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,B∈Mn(C) are such that W(A),W(B)⊆Sα, f,g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1) and 0<mIn≤ℜA,ℜB≤MIn, then
ℜ(Φ(f(A))σhΦ(f(B)))≤sec4(α)KℜΦ(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,B∈Mn(C) are such that W(A),W(B)⊆Sα, f,g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1) and 0<mIn≤ℜA,ℜB≤MIn, then
ℜ(Φ(f(A))σhΦ(f(B)))≤sec4(α)KℜΦ(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 A∈Mn(C), the conjugate transpose of A is denoted by A∗, and the matrices ℜA=12(A+A∗) and ℑA=12i(A−A∗) are called the real part and imaginary part of A, respectively ([6,p.6] and [12,p.7]). Moreover, A is called accretive if ℜA>0. For two Hermitian matrices A,B∈Mn(C), we write A≥B (resp. A>B) if A−B 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 A∈Mn(C) is defined by
‖A‖=max{|⟨Ax,y⟩|:x,y∈Cn,‖x‖=‖y‖=1}. |
A∈Mn(C) is contractive if ‖A‖≤1. Let ||⋅||u denote any unitarily invariant norm on Mn(C), which satisfies ||UAV||u=||A||u for any unitary matrices U,V∈Mn(C) and all A∈Mn(C).
For α∈[0,π2), Sα denotes the sectorial region in the complex plane as follows:
Sα={z∈C:ℜz>0,|ℑz|≤(ℜz)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 ℜ(A) is positive definite. Moreover, W(A)⊆Sα implies W(X∗AX)⊆Sα for any nonzero n×m matrix X, thus W(A−1)⊆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 A∈Mn(C) is defined by
W(A)={⟨Ax,x⟩:x∈Cn,‖x‖=1}. |
The numerical radius of A is defined by ω(A)=sup{|λ|:λ∈W(A)}. We note that if A≥0, then ω(A)=‖A‖. The following inequality holds true
ω(ℜA)≤ω(A)≤‖A‖ | (1.1) |
for A∈Mn(C).
For two positive definite matrices A,B∈Mn(C) and 0≤t≤1, the weighted geometric mean, weighted harmonic mean and weighted arithmetic mean are defined respectively as follows:
A♯tB=A12(A−12BA−12)tA12, |
A!tB=((1−t)A−1+tB−1)−1, |
A∇tB=(1−t)A+tB. |
In particular, when t=12, we denote the geometric mean, harmonic mean and arithmetic mean by A♯B, A!B and A∇B, respectively. Another interesting operator mean is the Heron mean, which is defined by Ft(A,B)=t(A∇B)+(1−t)(A♯B) for positive definite matrices A,B∈Mn(C) and 0≤t≤1. The weighted arithmetic-geometric-harmonic mean inequalities states that
A!tB≤A♯tB≤A∇tB. | (1.2) |
For two accretive matrices A,B∈Mn(C), Drury [9] defined the geometric mean of A and B as follows
A♯B=(2π∫∞0(tA+t−1B)−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, A♯B=B♯A, (A♯B)−1=A−1♯B−1. Moreover, if A,B∈Mn(C) with W(A),W(B)⊂Sα, then W(A♯B)⊂Sα.
Later, Raissouli, Moslehian and Furuichi [19] defined the following weighted geometric mean of two accretive matrices A,B∈Mn(C),
A♯λB=sinλππ∫∞0tλ−1(A−1+tB−1)−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, A≥B implies f(A)≥f(B). If f(A)≤f(B) whenever A≥B>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,B∈Mn(C),
AσgB=∫10((1−s)A−1+sB−1)−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 !t≤σg≤∇t for positive matrices if g∈m 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 A∈Mn(C) be accretive and f∈m,
f(A)=∫10((1−s)I+sA−1)−1dvf(s), | (1.6) |
where vf is the probability measure satisfying f(x)=∫10((1−s)+sx−1)−1dvf(s). This is because AσgB=A12g(A−12BA−12)A12 for accretive matrices A,B.
