the principal inverse of the gamma function
TRANSCRIPT
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The principal inverse of the gamma function
Mitsuru Uchiyama
Shimane University
2013/7
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Introduction
The gamma function Γ(x) is usually defined by the Euler form
Γ(x) =
∫ ∞
0e−ttx−1dt
for x > 0. This is extended to ℜz > 0. By Γ(z + 1) = zΓ(z) forz = 0,−1,−2, · · · it is defined and holomorphic on C \ {0,−1,−2, · · · }
The Weierstrass form
1
Γ(x)= xeγx
∞∏n=1
(1 +x
n)e−
xn (1)
is useful, where γ is the Euler constant defined by
γ = limn→∞
(1 +1
2+ · · ·+ 1
n− log n) = 0.57721 · · · .
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Introduction
The gamma function Γ(x) is usually defined by the Euler form
Γ(x) =
∫ ∞
0e−ttx−1dt
for x > 0. This is extended to ℜz > 0. By Γ(z + 1) = zΓ(z) forz = 0,−1,−2, · · · it is defined and holomorphic on C \ {0,−1,−2, · · · }The Weierstrass form
1
Γ(x)= xeγx
∞∏n=1
(1 +x
n)e−
xn (1)
is useful, where γ is the Euler constant defined by
γ = limn→∞
(1 +1
2+ · · ·+ 1
n− log n) = 0.57721 · · · .
Mitsuru Uchiyama (Shimane University) The principal inverse of the gamma function 2013/7 2 / 25
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Introduction
From (1) (Weierstrass form) it follows that
log Γ(x) = − log x − γx +∞∑n=1
(xn− log(1 +
x
n)),
Γ′(x)
Γ(x)= −γ +
∞∑n=0
(1
n + 1− 1
n + x) (psifunction) (2)
on C \ {0,−1,−2, · · · }.
By (2), Γ′(z)Γ(z) maps the open upper half plane Π+ into itself, namely Γ′(z)
Γ(z)
is a Pick (Nevanlinna) function. Γ′(z) does not vanish on Π+.
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Introduction
From (1) (Weierstrass form) it follows that
log Γ(x) = − log x − γx +∞∑n=1
(xn− log(1 +
x
n)),
Γ′(x)
Γ(x)= −γ +
∞∑n=0
(1
n + 1− 1
n + x) (psifunction) (2)
on C \ {0,−1,−2, · · · }.By (2), Γ′(z)
Γ(z) maps the open upper half plane Π+ into itself, namely Γ′(z)Γ(z)
is a Pick (Nevanlinna) function.
Γ′(z) does not vanish on Π+.
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Introduction
From (1) (Weierstrass form) it follows that
log Γ(x) = − log x − γx +∞∑n=1
(xn− log(1 +
x
n)),
Γ′(x)
Γ(x)= −γ +
∞∑n=0
(1
n + 1− 1
n + x) (psifunction) (2)
on C \ {0,−1,−2, · · · }.By (2), Γ′(z)
Γ(z) maps the open upper half plane Π+ into itself, namely Γ′(z)Γ(z)
is a Pick (Nevanlinna) function. Γ′(z) does not vanish on Π+.
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Introduction
-2 2 4
-20
-10
10
20
Figure : Gamma function
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Introduction
Γ(1) = Γ(2) = 1, Γ′(1) = −γ, Γ′(2) = −γ + 1.
Denote the unique zero in (0,∞) of Γ′(x) by α.
α = 1.4616 · · · , Γ(α) = 0.8856 · · ·.
We call the inverse function of the restriction of Γ(x) to (α,∞) theprincipal inverse function and write Γ−1.Γ−1(x) is an increasing and concave function defined on (Γ(α),∞).
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Introduction
Γ(1) = Γ(2) = 1, Γ′(1) = −γ, Γ′(2) = −γ + 1.
Denote the unique zero in (0,∞) of Γ′(x) by α.
α = 1.4616 · · · , Γ(α) = 0.8856 · · ·.
We call the inverse function of the restriction of Γ(x) to (α,∞) theprincipal inverse function and write Γ−1.Γ−1(x) is an increasing and concave function defined on (Γ(α),∞).
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Introduction
Main Theorem
Theorem 1
The principal inverse Γ−1(x) of Γ(x) has the holomorphic extensionΓ−1(z) to D := C \ (−∞, Γ(α)], which satisfies
(i) Γ−1(Π+) ⊂ Π+ and Γ−1(Π−) ⊂ Π−,
(ii) Γ−1(z) is univalent,
(iii) Γ(Γ−1(z)) = z for z ∈ D.
