Notations with Almost everywhere

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In summary, this symbol stands for the product measure and it is used in the definition of a strong solution of the semilinear SDE. The measure used is the product measure $Leb\otimes\mathbb{P}.$.
  • #1
gnob
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Good day! I came across this symbol $dt \otimes dP$-a.e. in the book of Mandrekar (page 72) Stochastic Differential Equations in Infinite Dimensions: With Applications ... - Leszek Gawarecki, Vidyadhar Mandrekar - Google Books.

What does this symbol mean? I understand that in real analysis, given a measure space $(X,\mathcal{A},\mu)$ we say that a property holds $\mu$-a.e. if there is a set $N$ such that $\mu(N)=0$ and the property holds for all $x\in (X\smallsetminus N).$

I am a newbie with the symbols $dt\otimes dP$ since $dt$ and $dP$ aren't measures?
Also, can you suggest a book with detailed explanation on such notation?

Thanks a lot.
 
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  • #2
I have not been able to see page 72 in google books. I am pretty sure that those symbols stand for the product measure though, and that by $dt$ they mean the Lebesgue measure.

You should be able to find a section on the product measure in most Real Analysis books (almost everywhere :D).
 
  • #3
PaulRS said:
I have not been able to see page 72 in google books. I am pretty sure that those symbols stand for the product measure though, and that by $dt$ they mean the Lebesgue measure.

You should be able to find a section on the product measure in most Real Analysis books (almost everywhere :D).

I see. Below is taken from page 72 of the book. It is part of the definition of a strong solution of the semilinear SDE. This is the setting:

Let $K$ and $H$ be real separable Hilbert spaces, and $W_t$ be a $K$-valued $Q$-Wiener process on a complete filtered probability space $\Big(\Omega,\mathcal{F},\{ \mathcal{F}_t\}_{t\leq T},\mathbb{P}\Big)$ with the filtration $\mathcal{F}_t$ satisfying the usual conditions. We consider the semilinear SDEs on $[0,T]$ in $H$ in the general form
\begin{align*}
dX(t) &= (AX(t) +F(t,X))dt + B(t,X)dW_t\\
X(0) &= \xi_0.
\end{align*}
Here, $A: \mathcal{D}(A) \subset H \to H$ is the generator of a $C_0$-semigroup of operators $\{ S_t, t\geq 0\}$ on $H.$ The coefficients $F$ and $B$ are, in general, nonlinear mappings,
\begin{align*}
F&:\Omega\times [0,T] \times C\big([0,T],H\big) \to H\\
B&:\Omega\times [0,T] \times C\big([0,T],H\big) \to \mathcal{L}_{2}(K_Q,H).
\end{align*}
Finally, the initial condition $\xi_0$ is an $\mathcal{F}_0$-measurable $H$-valued random variable.

In the definition of a strong solution of the above SSDE, one requirement is the ff:

$X(t,\omega)\in\mathcal{D}(A)$ $dt\otimes d\mathbb{P}$-a.e.

Does this mean that $X(t,\omega)$ belongs to $\mathcal{D}(A)$, except for a set of measure zero? Which measure will we use? The product measure $Leb\otimes\mathbb{P}.$
Thanks again for further enlightenment.
 

FAQ: Notations with Almost everywhere

What does "almost everywhere" mean in mathematical notations?

"Almost everywhere" in mathematical notations refers to a set of values or points where a property or statement holds true except for a set of measure zero. This means that the property or statement is true for almost all values or points, with a few exceptions.

How is "almost everywhere" different from "almost surely"?

"Almost everywhere" and "almost surely" are similar concepts, but they differ in terms of measure. "Almost everywhere" refers to a set of measure zero, while "almost surely" refers to a set of measure 1. This means that while both involve exceptions, "almost surely" has a stronger guarantee that the property or statement holds true for almost all values or points.

Can "almost everywhere" be used interchangeably with "almost surely"?

No, "almost everywhere" and "almost surely" cannot be used interchangeably. While they both involve exceptions and refer to a set of measure zero or 1, they have different implications and cannot be substituted for one another in mathematical notations.

How is "almost everywhere" used in probability theory?

In probability theory, "almost everywhere" is used to describe events or outcomes that are guaranteed to occur except for a set of measure zero. This means that the event or outcome is almost certain to occur, with a few exceptions.

Are there any real-life applications of "almost everywhere" in mathematics?

Yes, "almost everywhere" has real-life applications in various fields of mathematics, including measure theory, probability theory, and analysis. It is used to describe the behavior of functions, measure the properties of sets, and make statements about the convergence of sequences.

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