Next Article in Journal
Numerical Solutions of Space-Fractional Advection–Diffusion–Reaction Equations
Next Article in Special Issue
The Role of the Discount Policy of Prepayment on Environmentally Friendly Inventory Management
Previous Article in Journal
Shifted Fractional-Order Jacobi Collocation Method for Solving Variable-Order Fractional Integro-Differential Equation with Weakly Singular Kernel
Previous Article in Special Issue
Some Hadamard–Fejér Type Inequalities for LR-Convex Interval-Valued Functions
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials

1
School of Mathematics and Statistics, Zhengzhou Normal University, Zhengzhou 450000, China
2
School of Science, Zhengzhou University of Aeronautics, Zhengzhou 450000, China
3
School of Information, Beijing Wuzi University, Beijing 101149, China
4
Beijing Institute of Technology, School of Mathematics and Statistics, Beijing 100081, China
5
Yangtze Delta Region Academy of Beijing Institute of Technology, Jiaxing 314000, China
*
Author to whom correspondence should be addressed.
Fractal Fract. 2022, 6(1), 20; https://doi.org/10.3390/fractalfract6010020
Submission received: 18 October 2021 / Revised: 29 November 2021 / Accepted: 9 December 2021 / Published: 31 December 2021
(This article belongs to the Special Issue Advances in Optimization and Nonlinear Analysis)

Abstract

:
The Lieb concavity theorem, successfully solved in the Wigner–Yanase–Dyson conjecture, is an important application of matrix concave functions. Recently, the Thompson–Golden theorem, a corollary of the Lieb concavity theorem, was extended to deformed exponentials. Hence, it is worthwhile to study the Lieb concavity theorem for deformed exponentials. In this paper, the Pick function is used to obtain a generalization of the Lieb concavity theorem for deformed exponentials, and some corollaries associated with exterior algebra are obtained.

1. Introduction

Matrix theory is widely used in statistics [1], physics [2], computer science [3] and so on. For convenience, M ( n , C ) is denoted as the set of all n × n complex matrices ( C is the set of complex numbers) [4]. A is called a Hermitian matrix when A M ( n , C ) satisfies A * = A ( A * denotes conjugate transposition of A). The Hermitian matrix is frequently used in quadratic forms and their correlation theory [5]. Let H n denote the set of n × n Hermitian matrices and H n + denote the n × n positive semidefinite Hermitian matrix ( C n is the n dimensional complex Euclidean space).
Set u 1 , u 2 , , u n to be any orthonormal basis of C n , and then the trace operator Tr is defined as [4]
Tr [ A ] = i = 1 n ( u i , A u i ) ,
where ( · , · ) is the inner product of C n . It is well known that for any A = ( a i j ) M ( n , C ) , the following equalities hold [6]
Tr [ A ] = j = 1 n λ i = j = 1 n a i i ,
where λ i is the eigenvalue of A.
From the spectral theorem [5], A H n + can be decomposed as
A = P * Λ A P ,
where P is a unitary matrix and Λ A : = diag { λ 1 , . . . , λ n } is a diagonal matrix with eigenvalues λ 1 , . . . , λ n . Then, matrix function f ( A ) is defined as
f ( A ) = P * f ( Λ A ) P = i = 1 f ( λ i ) P i ,
where f ( Λ A ) : = diag { f ( λ 1 ) , . . . , f ( λ n ) } and P i 2 = P i .
Based on the above definition, in 1963, the Wigner–Yanase skew information
I W Y ( ρ ) = 1 2 Tr [ ρ , H ] 2
was introduced by Wigner and Yanase ([7]), where ρ is a density matrix ( ρ 0 , tr ρ = 1 ) and H is a Hermitian matrix. Then, an open problem was left
Tr [ A s K A 1 s K * ] ,
which is concave for any positive semidefinite matrix A.
In 1973, (2) was proven by Lieb for all 0 < s < 1 [8], and a more generalized result was obtained from the following fact [9]
Tr [ A s K B 1 s K * ] = K , B 1 s K * A s L ( H ) = K , Ψ 1 ( B 1 s A s ) K * L ( H ) .
where Ψ 1 ( A ) = j ( A e j ) e j * . In fact, the Lieb concavity theorem is equivalent to the concavity of B 1 s A s .
A more elegant proof of the Lieb concavity theorem appeared in [10] using
Tr [ K * A s K B 1 s ] = K , ( A s B 1 s ) K L ( H ) ,
where
[ ( A B ) K ] i , j = k , l A i , k B j , l K k , l .
In 2009, Effros gave another proof of the Lieb concavity theorem based on the Hansen–Pedersen–Jensen inequality ([11]). Using
L A ( K ) = A K , R B ( K ) = K B ,
then one obtains
Tr [ K * A s K B 1 s ] = K , L A s R B 1 s ( K ) L ( H ) = K , R B 1 2 ( R B 1 2 L A R B 1 2 ) s R B 1 2 ( K ) L ( H ) .
All the above proof of the Lieb concave theorem is equivalent to the joint concavity of commutative operators. In addition, Epstein also obtained the Lieb concave theorem using the theory of Herglotz functions [12].
Recently, Shi and Hansen [13] generalized the Thompson–Golden theorem
Tr [ exp q ( A + B ) ] Tr [ ( exp q ( A ) ) 2 q ( A ( q 1 ) + exp q ( B ) ) ]
As the Thompson–Golden theorem can be regarded as a special form of the Lieb concave theorem, it is worthwhile to study the Lieb concavity theorem for deformed exponentials. In this paper, we will use the theory of the Pick function to obtain a generalization of the Lieb concavity theorem and some other corollaries. The rest of the paper is organized as follows. In Section 2, some general definitions and important conclusions are introduced. With these preparations, we obtain some useful results, such as the Lieb concavity theorem, presented in the final Section 3.