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kernel function
Definition 2
Let I be an interval in R and K (x , y) a continuous function defined onI × I . Then K (x , y) is said to be a positive semidefinite (p.s.d.) kernelfunction on an interval I × I (on I for short) if∫∫
I×IK (x , y)ϕ(x)ϕ(y)dxdy ≧ 0 (3)
for every complex continuous function ϕ with compact support in I .
• K (x , y) is p.s.d. if and only if for each n and for all n points xi ∈ I ,
n∑i ,j=1
K (xi , xj)zizj ≧ 0
for n complex numbers zi .
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kernel function
Definition 2
Let I be an interval in R and K (x , y) a continuous function defined onI × I . Then K (x , y) is said to be a positive semidefinite (p.s.d.) kernelfunction on an interval I × I (on I for short) if∫∫
I×IK (x , y)ϕ(x)ϕ(y)dxdy ≧ 0 (3)
for every complex continuous function ϕ with compact support in I .
• K (x , y) is p.s.d. if and only if for each n and for all n points xi ∈ I ,
n∑i ,j=1
K (xi , xj)zizj ≧ 0
for n complex numbers zi .
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kernel function
Definition 3
K (x , y) is said to be conditionally (or almost) positive semidefinite(c.p.s.d.) on I × I (on I for short) if (3) holds for every continuousfunction ϕ on I such that the support of ϕ is compact and
∫I ϕ(x)dx = 0.
K (x , y) is said to be conditionally negative semidefinite (c.n.s.d.) on I if−K (x , y) is c.p.s.d.
• K (x , y) is c.p.s.d. if and only if
n∑i ,j=1
K (xi , xj)zizj ≧ 0 (4)
for each n, for all n points xi ∈ I and for n complex numbers zi with∑ni=1 zi = 0.
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kernel function
Definition 3
K (x , y) is said to be conditionally (or almost) positive semidefinite(c.p.s.d.) on I × I (on I for short) if (3) holds for every continuousfunction ϕ on I such that the support of ϕ is compact and
∫I ϕ(x)dx = 0.
K (x , y) is said to be conditionally negative semidefinite (c.n.s.d.) on I if−K (x , y) is c.p.s.d.
• K (x , y) is c.p.s.d. if and only if
n∑i ,j=1
K (xi , xj)zizj ≧ 0 (4)
for each n, for all n points xi ∈ I and for n complex numbers zi with∑ni=1 zi = 0.
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kernel function
Facts
K (x , y) = f (x)f (y) is p.s.d.
If K (x , y) is p.s.d. on [a, b] and h : [c , d ] 7→ [a, b] is increasing and(differentiable), then so is K (h(t), h(s)) on [c , d ].
If Kt(x , y) is p.s.d. for each t, then so is∫Kt(x , y)dµ(t).
(Schur) If K1(x , y) and K2(x , y) are both p.s.d. on I , then so is theproduct K1(x , y)K2(x , y).
If K (x , y) is p.s.d. on I , then K (x , y) is c.p.s.d. on I .
K (x , y) = x + y is not p.s.d. but c. p. s. d. and c. n. s. d. on any I .
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kernel function
Definition 4
Suppose K (x , y) ≧ 0 for every x , y in I . Then K (x , y) is said to be infinitely divisible on I × I (on I for short) if K (x , y)a is positivesemi-definite for every a > 0.
K (x , y) is infinitely divisible if and only if for each n, for all n points xi ∈ Iand for every a > 0matrix
(K (xi , xj)a)
is positive semi-definite.
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kernel function
Definition 4
Suppose K (x , y) ≧ 0 for every x , y in I . Then K (x , y) is said to be infinitely divisible on I × I (on I for short) if K (x , y)a is positivesemi-definite for every a > 0.
K (x , y) is infinitely divisible if and only if for each n, for all n points xi ∈ Iand for every a > 0matrix
(K (xi , xj)a)
is positive semi-definite.
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kernel function
Cauchy kernel1
x + y
is infinitely divisible on (0,∞)× (0,∞).
∵ 1
(x + y)a=
1
Γ(a)
∫ ∞
0e−txe−ty ta−1dt
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kernel function
Cauchy kernel1
x + y
is infinitely divisible on (0,∞)× (0,∞).
