The Blumenthal 0-1 Law , named after RM Blumenthal, is a mathematical theorem in the field of probability theory . Like all zero-one laws , it describes a class of events whose probabilities are always 0 or 1.
statement
Let be a probability space and a defined Brownian motion with filtration . Then the σ-algebra defined by , is -trivial , i.e. H. it applies: for everyone .
(
Ω
,
A.
,
P
)
{\ displaystyle (\ Omega, {\ mathcal {A}}, \ mathbb {P})}
(
B.
t
)
t
≥
0
{\ displaystyle (B_ {t}) _ {t \ geq 0}}
F.
t
=
σ
(
{
B.
s
∣
s
≤
t
}
)
{\ displaystyle {\ mathcal {F}} _ {t} = \ sigma (\ {B_ {s} \ mid s \ leq t \})}
F.
0
+
{\ displaystyle {\ mathcal {F}} _ {0} ^ {+}}
F.
0
+
=
⋂
t
>
0
F.
t
{\ displaystyle \ textstyle {\ mathcal {F}} _ {0} ^ {+} = \ bigcap _ {t> 0} {\ mathcal {F}} _ {t}}
P
{\ displaystyle \ mathbb {P}}
P
(
A.
)
∈
{
0
,
1
}
{\ displaystyle \ mathbb {P} (A) \ in \ {0,1 \}}
A.
∈
F.
0
+
{\ displaystyle A \ in {\ mathcal {F}} _ {0} ^ {+}}
Descriptive includes exactly those events that only depend on , for anything small . For example, the event is , so it applies .
F.
0
+
{\ displaystyle {\ mathcal {F}} _ {0} ^ {+}}
(
B.
t
)
0
≤
t
≤
ε
{\ displaystyle (B_ {t}) _ {0 \ leq t \ leq \ varepsilon}}
ε
{\ displaystyle \ varepsilon}
A.
=
{
∀
ε
>
0
∃
t
>
0
:
t
<
ε
∧
B.
t
=
0
}
∈
F.
0
+
{\ displaystyle A = \ {\ forall \ varepsilon> 0 \ exists t> 0: \; t <\ varepsilon \ wedge B_ {t} = 0 \} \ in {\ mathcal {F}} _ {0} ^ { +}}
P
(
A.
)
∈
{
0
,
1
}
{\ displaystyle \ mathbb {P} (A) \ in \ {0,1 \}}
literature
Blumenthal, RM: An extended Markov property. In: Transactions of the American Mathematical Society. Volume 85, 1957, pp. 52-72.
Klenke, Achim: Probability Theory , Springer-Verlag Berlin Heidelberg 2008, ISBN 978-3-540-76317-8
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