2. Preliminary

In this section, some general definitions and some important properties are introduced.

2.1. The q-Logarithm Function and q-Exponential Function

It is well known that the q-logarithm function ln q ( x ) is defined as [13]
ln q ( x ) = x q 1 1 q 1 , q 1 ln x , q = 1
for any x > 0 . The deformed exponential function or the q - exponential exp q ( x ) is the inverse function of the q - logarithm and is defined as
exp q ( x ) = [ ( q 1 ) x + 1 ] 1 q 1 , x > 1 q 1 , q > 1 [ ( q 1 ) x + 1 ] 1 q 1 , x < 1 q 1 , q < 1 exp ( x ) , x R , q = 1

2.2. Tensor Product and Exterior Algebra

The tensor product, denoted by , is also called the Kronecker product. It is a generalization of the outer product from vectors to matrices, and the tensor product of matrices is also referred to as the outer product in certain contexts ([9]). For an m × n matrix A and a p × q matrix B, the tensor product of A and B is defined by
A B : = a 11 B a 1 n B a m 1 B a m n B ,
where A = a i j 1 i m , 1 j n .
The tensor product is different from matrix multiplication, and one of the differences is commutativity
( I B ) ( A I ) = ( A I ) ( I B ) = A B .
From the above equations, we obtain
A C B D = ( A C I ) ( I B D ) = ( A I ) ( C I ) ( I B ) ( I D ) = ( A I ) ( I B ) ( C I ) ( I D ) = ( A B ) ( C D ) .
For convenience, we denote
k A = A A A k .
In addition to the tensor product, there is another common product called exterior algebra [6]. Exterior algebra, denoted by , is a binary operation for any A i H n + , and the definition is
( A 1 A 2 A k k ) ( ξ i 1 ξ i 2 ξ i k ) 1 i 1 < < i k n = ( A 1 ξ i 1 A 2 ξ i 2 A k ξ i k ) 1 i 1 < < i k n ,
where { ξ j } j = 1 n is an orthonormal basis of C n , and
ξ i 1 ξ i 2 ξ i k = 1 n ! π σ n ( 1 ) π ξ π ( i 1 ) ξ π ( i 2 ) ξ π ( i k ) ,
σ n is the family of all permutations on { 1 , 2 , , n } .
Let k C n be the span of the { ξ i 1 ξ i 2 ξ i k } 1 i 1 < < i k n , and then a simple calculation shows that
n A = ( A A A k ) = det ( A )