∵ 1
(x + y)a=
1
Γ(a)
∫ ∞
0e−txe−ty ta−1dt
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kernel function
Lemma 5
(Fitzgerald, Horn) Let K (x , y) > 0 for x , y ∈ I and suppose −K (x , y) isc.p.s.d. on I × I . Then exp(−K (x , y)) and the reciprocal function 1
K(x ,y)are infinitely divisible there.
Example K (x , y) := x + y on (0,∞)× (0,∞)K (x , y) > 0 and −K (x , y) is c.p.s.d. on (0,∞)× (0,∞).(exp(−K (x , y)))a = e−axe−ay is p.s.d. for every a > 0.
1K(x ,y) =
1x+y is the Cauchy kernel .
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kernel function
Lemma 5
(Fitzgerald, Horn) Let K (x , y) > 0 for x , y ∈ I and suppose −K (x , y) isc.p.s.d. on I × I . Then exp(−K (x , y)) and the reciprocal function 1
K(x ,y)are infinitely divisible there.
Example K (x , y) := x + y on (0,∞)× (0,∞)K (x , y) > 0 and −K (x , y) is c.p.s.d. on (0,∞)× (0,∞).(exp(−K (x , y)))a = e−axe−ay is p.s.d. for every a > 0.
1K(x ,y) =
1x+y is the Cauchy kernel .
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kernel function
The Lowner kernel
Definition 6
Let f (x) be a real C 1-function on I . Then the Lowner kernel function isdefined by
Kf (x , y) =
{f (x)−f (y)
x−y (x = y)
f ′(x) (x = y).
Example
(i) For f (x) = x , Kf (x , y) = 1 is p. s. d. on R2.
(ii) For f (x) = − 1x+λ , Kf (x , y) =
1(x+λ)(y+λ) is p. s. d. on
(−λ,∞)× (−λ,∞) and on (−∞,−λ)× (−∞,−λ).
(iii) For f (x) = x2, Kf (x , y) = x + y is not p. s. d. but c. p. s. d. and c.n. s. d.
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kernel function
The Lowner kernel
Definition 6
Let f (x) be a real C 1-function on I . Then the Lowner kernel function isdefined by
Kf (x , y) =
{f (x)−f (y)
x−y (x = y)
f ′(x) (x = y).
Example
(i) For f (x) = x , Kf (x , y) = 1 is p. s. d. on R2.
(ii) For f (x) = − 1x+λ , Kf (x , y) =
1(x+λ)(y+λ) is p. s. d. on
(−λ,∞)× (−λ,∞) and on (−∞,−λ)× (−∞,−λ).
(iii) For f (x) = x2, Kf (x , y) = x + y is not p. s. d. but c. p. s. d. and c.n. s. d.
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kernel function
(Lowner Theorem) (also Koranyi)
Let f (x) be a real C 1-function on I . Then the Lowner kernel functionKf (x , y) is p.s.d. on I × I if and only if f (x) has a holomorphic extensionf (z) to Π+ which is a Pick (Nevanlinna) function.
We will showKΓ−1(x , y)
is p. s. d. on (Γ(α),∞)× (Γ(α),∞).
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kernel function
(Lowner Theorem) (also Koranyi)
Let f (x) be a real C 1-function on I . Then the Lowner kernel functionKf (x , y) is p.s.d. on I × I if and only if f (x) has a holomorphic extensionf (z) to Π+ which is a Pick (Nevanlinna) function.
We will showKΓ−1(x , y)
is p. s. d. on (Γ(α),∞)× (Γ(α),∞).
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Proof
Lemma 7
(Known result)
Klog x(x , y) :=
{log x−log y
x−y (x = y)1x (x = y)
is p.s.d. on (0,∞)× (0,∞)
Proof. By the formula
log x =∫∞0 ( −1
x+t +t
t2+1)dt (x > 0),
we obtain
Klog x(x , y) =∫∞0
1(x+t)(y+t)dt
for x , y > 0. □
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Proof
Lemma 7
(Known result)
Klog x(x , y) :=
{log x−log y
x−y (x = y)1x (x = y)
is p.s.d. on (0,∞)× (0,∞)
Proof. By the formula
log x =∫∞0 ( −1
x+t +t
t2+1)dt (x > 0),
we obtain
Klog x(x , y) =∫∞0
1(x+t)(y+t)dt
for x , y > 0. □
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Proof
Lemma 7
(Known result)
Klog x(x , y) :=
{log x−log y
x−y (x = y)1x (x = y)
is p.s.d. on (0,∞)× (0,∞)
Proof. By the formula
log x =∫∞0 ( −1
x+t +t
t2+1)dt (x > 0),
we obtain
Klog x(x , y) =∫∞0
1(x+t)(y+t)dt
for x , y > 0. □
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Proof
Lemma 8
Klog Γ(x)(x , y) :=
{log Γ(x)−log Γ(y)
x−y (x = y)Γ′(x)Γ(x) (x = y).
