B)(by inequality (1.1))sec(α)(Ft(A,B))(by Lemma 2.5)sec3(α)(1tsin2(α))(AB)(by Theorem 1 in [11]) =sec3(α)(1tsin2(α))ω((AB))sec3(α)(1tsin2(α))ω(AB),(by inequality (1.1))

    which completes the proof.

    We remark that Theorem 2.11 is an improvement of inequality (1.15) when taking the bound on both sides into consideration.

    The author is grateful to the referees and editor for their helpful comments and suggestions. This project was funded by China Postdoctoral Science Foundation(No.2020M681575).

    The author declares no conflict of interest in this paper.



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