2.3. Pick Function

Let z = x + i y be a complex number where i is the imaginary unit and f ( z ) = U ( z ) + i V ( z ) is analytic where U ( z ) , V ( z ) are all real functions. Re z = x denotes the real part of z, and Im z = y is the imaginary part of z. If Im f ( z ) > 0 for any Im z > 0 , then we call the analytic function f ( z ) a Pick function [14]. It is equivalent that f ( z ) is analytic in the upper half-plane with the positive imaginary part.
The Pick functions evidently form a convex cone—for instance, if α and β are positive numbers and f ( z ) and g ( z ) are two Pick functions, then the function α f ( z ) + β g ( z ) is also a Pick function. A simple example is that tan ( z ) is a Pick function.
tan ( x + i y ) = tan ( x ) + tan ( i y ) 1 tan ( x ) tan ( i y ) = tan ( x ) + i tanh ( y ) 1 i tan ( x ) tanh ( y ) .
Hence, Im tan ( z ) = ( 1 + tan 2 ( x ) ) tanh ( y ) 1 + tan 2 ( x ) tanh 2 ( y ) , and this implies that Im tan ( z ) > 0 when y > 0 .
It is well known that the Pick function has a integral representation, such as the following lemma [14].
Lemma 1.
Let f ( z ) be a Pick function. Then, f ( z ) has a unique canonical representation of the form
f ( z ) = α + β z + R 1 λ z λ 1 + λ 2 d μ ( λ ) ,
where α is real, β 0 and d μ ( λ ) is a positive Borel measure on the real λ - axis that R ( 1 + λ 2 ) 1 d μ ( λ ) is finite. Conversely, any function of this form is also a Pick function.
Lemma 1 is frequently used for functions that are positive and harmonic in the half-plane.

2.4. The Matrix-Monotone Function

A matrix function f is said to be matrix-monotonic if it satisfies
f ( A ) f ( B ) for all A B > 0 .
where A B > is equivalent to A B is a positive semidefinite Hermitian matrix.
Since the matrix-monotone function is a special kind of operator monotone function, we have the following general conclusions [14].
Lemma 2.
The following statements for a real valued continuous function f on ( 0 , + ) are equivalent:
( 1 ) f ( z ) is matrix-monotone;
( 2 ) f ( z ) admits an analytic continuation to the whole domain Im z 0 and Im ( z ) Im f ( z ) 0 .
( 3 ) f admits an integral representation:
f ( λ ) = α + β λ + 0 ( 1 + λ t ) ( t λ ) 1 d μ ( t ) , for   any   λ > 0 ,
where α is a real number, β is non-negative and μ is a finite positive measure on ( , 0 ) .
From Lemmas 1 and 2, we know that a Pick function must be a matrix-monotone function.

2.5. Convexity of Matrix

Suppose that X is a convex set in R n and f is a function defined on X. Then, we call f a convex function if
f ( t x 1 + ( 1 t ) x 2 ) t f ( x 1 ) + ( 1 t ) f ( x 2 ) , x 1 , x 2 X , t [ 0 , 1 ] ,
for all x 1 , x 2 X and t [ 0 , 1 ] .
A matrix function f is called convex if [15,16,17]
f ( t A + ( 1 t ) B ) t f ( A ) + ( 1 t ) f ( B ) ,
for any A , B H n + and any t [ 0 , 1 ] . Replacing ≤ by < in (5), this gives the definition of a strictly matrix convex function. A matrix function f is called (strictly) concave if f is (strictly) convex. More details can be found in [18].
A matrix convex function must be a convex function; however, the inverse claim is not always true. For instance, the function f : [ 0 , + ) R given by f ( x ) = x 3 is a convex function. However, the matrix function f ( A ) = A 3 for any A H n + is not convex.
Let f ( · , · ) be a bivariate function defined on H n + × H n + . We call f ( · , · ) jointly convex if
f ( t A 1 + ( 1 t ) A 2 , t B 1 + ( 1 t ) B 2 ) t f ( A 1 , B 1 ) + ( 1 t ) f ( A 2 , B 2 ) ,
for all A 1 , A 2 , B 1 , B 2 H n + and all t [ 0 , 1 ] .