−Klog Γ(x)(x , y) is c.p.s.d. on (0,∞).
Proof.
log Γ(x) = − log x − γx +∑∞
n=1
(xn − log(1 + x
n ))
g(x) :=∑∞
k=1
(xk − log(1 + x
k ))
log Γ(x) = − log x − γx + g(x)−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
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Proof
Lemma 8
Klog Γ(x)(x , y) :=
{log Γ(x)−log Γ(y)
x−y (x = y)Γ′(x)Γ(x) (x = y).
−Klog Γ(x)(x , y) is c.p.s.d. on (0,∞).
Proof.
log Γ(x) = − log x − γx +∑∞
n=1
(xn − log(1 + x
n ))
g(x) :=∑∞
k=1
(xk − log(1 + x
k ))
log Γ(x) = − log x − γx + g(x)−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
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Proof
Lemma 8
Klog Γ(x)(x , y) :=
{log Γ(x)−log Γ(y)
x−y (x = y)Γ′(x)Γ(x) (x = y).
−Klog Γ(x)(x , y) is c.p.s.d. on (0,∞).
Proof.
log Γ(x) = − log x − γx +∑∞
n=1
(xn − log(1 + x
n ))
g(x) :=∑∞
k=1
(xk − log(1 + x
k ))
log Γ(x) = − log x − γx + g(x)−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
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Proof
−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
Klog x(x , y) is p.s.d. and a constant function γ is c.p.s.d.We will see −Kg (x , y) is c.p.s.d.
gn(x) :=∑n
k=1
(xk − log(1 + x
k )).
(i) −Kgn(x , y) is c.p.s.d.
(ii) g ′n(x) =
∑nk=1
xk(k+x) ⇒
∑∞k=1
xk(k+x) = g ′(x) on any finite interval
[0,M].
(iii) Kgn(x , y)− Kg (x , y) =
1
x−y
∫ xy (g ′
n(t)− g ′(t)) dt (x = y)
g ′n(x)− g ′(x) (x = y)
Therefore, −Kg (x , y) is c.p.s.d. on (0,∞). □
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Proof
−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
Klog x(x , y) is p.s.d. and a constant function γ is c.p.s.d.We will see −Kg (x , y) is c.p.s.d.gn(x) :=
∑nk=1
(xk − log(1 + x
k )).
(i) −Kgn(x , y) is c.p.s.d.
(ii) g ′n(x) =
∑nk=1
xk(k+x) ⇒
∑∞k=1
xk(k+x) = g ′(x) on any finite interval
[0,M].
(iii) Kgn(x , y)− Kg (x , y) =
1
x−y
∫ xy (g ′
n(t)− g ′(t)) dt (x = y)
g ′n(x)− g ′(x) (x = y)
Therefore, −Kg (x , y) is c.p.s.d. on (0,∞). □
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Proof
−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
Klog x(x , y) is p.s.d. and a constant function γ is c.p.s.d.We will see −Kg (x , y) is c.p.s.d.gn(x) :=
∑nk=1
(xk − log(1 + x
k )).
(i) −Kgn(x , y) is c.p.s.d.
(ii) g ′n(x) =
∑nk=1
xk(k+x) ⇒
∑∞k=1
xk(k+x) = g ′(x) on any finite interval
[0,M].
(iii) Kgn(x , y)− Kg (x , y) =
1
x−y
∫ xy (g ′
n(t)− g ′(t)) dt (x = y)
g ′n(x)− g ′(x) (x = y)
Therefore, −Kg (x , y) is c.p.s.d. on (0,∞). □
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Proof
−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
Klog x(x , y) is p.s.d. and a constant function γ is c.p.s.d.We will see −Kg (x , y) is c.p.s.d.gn(x) :=
∑nk=1
(xk − log(1 + x
k )).
(i) −Kgn(x , y) is c.p.s.d.
(ii) g ′n(x) =
∑nk=1
xk(k+x) ⇒
∑∞k=1
xk(k+x) = g ′(x) on any finite interval
[0,M].
