MHB Notations with Almost everywhere

  • Thread starter Thread starter gnob
  • Start date Start date
gnob
Messages
11
Reaction score
0
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.
 
Physics news on Phys.org
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).
 
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.
 
Hi all, I've been a roulette player for more than 10 years (although I took time off here and there) and it's only now that I'm trying to understand the physics of the game. Basically my strategy in roulette is to divide the wheel roughly into two halves (let's call them A and B). My theory is that in roulette there will invariably be variance. In other words, if A comes up 5 times in a row, B will be due to come up soon. However I have been proven wrong many times, and I have seen some...
Namaste & G'day Postulate: A strongly-knit team wins on average over a less knit one Fundamentals: - Two teams face off with 4 players each - A polo team consists of players that each have assigned to them a measure of their ability (called a "Handicap" - 10 is highest, -2 lowest) I attempted to measure close-knitness of a team in terms of standard deviation (SD) of handicaps of the players. Failure: It turns out that, more often than, a team with a higher SD wins. In my language, that...

Similar threads

Replies
9
Views
2K
Replies
7
Views
3K
Replies
33
Views
5K
Replies
42
Views
10K
Replies
46
Views
8K
Back
Top