Ando [1] proved that if A,B∈Mn(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 A∈B(H) be such that 0<mI≤A,B≤MI, !t≤σh,σh′≤∇t and t∈[0,1]. Then for every positive unital linear map Φ,
Φ(f(A))σhΦ(f(B))≤KΦ(f(Aσh′B)), | (1.11) |
g(Φ(AσhB))≤K(g(Φ(A))σh′g(Φ(B))), | (1.12) |
(g(Φ(A))σh′g(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 f−1) is operator monotone decreasing. Thus we can treat f−1 as operator monotone decreasing function when f is an operator monotone function.
In [3], the authors gave an comparison for sector matrices: Let A,B∈Mn with W(A),W(B)⊂Sα and 0<mIn≤ℜ(A),ℜ(B)≤MIn. If g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1), then for every positive unital linear map Φ,
‖Φ(ℜ(AσgB))Φ−1(ℜ(AσhB))‖≤sec6(α)K. | (1.14) |
Very recently, the authors in [11] gave the definition of Heron mean of sector matrices A,B∈Mn(C)(in particular, positive definite matrices): Ft(A,B)=t(A∇B)+(1−t)(A♯B), t∈[0,1]. They also gave numerical radius inequalities for Heron mean of two sector matrices: Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and t∈(0,1). Then
cos2t+2(α)ω(A♯B)≤ω(Ft(A,B))≤sec4(α)(1−tsin2(α)ω(A∇B). | (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 A∈Mn(C) with W(A)⊆Sα. If f∈m, then
f(ℜA)≤ℜ(f(A))≤sec2(α)f(ℜA). |
Lemma 2.2. (see [3,14,19,21]) Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and f∈m. Then
ℜAσfℜB≤ℜ(AσfB)≤sec2(α)(ℜAσfℜB). |
Lemma 2.3. (see [4]) Let A∈Mn be such that W(A)⊂Sα. Then
cos(α)ω(A)≤ω(ℜA)≤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 α≥1. The inequality is reversed when 0≤α≤1.
Lemma 2.5. (see [24]) Let A∈Mn(C) with W(A)⊆Sα and let ‖⋅‖u be any unitarily invariant norm on Mn(C). Then
cos(α)‖A‖u≤‖ℜA‖u≤‖A‖u. |
Lemma 2.6. (see [10,15]) Let A∈Mn(C) with W(A)⊆Sα. Then
ℜ(A−1)≤ℜ−1A≤sec2(α)ℜ(A−1). |
Lemma 2.7. (see [7]) Let A,B∈Mn(C) be positive semidefinite. Then
‖AB‖≤14‖A+B‖2. |
Theorem 2.1. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f,g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1), then for every positive unital linear map Φ,
ℜ(Φ(f(A))σhΦ(f(B)))≤sec4(α)KℜΦ(f(AσgB)). |
Proof. We have the following chain of inequalities
ℜ(Φ(f(A))σhΦ(f(B)))≤sec2(α)ℜΦ(f(A))σhℜΦ(f(B))(by Lemma 2.2)≤sec4(α)Φ(f(ℜA))σhΦ(f(ℜB))(by Lemma 2.1)≤sec4(α)KΦ(f(ℜAσgℜB))(by inequality (1.11))≤sec4(α)KΦ(f(ℜ(AσgB)))(by Lemma 2.2)≤sec4(α)KℜΦ(f(AσgB)),(by Lemma 2.1) |
which completes the proof.
Note that when A,B≥0 in Theorem 2.1, we get inequality (1.11).
Theorem 2.2. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f,g∈m are such that g′(1)=t for some t∈(0,1), then
‖f(A)σgf(B)‖u‖AσgB‖u≤sec5(α)K‖f(AσgB)AσgB‖u. |
Proof. Compute
‖f(A)σgf(B)‖u‖AσgB‖u≤sec(α)‖ℜ(f(A)σgf(B))‖u‖AσgB‖u(by Lemma 2.5)≤sec5(α)K‖ℜ(f(AσgB))‖u‖AσgB‖u(by Theorem 2.1)≤sec5(α)K‖f(AσgB)‖u‖AσgB‖u(by Lemma 2.5)≤sec5(α)K‖f(AσgB)AσgB‖u, |
which completes the proof.