(iii) Kgn(x , y)− Kg (x , y) =
1
x−y
∫ xy (g ′
n(t)− g ′(t)) dt (x = y)
g ′n(x)− g ′(x) (x = y)
Therefore, −Kg (x , y) is c.p.s.d. on (0,∞). □
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Proof
−Klog Γ(x)(x , y) = Klog x(x , y) + γ − Kg (x , y).
Klog x(x , y) is p.s.d. and a constant function γ is c.p.s.d.We will see −Kg (x , y) is c.p.s.d.gn(x) :=
∑nk=1
(xk − log(1 + x
k )).
(i) −Kgn(x , y) is c.p.s.d.
(ii) g ′n(x) =
∑nk=1
xk(k+x) ⇒
∑∞k=1
xk(k+x) = g ′(x) on any finite interval
[0,M].
(iii) Kgn(x , y)− Kg (x , y) =
1
x−y
∫ xy (g ′
n(t)− g ′(t)) dt (x = y)
g ′n(x)− g ′(x) (x = y)
Therefore, −Kg (x , y) is c.p.s.d. on (0,∞). □
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Proof
Lemma 9
1
Klog Γ(x)(x , y)
is infinitely divisible on (α,∞).
Proof
By the previous lemmaKlog Γ(x)(x , y) > 0
is c.n.s.d. on (α,∞). By Fitzgerald and Horn’s result, we get the requiredresult.
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Proof
Lemma 9
1
Klog Γ(x)(x , y)
is infinitely divisible on (α,∞).
Proof
By the previous lemmaKlog Γ(x)(x , y) > 0
is c.n.s.d. on (α,∞). By Fitzgerald and Horn’s result, we get the requiredresult.
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Proof
Lemma 10
Let K1(x , y) be the kernel function defined on (α,∞)× (α,∞) by
K1(x , y) =
{x−y
Γ(x)−Γ(y) (x = y)1
Γ′(x) (x = y).
Then K1(x , y) is p.s.d. on (α,∞).
Proof.
K1(x , y) =
{log Γ(x)−log Γ(y)
Γ(x)−Γ(y)x−y
log Γ(x)−log Γ(y) (x = y)1
Γ(x)Γ(x)Γ′(x) (x = y)
= Klog x(Γ(x), Γ(y)) ·1
Klog Γ(x)(x , y)□
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Proof
Lemma 10
Let K1(x , y) be the kernel function defined on (α,∞)× (α,∞) by
K1(x , y) =
{x−y
Γ(x)−Γ(y) (x = y)1
Γ′(x) (x = y).
Then K1(x , y) is p.s.d. on (α,∞).
Proof.
K1(x , y) =
{log Γ(x)−log Γ(y)
Γ(x)−Γ(y)x−y
log Γ(x)−log Γ(y) (x = y)1
Γ(x)Γ(x)Γ′(x) (x = y)
= Klog x(Γ(x), Γ(y)) ·1
Klog Γ(x)(x , y)□
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Proof
Proof of Theorem
We have shown
K1(x , y) =
{x−y
Γ(x)−Γ(y) (x = y)1
Γ′(x) (x = y).
is p.s.d. on (α,∞). Hence
KΓ−1(x , y) =
{Γ−1(x)−Γ−1(y)
x−y (x = y)
(Γ−1)′(x) (x = y)= K1(Γ
−1(x), Γ−1(y))
is p.s.d. on (Γ(α),∞)× (Γ(α),∞).Thus by the Lowner theorem, Γ−1(x) has the holomorphic extensionΓ−1(z) onto Π+, which is a Pick function.By reflection Γ−1(x) has also holomorphic extension to Π− and the rangeis in it.
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Proof
Γ(Γ−1(z)) is thus holomorphic on the simply connected domainD := C \ (−∞, Γ(α)], and Γ(Γ−1(x)) = x for Γ(α) < x < ∞. By theunicity theorem, Γ
(Γ−1(z)
)= z for z ∈ D. It is clear that Γ−1(z) is
univalent. □
Corollary 11
There is a Borel measure µ so that
Γ−1(x) = a+ bx +
∫ Γ(α)
−∞(
1
t − x− t
t2 + 1)dµ(t), (5)
where∫ Γ(α)−∞
1t2+1
dµ(t) < ∞, and a, b are real numbers and b ≧ 0.
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Proof
Γ(Γ−1(z)) is thus holomorphic on the simply connected domainD := C \ (−∞, Γ(α)], and Γ(Γ−1(x)) = x for Γ(α) < x < ∞. By theunicity theorem, Γ
(Γ−1(z)
)= z for z ∈ D. It is clear that Γ−1(z) is
univalent. □Corollary 11
There is a Borel measure µ so that
Γ−1(x) = a+ bx +
∫ Γ(α)
−∞(
1
t − x− t
t2 + 1)dµ(t), (5)
where∫ Γ(α)−∞
1t2+1
dµ(t) < ∞, and a, b are real numbers and b ≧ 0.