2.6. Brunn–Minkowski Inequality

Finally, let us review the Brunn–Minkowski inequality [19].
Lemma 3.
For any A , B > 0 , and then
{ Tr [ k ( A + B ) ] } 1 k { Tr [ k A ] } 1 k + { Tr [ k B ] } 1 k .
Proof. 
Let { ξ i } i = 1 n be the eigenvectors of A + B with the eigenvalue { λ i } i = 1 n , then
{ Tr [ k ( A + B ) ] } 1 k = 1 ξ i 1 < < ξ i k n λ i 1 λ i k 1 k = 1 ξ i 1 < < ξ i k n det P i 1 , , i k * ( A + B ) P i 1 , , i k 1 k 1 ξ i 1 < < ξ i k n det P i 1 , , i k * A P i 1 , , i k + det P i 1 , , i k * B P i 1 , , i k 1 k
where P i 1 , , i k = ( ξ i 1 , , ξ i k ) and ≥ holds due to det ( A + B ) det ( A ) + det ( B ) .
As S k = 1 ξ i 1 < < ξ i k n x i 1 x i k 1 k is concave [20], we have
{ Tr [ k ( A + B ) ] } 1 k 1 ξ i 1 < < ξ i k n det P i 1 , , i k * A P i 1 , , i k 1 k + 1 ξ i 1 < < ξ i k n det P i 1 , , i k * B P i 1 , , i k 1 k = 1 ξ i 1 < < ξ i k n ξ i 1 ξ i k , A ξ i 1 A ξ i k 1 k + 1 ξ i 1 < < ξ i k n ξ i 1 ξ i k , B ξ i 1 B ξ i k 1 k = { Tr [ k A ] } 1 k + { Tr [ k B ] } 1 k .

3. Lieb Concavity Theorem for Deformed Exponential

In this section, we obtain some useful conclusions, and some simple and straightforward computations are omitted. Recently, by using the Young inequality,
Tr [ Y ] = max X 0 { Tr [ X ] Tr [ X 2 q ( ln q X ln q Y ) ] } ,
Shi and Hansen obtained that F ( A ) = Tr exp q 1 p ( K * ln q ( A p ) K ) is concave for any 1 q 2 where K * K I (I is the identity matrix of M ( n , C ) ) [13], namely, the following theorem.
Theorem 1.
For 0 < p 1 , 1 < q 2 and K * K I , the function
F ( A ) = Tr exp q 1 p ( K * ln q ( A p ) K )
is concave for the strictly positive A H n + .
Proof. (The first proof of Theorem 1)
 