Theorem 2.3. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f,g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1), then for every positive unital linear map Φ,
ℜf−1(Φ(AσgB))≤sec4(α)Kℜ(f−1(Φ(A))σhf−1(Φ(B))). |
Proof. We have
ℜf−1(Φ(AσgB))≤(ℜf(Φ(AτtB)))−1(by Lemma 2.6)≤(f(ℜ(Φ(AσgB)))−1(by Lemma 2.1)≤(f(Φ(ℜAσgℜB)))−1(by Lemma 2.2)≤Kf−1(Φ(ℜA))σhf−1(Φ(ℜB))(by inequality (1.12))≤sec2(α)Kℜ−1f(Φ(A))σhℜ−1f(Φ(B))(by Lemma 2.1)≤sec4(α)Kℜf−1(Φ(A))σhℜf−1(Φ(B))(by Lemma 2.6)≤sec4(α)Kℜ(f−1(Φ(A))σhf−1(Φ(B))),(by Lemma 2.2) |
which completes the proof.
Note that when A,B≥0 in Theorem 2.3, we get inequality (1.12).
Theorem 2.4. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f,g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1), then for every positive unital linear map Φ,
ℜ(f−1(Φ(A))σhf−1(Φ(B)))≤sec8(α)Kℜf−1(Φ(AσgB)). |
Proof. Compute
ℜ(f−1(Φ(A))σhf−1(Φ(B)))≤sec2(α)ℜ(f−1(Φ(A)))σhℜ(f−1(Φ(B)))(by Lemma 2.2)≤sec2(α)ℜ−1(f(Φ(A)))σhℜ−1(f(Φ(B)))(by Lemma 2.6)≤sec2(α)f−1(ℜ(Φ(A)))σhf−1(ℜ(Φ(B)))(by Lemma 2.1)≤sec2(α)Kf−1(Φ(ℜAσgℜB))(by inequality (1.2))≤sec2(α)Kf−1(cos2(α)Φ(ℜ(AσgB)))(by Lemma 2.2)≤sec4(α)Kf−1(Φ(ℜ(AσgB)))(by Lemma 2.4)≤sec6(α)Kℜ−1(f(Φ(AσgB)))(by Lemma 2.1)≤sec8(α)Kℜf−1(Φ(AσgB)),(by Lemma 2.6) |
which completes the proof.
Note that when A,B≥0 in Theorem 2.4, we get inequality (1.2).
Theorem 2.5. Let A∈Mn(C) be such that W(A)⊆Sα and f∈m. Then for any positive unital linear map Φ,
f(Φ(A♯A∗))≥cos2(α)ℜ(Φf(A)). |
Proof. Compute
f(Φ(A♯A∗))=f(Φ(ℜ(A♯A∗)))≥Φf(ℜ(A♯A∗))(by inequality (1.10))≥Φf(ℜA♯ℜA∗)(by Lemma 2.2)=Φf(ℜA)≥cos2(α)ℜ(Φf(A)),(by Lemma 2.1) |
which completes the proof.
Corollary 2.1. Let A∈Mn(C) be accretive. Then
A♯A∗≥ℜA. |
Corollary 2.2. Let A∈Mn(C) be contractive. Then
In−A∗A≤(In−A∗)(In+A)♯(In+A∗)(In−A). |
In particular, if A=U is unitary, then 0≤(U−U∗)♯(U∗−U).
In [17], the authors obtained that (In−A∗B)♯(In−B∗A)≥(In−A∗A)♯(In−B∗B) for contractions A,B∈Mn(C). Imposing Φ on both sides implies Φ((In−A∗B)♯(In−B∗A))≥Φ((In−A∗A)♯(In−B∗B)). We note that a stronger result holds Φ((In−A∗B)♯(In−B∗A))≥Φ(In−A∗A)♯Φ(In−B∗B).
