Three-dimensional plot showing the values of the logarithmic mean. In mathematics , the logarithmic mean is a function of two non-negative numbers which is equal to their difference divided by the logarithm of their quotient .
This calculation is applicable in engineering problems involving heat and mass transfer .
Definition
The logarithmic mean is defined as:
M
lm
(
x
,
y
)
=
lim
(
ξ
,
η
)
→
(
x
,
y
)
η
−
ξ
ln
(
η
)
−
ln
(
ξ
)
=
{
x
if
x
=
y
,
y
−
x
ln
(
y
)
−
ln
(
x
)
otherwise,
{\displaystyle {\begin{aligned}M_{\text{lm}}(x,y)&=\lim _{(\xi ,\eta )\to (x,y)}{\frac {\eta -\xi }{\ln(\eta )-\ln(\xi )}}\\[6pt]&={\begin{cases}x&{\text{if }}x=y,\\{\frac {y-x}{\ln(y)-\ln(x)}}&{\text{otherwise,}}\end{cases}}\end{aligned}}}
for the positive numbers
x
,
y
{\displaystyle x,y}
Inequalities
The logarithmic mean of two numbers is smaller than the arithmetic mean and the generalized mean with exponent one third but larger than the geometric mean , unless the numbers are the same, in which case all three means are equal to the numbers.
x
y
≤
M
lm
(
x
,
y
)
≤
(
x
1
/
3
+
y
1
/
3
2
)
3
≤
x
+
y
2
for all
x
>
0
and
y
>
0.
{\displaystyle {\sqrt {xy}}\leq M_{\text{lm}}(x,y)\leq \left({\frac {x^{1/3}+y^{1/3}}{2}}\right)^{3}\leq {\frac {x+y}{2}}\qquad {\text{ for all }}x>0{\text{ and }}y>0.}
[ 1] [ 2] [ 3]
Derivation
Mean value theorem of differential calculus
From the mean value theorem , there exists a value
ξ
{\displaystyle \xi }
interval between x and y where the derivative
f
′
{\displaystyle f'}
secant line :
∃
ξ
∈
(
x
,
y
)
:
f
′
(
ξ
)
=
f
(
x
)
−
f
(
y
)
x
−
y
{\displaystyle \exists \xi \in (x,y):\ f'(\xi )={\frac {f(x)-f(y)}{x-y}}}
The logarithmic mean is obtained as the value of
ξ
{\displaystyle \xi }
ln
{\displaystyle \ln }
f
{\displaystyle f}
derivative :
1
ξ
=
ln
(
x
)
−
ln
(
y
)
x
−
y
{\displaystyle {\frac {1}{\xi }}={\frac {\ln(x)-\ln(y)}{x-y}}}
and solving for
ξ
{\displaystyle \xi }
ξ
=
x
−
y
ln
(
x
)
−
ln
(
y
)
{\displaystyle \xi ={\frac {x-y}{\ln(x)-\ln(y)}}}
Integration
The logarithmic mean can also be interpreted as the area under an exponential curve .
L
(
x
,
y
)
=
∫
0
1
x
1
−
t
y
t
d
t
=
∫
0
1
(
y
x
)
t
x
d
t
=
x
∫
0
1
(
y
x
)
t
d
t
=
x
ln
(
y
x
)
(
y
x
)
t
|
t
=
0
1
=
x
ln
(
y
x
)
(
y
x
−
1
)
=
y
−
x
ln
(
y
x
)
=
y
−
x
ln
(
y
)
−
ln
(
x
)
{\displaystyle {\begin{aligned}L(x,y)={}&\int _{0}^{1}x^{1-t}y^{t}\ \mathrm {d} t={}\int _{0}^{1}\left({\frac {y}{x}}\right)^{t}x\ \mathrm {d} t={}x\int _{0}^{1}\left({\frac {y}{x}}\right)^{t}\mathrm {d} t\\[3pt]={}&\left.{\frac {x}{\ln \left({\frac {y}{x}}\right)}}\left({\frac {y}{x}}\right)^{t}\right|_{t=0}^{1}={}{\frac {x}{\ln \left({\frac {y}{x}}\right)}}\left({\frac {y}{x}}-1\right)={}{\frac {y-x}{\ln \left({\frac {y}{x}}\right)}}\\[3pt]={}&{\frac {y-x}{\ln \left(y\right)-\ln \left(x\right)}}\end{aligned}}}
The area interpretation allows the easy derivation of some basic properties of the logarithmic mean. Since the exponential function is monotonic , the integral over an interval of length 1 is bounded by
x
{\displaystyle x}
y
{\displaystyle y}
homogeneity of the integral operator is transferred to the mean operator, that is
L
(
c
x
,
c
y
)
=
c
L
(
x
,
y
)
{\displaystyle L(cx,cy)=cL(x,y)}
Two other useful integral representations are
1
L
(
x
,
y
)
=
∫
0
1
d
t
t
x
+
(
1
−
t
)
y
{\displaystyle {1 \over L(x,y)}=\int _{0}^{1}{\operatorname {d} \!t \over tx+(1-t)y}}
1
L
(
x
,
y
)
=
∫
0
∞
d
t
(
t
+
x
)
(
t
+
y
)
.