Since [21]
D f ( A ) ( B ) = i j f ( λ i ) f ( λ j ) λ i λ i P i B P j ,
we obtain
d ( Tr [ f ( A + t B ) f ( A ) ] ) d t = Tr i j f ( λ i ) f ( λ j ) λ i λ i P i B P j = Tr i P j j f ( λ i ) f ( λ j ) λ i λ i P i B = Tr i f ( λ i ) P i B = Tr [ f ( A ) B ] ,
where λ i are eigenvalues of A. When f ( x ) is a convex function, we obtain
Tr [ f ( A + t B ) f ( A ) ] Tr [ f ( A ) t B ]
for any t. This implies that
Tr [ f ( C ) ] = max { Tr [ f ( D ) + f ( D ) ( C D ) ] : D > 0 } .
Therefore, we obtain
Tr [ ( K * A p q p K + I K * K ) 1 p q p ] = max { Tr [ D 1 p q p + D 1 p q p 1 ( K * A p q p K + I K * K D ) p q p ] : D > 0 } = max { Tr [ C + C 1 p q + p ( K * A p q p K + I K * K C p q p ) p q p ] : C = D 1 p q p > 0 } = max { Tr [ C ( 1 1 p q p ) + C 1 p q + p K * A p q p K p q p + C 1 p q + p ( I K * K ) ] : C > 0 }
Thus, the concavity of F ( A ) is equivalent to the jointly concavity of Tr [ C 1 p q + p K * A p q p K p q p ] for the strictly positive A and C, which is the Lieb concavity theorem [22,23]. □
Unfortunately, Theorem 1 cannot be obtained using Epstein’s theorem. Hence, we require a more general generalization of Epstein’s theorem. First, for any Im ( z ) > 0 , we know that A + z B is invertible and x * ( A + z B ) x is a Pick function for any x C n [14]. For any A M ( n , C ) , we know f ( A ) is defined as [12]
f ( A ) = 1 2 π C f ( z ) z A d z ,
where f ( z ) is a complex holomorphic function in an open set of the complex plane containing Sp ( A ) (the set of all eigenvalues of A). Then, we have the following lemma.
Lemma 4.
Let A , B H n + and 0 < α 1 , then
x * ( A + z B ) α x
is a Pick function for any x C n and 0 < arg ( x * ( A + z B ) α x ) < α π if 0 < arg ( z ) = θ < π , such as Sp ( ( A + z B ) α ) ( Sp ( A + z B ) α ) . Generally, we can find that
x * f ( A + z B ) x
is a Pick function when f is a Pick function.
Proof. 
Setting z = ρ e i θ , we have
( A + z B ) α = 0 + ( A + z B t + A + z B ) d μ ( t ) = 0 + ( 1 t A + z B + 1 ) d μ ( t ) ,
where d μ ( t ) = t α 1 π sin α π .
Since Im z > 0 , we see that A + z B is invertible. Hence, we have
x * ( A + z B ) α x = 0 + x * ( 1 t A + z B + 1 ) x d μ ( t ) = 0 + y * ( t A + z * B + 1 ) y d μ ( t ) , y = ( t A + z B + 1 ) 1 x = 0 + y * y + t w * ( A + z B ) w d μ ( t ) , w = ( A + z * B ) 1 y = 0 + y * y + t w * A w d μ ( t ) + z 0 + t w * B w d μ ( t ) .
This implies that
Im x * ( A + z B ) α x = Im ( z ) · 0 + t w * B w d μ ( t ) > 0 ;
hence, 0 < arg ( x * ( A + z B ) α x ) when 0 < arg ( z ) = θ < π .
In the same way, we can obtain
Im w * [ ( A z * B ) α ] w = Im ( e i α π z * ) · 0 + t v * B v d μ ( t ) < 0 , v = ( t ( A + z * B ) + 1 ) 1 w .
In particular, letting w = ( A + z * B ) α x , we have
Im ( e i α π x * ( A + z B ) α x ) < 0 .
This is equivalent to arg ( x * ( A + z B ) α x ) < α π .
To prove Sp ( ( A + z B ) α ) ( Sp ( A + z B ) α ) , let ( A + z B ) ξ = λ ξ , we find
ξ * ( A + z B ) α ξ = ξ * ( A + z B ) ξ α = [ ξ * A ξ + z ξ * B ξ ] α = ρ α e i α θ ,
where tan θ = ξ * B ξ Im ( z ) ξ * A ξ + ξ * B ξ Re ( z ) tan arg ( z ) .
When f ( z ) is a Pick function, using the integral represented of f ( z ) , in a similar way, we can obtain that
x * f ( A + z B ) x
is a Pick function for any x C n . □
Using Lemma 4, another proof of Theorem 1 can be obtained.
Theorem 2.
For 0 < p 1 , 1 < q 2 and K * K I , the function
F ( A ) = Tr exp q 1 p ( K * ln q ( A p ) K )
is concave for the strictly positive A H n + .
Proof. (The second proof of Theorem 1)
 