Theorem 2.6. Let A∈Mn(C) be such that W(A)⊆Sα and f∈m. Then for any positive unital linear map Φ,
f−1(Φ(A♯A∗))≤sec4(α)ℜ(Φf−1(A)). |
Proof. We have
f−1(Φ(A♯A∗))≤Φ−1(f(A♯A∗))(by inequality (1.10))≤Φ(f−1(A♯A∗))(by inequality (1.8))≤Φ(f−1(ℜA))(by Corollary 2.1)≤sec2(α)Φ(ℜ−1f(A))(by Lemma 2.1)≤sec4(α)ℜ(Φf−1(A)),(by Lemma 2.6) |
which completes the proof.
Theorem 2.7. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f∈m and t∈(0,1), then for every positive unital linear map Φ,
ℜ(Φ(f(A!tB)))≤sec4(α)ℜ(f(Φ(A))!tf(Φ(B))). |
Proof. Compute
ℜ(Φ(f(A!tB)))≤sec2(α)Φf(ℜ(A!tB))(by Lemma 2.1)≤sec2(α)Φf(sec2(α)ℜA!tℜB)(by Lemma 2.2)≤sec4(α)Φf(ℜA!tℜB)(by Lemma 2.4)≤sec4(α)f(Φ(ℜA!tℜB))(by inequality (1.10))≤sec4(α)f(Φ(ℜA)!tΦ(ℜB))(by inequality (1.7))=sec4(α)f(ℜ(Φ(A))!tℜ(Φ(B)))≤sec4(α)f(ℜ(Φ(A)))!tf(ℜ(Φ(B)))(by Theorem 4 in [8])≤sec4(α)ℜf(Φ(A))!tℜf(Φ(B))(by Lemma 2.1)≤sec4(α)ℜ(f(Φ(A))!tf(Φ(B))),(by Lemma 2.2) |
which completes the proof.
Theorem 2.8. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and 0<mIn≤ℜA,ℜB≤MIn. If f∈m and t∈(0,1), then
ℜf−1(A∇tB)≤sec4(α)ℜ(f−1(A)!tf−1(B)). |
Proof. Compute
ℜf−1(A∇tB)≤(ℜf(A∇tB))−1(by Lemma 2.6)≤f−1(ℜA∇tℜB)(by Lemma 2.1)≤f−1(ℜA)!tf−1(ℜB)(by Remark 2.6 in [2])≤sec2(α)ℜ−1(f(A))!tℜ−1(f(B))(by Lemma 2.1)≤sec4(α)ℜf−1(A)!tℜf−1(B)(by Lemma 2.6)≤sec4(α)ℜ(f−1(A)!tf−1(B)),(by Lemma 2.2) |
which completes the proof.
Theorem 2.9. Let A,B∈Mn with W(A),W(B)⊂Sα and 0<mIn≤ℜ(A),ℜ(B)≤MIn. If g,h∈m are such that g′(1)=h′(1)=t for some t∈(0,1), then for every positive unital linear map Φ,
‖Φ(ℜ(AσgB))Φ−1(ℜ(AσhB))‖≤sec2(α)K. | (2.1) |
Proof. From 0<mIn≤ℜ(A),ℜ(B)≤MIn we have
(1−t)(M−ℜ(A))(m−ℜA)A−1≤0, |
which is equivalent to
(1−t)ℜ(A)+(1−t)Mmℜ−1(A)≤(1−t)(M+m)In. | (2.2) |
Similarly, we have
tℜ(B)+tMmℜ−1(B)≤t(M+m)In. | (2.3) |
Summing up inequalities (2.2) and (2.3), we get
ℜ(A∇tB)+Mm(ℜ−1(A)∇tℜ−1(B))≤(M+m)In. | (2.4) |
By computation, we have