{\displaystyle {1 \over L(x,y)}=\int _{0}^{\infty }{\operatorname {d} \!t \over (t+x)\,(t+y)}.}
Generalization
Mean value theorem of differential calculus
One can generalize the mean to
n
+
1
{\displaystyle n+1}
mean value theorem for divided differences for the
n
{\displaystyle n}
derivative of the logarithm.
We obtain
L
MV
(
x
0
,
…
,
x
n
)
=
(
−
1
)
(
n
+
1
)
n
ln
(
[
x
0
,
…
,
x
n
]
)
−
n
{\displaystyle L_{\text{MV}}(x_{0},\,\dots ,\,x_{n})={\sqrt[{-n}]{(-1)^{(n+1)}n\ln \left(\left[x_{0},\,\dots ,\,x_{n}\right]\right)}}}
where
ln
(
[
x
0
,
…
,
x
n
]
)
{\displaystyle \ln \left(\left[x_{0},\,\dots ,\,x_{n}\right]\right)}
divided difference of the logarithm.
For
n
=
2
{\displaystyle n=2}
L
MV
(
x
,
y
,
z
)
=
(
x
−
y
)
(
y
−
z
)
(
z
−
x
)
2
(
(
y
−
z
)
ln
(
x
)
+
(
z
−
x
)
ln
(
y
)
+
(
x
−
y
)
ln
(
z
)
)
{\displaystyle L_{\text{MV}}(x,y,z)={\sqrt {\frac {(x-y)\left(y-z\right)\left(z-x\right)}{2\left(\left(y-z\right)\ln \left(x\right)+\left(z-x\right)\ln \left(y\right)+\left(x-y\right)\ln \left(z\right)\right)}}}}
Integral
The integral interpretation can also be generalized to more variables, but it leads to a different result. Given the simplex
S
{\textstyle S}
S
=
{
(
α
0
,
…
,
α
n
)
:
(
α
0
+
⋯
+
α
n
=
1
)
∧
(
α
0
≥
0
)
∧
⋯
∧
(
α
n
≥
0
)
}
{\textstyle S=\{\left(\alpha _{0},\,\dots ,\,\alpha _{n}\right):\left(\alpha _{0}+\dots +\alpha _{n}=1\right)\land \left(\alpha _{0}\geq 0\right)\land \dots \land \left(\alpha _{n}\geq 0\right)\}}
d
α
{\textstyle \mathrm {d} \alpha }
L
I
(
x
0
,
…
,
x
n
)
=
∫
S
x
0
α
0
⋅
⋯
⋅
x
n
α
n
d
α
{\displaystyle L_{\text{I}}\left(x_{0},\,\dots ,\,x_{n}\right)=\int _{S}x_{0}^{\alpha _{0}}\cdot \,\cdots \,\cdot x_{n}^{\alpha _{n}}\ \mathrm {d} \alpha }
This can be simplified using divided differences of the exponential function to
L
I
(
x
0
,
…
,
x
n
)
=
n
!