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Application
Matrix inequality
Theorem 12
The principal inverse Γ−1(x) of Γ(x) is operator monotone on[Γ(α),∞); i.e.,and hence for bounded self-adjoint operators A,B whose spectra are in[Γ(α),∞)
A ≦ B ⇒ Γ−1(A) ≦ Γ−1(B).
Proof A ≦ B implies that −(A− tI )−1 ≦ −(B − tI )−1 for t < Γ(α). From
Γ−1(x) = a+ bx +∫ Γ(α)−∞ ( −1
x−t −t
t2+1)dµ(t)
we have Γ−1(A) ≦ Γ−1(B). □
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Application
Matrix inequality
Theorem 12
The principal inverse Γ−1(x) of Γ(x) is operator monotone on[Γ(α),∞); i.e.,and hence for bounded self-adjoint operators A,B whose spectra are in[Γ(α),∞)
A ≦ B ⇒ Γ−1(A) ≦ Γ−1(B).
Proof A ≦ B implies that −(A− tI )−1 ≦ −(B − tI )−1 for t < Γ(α). From
Γ−1(x) = a+ bx +∫ Γ(α)−∞ ( −1
x−t −t
t2+1)dµ(t)
we have Γ−1(A) ≦ Γ−1(B). □
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Application
K2(x , y) := Klog Γ(x)(x , y) =
{log Γ(x)−log Γ(y)
x−y (x = y)Γ′(x)Γ(x) (x = y).
Then
e−K2(x ,y) =
(Γ(y)Γ(x))1
x−y (x = y)
e− Γ′(x)
Γ(x) (x = y)
is infinitely divisible. Since Γ(x + 1) = xΓ(x),
Γ′(1)
Γ(1)= −γ,
Γ′(m + 1)
Γ(m + 1)=
Γ′(m)
Γ(m)+
1
m,Γ(n)
Γ(m)=
(n − 1)!
(m − 1)!.
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Application
matrix
The following (n+ 1)× (n+ 1) matrix is therefore not only p.s.d. but alsoinfinitely divisible. (
e−K2(i ,j))=
=
eγ (1!1!)−1 (2!)−
12 (3!)−
13 · · · (n!)−
1n
(1!1!)−1 eγ−1 (2!1!)
−1 (3!1!)− 1
2 · · · (n!1! )− 1
n−1
(2!)−12 (2!1!)
−1 eγ−1− 12 (3!2!)
−1 · · · (n!2! )− 1
n−2
(3!)−13 (3!1!)
− 12 (3!2!)
−1 eγ−1− 12− 1
3 · · · (n!3! )− 1
n−3
......
......
. . ....
(n!)−1n (n!1! )
− 1n−1 (n!2! )
− 1n−2 (n!3! )
− 1n−3 · · · eγ−1− 1
2−···− 1
n
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Application
R. Bhatia, Infinitely divisible matrices, Amer. Math. Monthly, 113, 221–235(2006).
R. Bahtia and H. Kosaki, Mean matrices and infinite divisibility, Linear Algebra Appl., 424,
36–54(2007).
C. Berg, H. L. Pedersen, Pick functions related to the gamma function, Rocky Mountain J. of Math.
32(2002)507–525.
A, Koranyi, On a theorem of Lowner and its connections with resolvents of selfadjoint
transformations, Acta Sci. Math. 17, 63–70(1956).
K. Lowner, Uber monotone Matrixfunctionen, Math. Z. 38(1934)177–216.
W. F. Donoghue, Monotone Matrix Functions and Analytic Continuation, Springer-Verlag, 1974.
C. H. Fitzgerald, On analytic continuation to a Schlicht function, Proc. Amer. Math. Soc., 18,
788–792(1967).
R. A. Horn, Schlicht mapping and infinitely divisible kernels, Pacific J. of Math. 38, 423–430(1971).
R. A. Horn and C. R. Johnson, Topics in Matrix Analysis, Cambridge University Press, 1991.
M. Uchiyama, Operator monotone functions, positive definite kernels and majorization, Proc. Amer.
Math. 138(2010)3985–3996
M. Uchiyama, The principal inverse of the gamma function, PAMS (2012) 1343–1348.
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