‖sec2(α)MmΦ(ℜ(AσgB))Φ−1(ℜ(AσhB))‖≤14‖Φ(ℜ(AσgB))+sec2(α)MmΦ−1(ℜ(AσhB))‖2(by Lemma 2.7)≤14‖Φ(ℜ(AσgB))+sec2(α)MmΦ(ℜ−1(AσhB))‖2(by inequality (1.8))≤14‖Φ(ℜ(AσgB))+sec2(α)MmΦ((ℜAσhℜB)−1)‖2(by Lemma 2.2)≤14‖Φ(ℜ(AσgB))+sec2(α)MmΦ((ℜA!tℜB)−1)‖2=14‖Φ(ℜ(AσgB))+sec2(α)MmΦ(ℜ−1A∇tℜ−1B)‖2≤14‖sec2(α)Φ(ℜ(A∇tB))+sec2(α)MmΦ(ℜ−1A∇tℜ−1B)‖2(by Theorem 5.2 in [3])=14‖sec2(α)Φ(ℜ(A∇tB)+Mm(ℜ−1A∇tℜ−1B))‖2≤14sec4(α)(M+m)2.(by inequality (2.4)) |
That is,
‖Φ(ℜ(AσgB))Φ−1(ℜ(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,B∈Mn(C) be such that W(A),W(B)⊆Sα and t∈(0,1). Then for every positive unital linear map Φ,
ℜF−1t(Φ(A),Φ(B))≤sec2(α)ℜFt(Φ(A−1),Φ(B−1)). |
Proof. We have the following chain of inequalities
ℜF−1t(Φ(A),Φ(B))=ℜ(tΦ(A)∇Φ(B)+(1−t)Φ(A)♯Φ(B))−1≤ℜ−1(tΦ(A)∇Φ(B)+(1−t)Φ(A)♯Φ(B))(by Lemma 2.6)=(tΦ(ℜA)∇Φ(ℜB)+(1−t)ℜ(Φ(A)♯Φ(B)))−1≤t(Φ(ℜA)∇Φ(ℜB))−1+(1−t)ℜ−1(Φ(A)♯Φ(B))≤tΦ((ℜA∇ℜB)−1)+(1−t)(ℜΦ(A)♯ℜΦ(B))−1(by Lemma 2.2 and (1.8))=tΦ((ℜA∇ℜB)−1)+(1−t)Φ−1(ℜA)♯Φ−1(ℜB)≤tΦ((ℜA∇ℜB)−1)+(1−t)Φ(ℜ−1A)♯Φ(ℜ−1B)(by (1.8))≤tΦ((ℜA∇ℜB)−1)+(1−t)sec2(α)Φ(ℜA−1)♯Φ(ℜB−1)(by Lemma 2.6)≤tΦ(ℜ−1A∇ℜ−1B)+(1−t)sec2(α)ℜ(Φ(A−1)♯Φ(B−1))(by Lemma 2.2)≤tsec2(α)Φ(ℜ(A−1)∇ℜ(B−1))+(1−t)sec2(α)ℜ(Φ(A−1)♯Φ(B−1))(by Lemma 2.6)=tsec2(α)ℜ(Φ(A−1)∇Φ(B−1))+(1−t)sec2(α)ℜ(Φ(A−1)♯Φ(B−1))=sec2(α)ℜFt(Φ(A−1),Φ(B−1)), |
which completes the proof.
We note that by letting Φ(X)=X for every X∈Mn(C) in Theorem 2.10, we get the right hand side of inequalities in Theorem 3 in [11].
Theorem 2.11. Let A,B∈Mn(C) be such that W(A),W(B)⊆Sα and t∈(0,1). Then
cos2t+1(α)ω(A♯B)≤ω(Ft(A,B))≤sec3(α)(1−tsin2(α)ω(A∇B). |
Proof. Compute
ω(A♯B)≤‖A♯B‖(by inequality (1.1))≤sec(α)‖ℜ(A♯B)‖(by Lemma 2.5)≤sec2t+1(α)‖ℜFt(A,B)‖(by Theorem 1 in [11])=sec2t+1(α)ω(ℜFt(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)‖ℜ(Ft(A,B))‖(by Lemma 2.5)≤sec3(α)(1−tsin2(α))‖ℜ(A∇B)‖(by Theorem 1 in [11]) =sec3(α)(1−tsin2(α))ω(ℜ(A∇B))≤sec3(α)(1−tsin2(α))ω(A∇B),(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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