First, setting f ( z ) = Tr [ ( A ( z ) + i B ( z ) ) 1 p q p ] where A ( z ) = Re ( K * ( A + z B ) p q p K + I K * K ) and B ( z ) = Im ( K * ( A + z B ) p q p K + I K * K ) H n + . As
Im Tr [ ( A ( z ) + i B ( z ) ) 1 p q p ] = Im Tr [ 0 + ( A ( z ) + i B ( z ) t + A ( z ) + i B ( z ) ) d μ ( t ) ] = Im 0 + Tr [ ( Λ A ( z ) + i B ( z ) t + Λ A ( z ) + i B ( z ) ) d μ ( t ) ] = Im 0 + i = 1 n [ ( λ i ( A ( z ) + i B ( z ) ) t + λ i ( A ( z ) + i B ( z ) ) ) d μ ( t ) ] = Im i = 1 n [ ( λ i ( A ( z ) + i B ( z ) ) 1 p q p ] ,
when arg ( z ) ( 0 , π ) and K * K I , then
arg ( λ i ( A ( z ) + i B ( z ) ) ) = arg ( x i * ( A ( z ) + i B ( z ) ) x i ) = arg ( x i * K * ( A + z B ) p q p K x i + x i * ( I K * K ) x i ) ( 0 , ( p q p ) π ) ,
where x i C n are the eigenvectors of K * ( A + z B ) p q p K + I K * K .
Hence,
Im Tr [ ( A ( z ) + i B ( z ) ) 1 p q p ] = Im i = 1 n z i ,
where z i is the i eigenvalue of ( A ( z ) + i B ( z ) ) 1 p q p and arg ( z i ) ( 0 , π ) .
Thus, f ( z ) = Tr [ ( A ( z ) + i B ( z ) ) 1 p q p ] is a Pick function, and this implies that F ( A ) is concave. □
Using a similar method, we can obtain the following corollary.
Corollary 1.
For 0 < p 1 and 1 < q 2 , the function
E ( A ) = Tr exp q 1 p [ B + ln q ( A p ) ]
is concave for the strictly positive A H n + .
Since the Thompson–Golden theorem can be seen as a corollary of the Lieb concavity theorem, we discuss the Lieb concavity theorem for deformed exponentials. Setting SP ( A ) { z = ρ e i θ : 0 < ρ , 0 < θ < α } and SP ( B ) { z = ρ e i θ : 0 < ρ , 0 < θ < β } , then for any A 1 , B 1 H n , A 2 , B 2 H n + and A = A 1 + i A 2 , B = B 1 + i B 2 , we have [12]
SP ( A B ) { z = ρ e i θ : 0 < ρ , 0 < θ < α + β } .
and then the following theorem can be obtained.
Theorem 3.
For 0 < p 1 , 1 < q 2 and P * P I , the following function
L ( A ) = Tr [ exp q ( P * ln q ( K * A p K ) P ) exp q ( P * ln q A 1 p P ) ]
is concave for any A H n + .
Proof. 
Set L A , B ( z ) = Tr [ exp q ( P * ln q ( K * ( A + z B ) p K ) P ) exp q ( P * ln q ( A + z B ) 1 p P ) ] .
When x i C n is a eigenvector of P * ( A + z B ) p q p P + I P * P and P * P I ,
arg ( x i * P * K * ( A + z B ) p q p K P x i + x i * ( I P * P ) x i ) ( 0 , ( p q p ) π ) ,
if arg ( z ) ( 0 , π ) . This implies
SP ( P * K * ( A + z B ) p q p K P + I P * P ) { z = ρ e i θ : 0 < ρ , 0 < θ < ( p q p ) π } ,
such as
SP ( exp q ( P * ln q ( K * ( A + z B ) p K ) P ) ) { z = ρ e i θ : 0 < ρ , 0 < θ < p π } .
Similarly, we can also obtain
