Ergodic flows are a term from the theory of dynamic systems . Clearly, ergodicity of a river means that almost all points belong to a single flow line.
definition
Let be a probability measure on a probability space and
a flow that receives the measure , i.e. H. for all and all measurable quantities applies , wherein .
μ
{\ displaystyle \ mu}
Ω
{\ displaystyle \ Omega}
ϕ
:
Ω
×
R.
→
Ω
{\ displaystyle \ phi \ colon \ Omega \ times \ mathbb {R} \ to \ Omega}
μ
{\ displaystyle \ mu}
t
∈
R.
{\ displaystyle t \ in \ mathbb {R}}
A.
⊂
Ω
{\ displaystyle A \ subset \ Omega}
μ
(
ϕ
t
(
A.
)
)
=
μ
(
A.
)
{\ displaystyle \ mu (\ phi _ {t} (A)) = \ mu (A)}
ϕ
t
(
A.
)
=
{
ϕ
(
x
,
t
)
:
x
∈
A.
}
{\ displaystyle \ phi _ {t} (A) = \ left \ {\ phi (x, t) \ colon x \ in A \ right \}}
Then an ergodic flow is called if for every -invariant set :
ϕ
{\ displaystyle \ phi}
ϕ
{\ displaystyle \ phi}
A.
⊂
Ω
{\ displaystyle A \ subset \ Omega}
μ
(
A.
)
=
0
{\ displaystyle \ mu (A) = 0}
or .
μ
(
A.
)
=
1
{\ displaystyle \ mu (A) = 1}
(A set is called -invariant if it holds for all .)
A.
{\ displaystyle A}
ϕ
{\ displaystyle \ phi}
ϕ
t
(
A.
)
=
A.
{\ displaystyle \ phi _ {t} (A) = A}
t
∈
R.
{\ displaystyle t \ in \ mathbb {R}}
An equivalent definition says that it is ergodic if and only if the only -invariant functions are the constant functions . (A function is called -invariant if the equation holds for all for- almost all .)
ϕ
{\ displaystyle \ phi}
ϕ
{\ displaystyle \ phi}
f
∈
L.
1
(
Ω
,
μ
)
{\ displaystyle f \ in L ^ {1} (\ Omega, \ mu)}
ϕ
{\ displaystyle \ phi}
t
∈
R.
{\ displaystyle t \ in \ mathbb {R}}
μ
{\ displaystyle \ mu}
x
∈
Ω
{\ displaystyle x \ in \ Omega}
f
(
ϕ
(
x
,
t
)
)
=
f
(
x
)
{\ displaystyle f (\ phi (x, t)) = f (x)}
properties
{
ϕ
(
x
,
t
)
,
t
∈
R.
}
{\ displaystyle \ left \ {\ phi (x, t), t \ in \ mathbb {R} \ right \}}
are (with ) -invariant, in particular exactly one orbit must have dimension 1 and all other orbits must have dimension 0. In particular, an ergodic flow defines an ergodic action of the group of real numbers .
x
∈
Ω
{\ displaystyle x \ in \ Omega}
ϕ
{\ displaystyle \ phi}
R.
{\ displaystyle \ mathbb {R}}
lim
T
→
∞
1
T
∫
0
T
f
(
ϕ
(
x
,
t
)
)
d
t
=
∫
Ω
f
d
μ
{\ displaystyle \ lim _ {T \ to \ infty} {\ frac {1} {T}} \ int _ {0} ^ {T} f (\ phi (x, t)) dt = \ int _ {\ Omega} fd \ mu}
for almost everyone and every function .
μ
{\ displaystyle \ mu}
x
∈
Ω
{\ displaystyle x \ in \ Omega}
f
∈
L.
1
(
Ω
,
μ
)
{\ displaystyle f \ in L ^ {1} (\ Omega, \ mu)}
Examples
literature
A. Katok and B. Hasselblatt: Introduction to the Modern Theory of Dynamical Systems. Cambridge University Press, Cambridge, 1995, ISBN 0-521-34187-6 .
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