exp
[
ln
(
x
0
)
,
…
,
ln
(
x
n
)
]
{\displaystyle L_{\text{I}}\left(x_{0},\,\dots ,\,x_{n}\right)=n!\exp \left[\ln \left(x_{0}\right),\,\dots ,\,\ln \left(x_{n}\right)\right]}
Example
n
=
2
{\textstyle n=2}
L
I
(
x
,
y
,
z
)
=
−
2
x
(
ln
(
y
)
−
ln
(
z
)
)
+
y
(
ln
(
z
)
−
ln
(
x
)
)
+
z
(
ln
(
x
)
−
ln
(
y
)
)
(
ln
(
x
)
−
ln
(
y
)
)
(
ln
(
y
)
−
ln
(
z
)
)
(
ln
(
z
)
−
ln
(
x
)
)
{\displaystyle L_{\text{I}}(x,y,z)=-2{\frac {x\left(\ln \left(y\right)-\ln \left(z\right)\right)+y\left(\ln \left(z\right)-\ln \left(x\right)\right)+z\left(\ln \left(x\right)-\ln \left(y\right)\right)}{\left(\ln \left(x\right)-\ln \left(y\right)\right)\left(\ln \left(y\right)-\ln \left(z\right)\right)\left(\ln \left(z\right)-\ln \left(x\right)\right)}}}
Connection to other means
Arithmetic mean :
L
(
x
2
,
y
2
)
L
(
x
,
y
)
=
x
+
y
2
{\displaystyle {\frac {L\left(x^{2},y^{2}\right)}{L(x,y)}}={\frac {x+y}{2}}}
Geometric mean :
L
(
x
,
y
)
L
(
1
x
,
1
y
)
=
x
y
{\displaystyle {\sqrt {\frac {L\left(x,y\right)}{L\left({\frac {1}{x}},{\frac {1}{y}}\right)}}}={\sqrt {xy}}}
Harmonic mean :
L
(
1
x
,
1
y
)
L
(
1
x
2
,
1
y
2
)
=
2
1
x
+
1
y
{\displaystyle {\frac {L\left({\frac {1}{x}},{\frac {1}{y}}\right)}{L\left({\frac {1}{x^{2}}},{\frac {1}{y^{2}}}\right)}}={\frac {2}{{\frac {1}{x}}+{\frac {1}{y}}}}}
See also
References
Citations Bibliography 
![{\displaystyle {\begin{aligned}M_{\text{lm}}(x,y)&=\lim _{(\xi ,\eta )\to (x,y)}{\frac {\eta -\xi }{\ln(\eta )-\ln(\xi )}}\\[6pt]&={\begin{cases}x&{\text{if }}x=y,\\{\frac {y-x}{\ln(y)-\ln(x)}}&{\text{otherwise,}}\end{cases}}\end{aligned}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/d0b45ba94901cfc8fc47565d4b9212ab83ff1e02)
![{\displaystyle {\begin{aligned}L(x,y)={}&\int _{0}^{1}x^{1-t}y^{t}\ \mathrm {d} t={}\int _{0}^{1}\left({\frac {y}{x}}\right)^{t}x\ \mathrm {d} t={}x\int _{0}^{1}\left({\frac {y}{x}}\right)^{t}\mathrm {d} t\\[3pt]={}&\left.{\frac {x}{\ln \left({\frac {y}{x}}\right)}}\left({\frac {y}{x}}\right)^{t}\right|_{t=0}^{1}={}{\frac {x}{\ln \left({\frac {y}{x}}\right)}}\left({\frac {y}{x}}-1\right)={}{\frac {y-x}{\ln \left({\frac {y}{x}}\right)}}\\[3pt]={}&{\frac {y-x}{\ln \left(y\right)-\ln \left(x\right)}}\end{aligned}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/834a3d1b2267cb6d782f1542ced8616b209e17c0)
![{\displaystyle L_{\text{MV}}(x_{0},\,\dots ,\,x_{n})={\sqrt[{-n}]{(-1)^{(n+1)}n\ln \left(\left[x_{0},\,\dots ,\,x_{n}\right]\right)}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/a3f768d4332d13acc1ed2bef32032c7fd92c84bc)
![{\displaystyle \ln \left(\left[x_{0},\,\dots ,\,x_{n}\right]\right)}](https://wikimedia.org/api/rest_v1/media/math/render/svg/7456e6367275d5f13829e0150ea009b5b093bb38)
![{\displaystyle L_{\text{I}}\left(x_{0},\,\dots ,\,x_{n}\right)=n!\exp \left[\ln \left(x_{0}\right),\,\dots ,\,\ln \left(x_{n}\right)\right]}](https://wikimedia.org/api/rest_v1/media/math/render/svg/a0beb3a5bfda4ba6e6185d83ddf13c718d7a590c)