SP ( exp q ( P * ln q ( A + z B ) 1 p P ) ) { z = ρ e i θ : 0 < ρ , 0 < θ < ( 1 p ) π } .
Hence, using Equation (8), we see that
SP [ exp q ( P * ln q ( K * ( A + z B ) p K ) P ) exp q ( P * ln q ( A + z B ) 1 p P ) ] { z = ρ e i θ : 0 < ρ , 0 < θ < π } .
Thus, we know arg ( L A , B ( z ) ) ( 0 , π ) , which implies that L A , B ( z ) is a Pick function. Hence, L(A) is concave. □
In fact, Theorem 3 is a generalization of the Lieb concavity theorem setting P = I , K = 0 0 H 0 and A = Z 0 0 B . Moreover, we can obtain the following theorem.
Theorem 4.
For 0 < p , s 1 , 1 < q 2 and P * P I , the functions
Tr exp q ( P * ln q A p s 2 P ) exp q ( P * ln q ( K * A s s p K ) P ) exp q ( P * ln q A p s 2 P ) 1 s
and
Tr exp q ( P * ln q A p s 2 P ) exp q ( P * ln q ( K * A s s p K ) P ) exp q ( P * ln q A p s 2 P ) 1 s
are jointly concave for any A H n + .
The proof of Theorem 4 is similar to Theorem 3; here, we do not repeat the proof. In [19], Huang used exterior algebra to find that
[ Tr k exp ( K * ln ( A ) K ) ] 1 k
is a concave function for any A H n + , K * K I and k n . Associated with Theorem 1, we can obtain a generalization as the following theorem.
Theorem 5.
For 0 < p 1 , 1 < q 2 and K * K I , the function
Tr k exp q 1 p ( K * ln q ( A p ) K ) 1 k
is concave for the strictly positive A H n + and k n .
Proof. 
In fact, we can prove that
Tr k ( H * A s H + B ) 1 s 1 k
is a concave function for any A H n + where 0 < s 1 and B H n + .
Using Theorem 1, we know that
Tr ( H * A p H + C ) 1 p
is a concave function for any A H n + where 0 < p 1 and C H n + .
Then, for any A 1 , A 2 H n + , we have
Tr k ( H * ( A 1 + A 2 2 ) s H + B ) 1 s 1 k = Tr ( H ¯ * ( A 1 k 1 I + A 2 k I 2 ) s H ¯ + B ¯ ) 1 s 1 k Tr ( H ¯ * ( A 1 k 1 I ) s H ¯ + B ¯ ) 1 s + ( H ¯ * ( A 2 k 1 I ) s H ¯ + B ¯ ) 1 s 2 1 k = Tr ( H * A 1 s H + B ) 1 s + ( H * A 2 s H + B ) 1 s 2 k 1 ( H * ( A 1 + A 2 2 ) s H + B ) 1 s 1 k ,
where H ¯ = H k 1 ( H * ( A 1 + A 2 2 ) s H + B ) 1 s and B ¯ = B k 1 ( H * ( A 1 + A 2 2 ) s H + B ) 1 s . Analogously, we can obtain
Tr k ( H * ( A 1 + A 2 2 ) s H + B ) 1 s 1 k Tr k ( H * A 1 s H + B ) 1 s + ( H * A 2 s H + B ) 1 s 2 1 k .
Using lemma 3, we obtain
Tr k ( H * ( A 1 + A 2 2 ) s H + B ) 1 s 1 k Tr k ( H * A 1 s H + B ) 1 s 1 k + Tr k ( H * A 2 s H + B ) 1 s 1 k 2 .
Clearly, the proof of Theorem 5 is in the application of exterior algebra and the Brunn–Minkowski inequality. Hence, other theorems, such as the Thompson–Golden theorem in a deformed exponential, can be generalized to a more general form, but we do not discuss this here.

4. Conclusions

In this paper, we used the Pick function to obtain a generalization of the Lieb concavity theorem and some corollaries. The advantage of using the Pick function is that it avoids discussing the commutativity of the matrix and variational method. Generally, we obtain that the following two functions are concave for 0 < p , s 1 , 1 < q 2 and P * P I
Tr k exp q ( P * ln q A p s 2 P ) exp q ( P * ln q ( K * A s s p K ) P ) exp q ( P * ln q A p s 2 P ) 1 s 1 k
and
Tr k [ exp q ( P * ln q A p s 2 P ) exp q ( P * ln q ( K * A s s p K ) P ) exp q ( P * ln q A p s 2 P ) ] 1 k s ,
where A H n + and k n , and this provides work for the future.

Author Contributions

Conceptualization, H.S.; writing—original draft, G.Y. and Y.L.; writing—review and editing, J.W.; funding acquisition, J.W. All authors have read and agreed to the published version of the manuscript.

Funding

The present research was supported by the General Project of Science and Technology Plan of Beijing Municipal Education Commission (Grant No. KM202010037003).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors thank the referees for detailed reading and comments that were both helpful and insightful.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Tropp, J.A. An introduction to matrix concentration inequalities. arXiv 2015, arXiv:1501.01571. [Google Scholar]
  2. Petz, D. Quantum Information Theory and Quantum Statistics; Springer Science and Business Media: Berlin/Heidelberg, Germany, 2007. [Google Scholar]
  3. Bellman, R. Introduction to Matrix Analysis; McGraw-Hill: New York, NY, USA, 1960. [Google Scholar]
  4. Carlen, E. Trace inequalities and quantum entropy: An introductory course. Contemp. Math. 2010, 529, 73–140. [Google Scholar]
  5. Zhang, F. Matrix Theory: Basic Results and Techniques; Springer: Berlin/Heidelberg, Germany, 1999. [Google Scholar]
  6. Simon, B. Trace Ideals and Their Applications. In Mathematical Surveys and Monographs, 2nd ed.; American Mathematical Society: Providence, Rhode Island, 2005. [Google Scholar]
  7. Wigner, E.P.; Yanase, M.M. On the positive definite nature of certain matrix expressions. Cunud. J. Math. 1964, 16, 397–406. [Google Scholar] [CrossRef]
  8. Lieb, E. Convex trace functions and the Wigner–Yanase–Dyson conjecture. Adv. Math. 1973, 11, 267–288. [Google Scholar] [CrossRef] [Green Version]
  9. Bhatia, R. Positive Definite Matrices; Princeton University Press: Princeton, NJ, USA, 2007. [Google Scholar]
  10. Ando, T. Concavity of certain maps on positive definite matrices and applications to Hadamard products. Linear Algebra Appl. 1979, 26, 203–241. [Google Scholar] [CrossRef] [Green Version]
  11. Effros, E.G. A matrix convexity approach to some celebrated quantum inequalities. Proc. Natl. Acad. Sci. USA 2009, 106, 1006–1008. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  12. Epstein, H. Remarks on two theorems of E. Lieb. Comm. Math. Phys. 1973, 31, 317–325. [Google Scholar] [CrossRef]
  13. Shi, G.H.; Hansen, F. Variational representations related to Tsallis relative entropy. Lett. Math. Phys. 2020, 110, 2203–2220. [Google Scholar] [CrossRef]
  14. Donogue, W. Monotone Matrix Functions and Analytic Continuution; Springer: New York, NY, USA, 1974. [Google Scholar]
  15. Davis, C. Notions generalizing convexity for functions defined on spaces of matrices. In Convexity: Proceedings of the Seventh Symposium in Pure Mathematics of the American Mathematical Society; American Mathematical Society: Providence, Rhode Island, 1963; pp. 187–201. [Google Scholar]
  16. Choi, M.D. A Schwarz inequality for positive linear maps on C-algebras. Illinois J. Math. 1974, 18, 565–574. [Google Scholar] [CrossRef]
  17. Bendat, J.; Sherman, S. Monotone and convex operator functions. Trans. Am. Math. Soc. 1955, 79, 58–71. [Google Scholar] [CrossRef]
  18. Hansen, F. Trace Functions with Applications in Quantum Physics. J. Stat. Phys. 2014, 154, 807–818. [Google Scholar] [CrossRef] [Green Version]
  19. Huang, D. A generalized Lieb’s theorem and its applications to spectrum estimates for a sum of random matrices. Linear Algebra Appl. 2019, 579, 419–448. [Google Scholar] [CrossRef] [Green Version]
  20. Marshall, A.W.; Olkin, I.; Arnold, B.C. Inequalities: Theory of Majorization and Its Applications; Springer: New York, NY, USA, 2011. [Google Scholar]
  21. Bhatia, R. Matrix Analysis; Springer: Berlin/Heidelberg, Germany, 1997. [Google Scholar]
  22. Aujla, J.S. A simple proof of Lieb concavity theorem. J. Math. Phys. 2011, 52, 043505. [Google Scholar] [CrossRef]
  23. Nikoufar, I.; Ebadian, A.; Gordji, M.E. The simplest proof of Lieb concavity theorem. Adv. Math. 2013, 248, 531–533. [Google Scholar] [CrossRef]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Yang, G.; Li, Y.; Wang, J.; Sun, H. Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials. Fractal Fract. 2022, 6, 20. https://doi.org/10.3390/fractalfract6010020

AMA Style

Yang G, Li Y, Wang J, Sun H. Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials. Fractal and Fractional. 2022; 6(1):20. https://doi.org/10.3390/fractalfract6010020

Chicago/Turabian Style

Yang, Guozeng, Yonggang Li, Jing Wang, and Huafei Sun. 2022. "Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials" Fractal and Fractional 6, no. 1: 20. https://doi.org/10.3390/fractalfract6010020

APA Style

Yang, G., Li, Y., Wang, J., & Sun, H. (2022). Application of the Pick Function in the Lieb Concavity Theorem for Deformed Exponentials. Fractal and Fractional, 6(1), 20. https://doi.org/10.3390/fractalfract6010020

Article Metrics

Back to TopTop