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I just want to double-check the domains for multiplicative constants.
Consider the stochastic process $d x_t = \tilde{\sigma}(x_t) d W_t$. For simplicity, assume it is reflected at 0 and 2.
We know that the infinitesimal generator is $\tilde{L} = \tilde{\sigma}(x)^2/2 \partial_{xx}$.
The question I have is to make sure we are precisely is how compose the multiplicative $\tilde{\sigma}(x)^2/2$ term... especially if $\tilde{\sigma}(x)$ is not defined below 0. Lets say that we let $\Delta x = 1$ so that the interior is $x \equiv$[0, 1, 2] and the extension is $\bar{x} \equiv$[-1, 0, 1, 2, 3].
In all cases, the discretized boundary operator is
B =
1 -1 0 0 0
0 0 0 -1 1
and we also know that
Q =
1 0 0
1 0 0
0 1 0
0 0 1
0 0 1
First the easy case. is if $\tilde{\sigma}(x) = \sqrt{2}$, then we know that the discretization in central differences of the $\partial_{xx}$ operator is
L_2 =
1 -2 1 0 0
0 1 -2 1 0
0 0 1 -2 1
and then $L = L_2$ and there is an appropriate $L Q$ for the composed operator which we can apply to $u \in R^3$.
Next, let $\tilde{\sigma}(x) = \sqrt{2}(1+x)$ and $\sigma(x)$ is undefined for $x$ outside of the $[0,2]$ domain. Then just to make sure we are thinking this through correctly... define the vector of this applied to the domain (and not the extended domain, since it is meaningless) as
$$
\sigma =\sqrt{2} \begin{bmatrix} 1\ 2\ 3 \end{bmatrix}
$$
Then put this into a diagonal matrix,
$$
C_1 = diag(\sigma.^2/2) \in R^{3\times 3}
$$
Finally, to compose this, we have
$$
L = C L_2
$$
Do I have that correct? Does this generalize, that if the domain is of size $M$ and the extended domain is of size $\bar{M}$ that all multiplicative constants are diagonal and of size $M \times M$?
Finally, is there any case in the composition of operators where you do would not want this as a diagonal, and what is the interpretation if you don't? This may be helpful to figure out before we make it lazy
The text was updated successfully, but these errors were encountered:
Finally, is there any case in the composition of operators where you do would not want this as a diagonal, and what is the interpretation if you don't?
This can happen in spectral discretizations since the basis isn't local but global.
But this is one of the reasons that a pre-restriction seems to be the easier way to go. This can actually be easily achieved with a view. We will want the result of Q to be a special type anyways so that way we are just allocating two Refs on the ends, in which case it will have the information for the view.
I just want to double-check the domains for multiplicative constants.
Consider the stochastic process$d x_t = \tilde{\sigma}(x_t) d W_t$ . For simplicity, assume it is reflected at 0 and 2.
We know that the infinitesimal generator is$\tilde{L} = \tilde{\sigma}(x)^2/2 \partial_{xx}$ .
The question I have is to make sure we are precisely is how compose the multiplicative$\tilde{\sigma}(x)^2/2$ term... especially if $\tilde{\sigma}(x)$ is not defined below 0. Lets say that we let $\Delta x = 1$ so that the interior is $x \equiv$ $\bar{x} \equiv$
[0, 1, 2]
and the extension is[-1, 0, 1, 2, 3]
.In all cases, the discretized boundary operator is
and we also know that
First the easy case. is if$\tilde{\sigma}(x) = \sqrt{2}$ , then we know that the discretization in central differences of the $\partial_{xx}$ operator is
and then$L = L_2$ and there is an appropriate $L Q$ for the composed operator which we can apply to $u \in R^3$ .
Next, let$\tilde{\sigma}(x) = \sqrt{2}(1+x)$ and $\sigma(x)$ is undefined for $x$ outside of the $[0,2]$ domain. Then just to make sure we are thinking this through correctly... define the vector of this applied to the domain (and not the extended domain, since it is meaningless) as
$$
\sigma =\sqrt{2} \begin{bmatrix} 1\ 2\ 3 \end{bmatrix}
$$
Then put this into a diagonal matrix,
$$
C_1 = diag(\sigma.^2/2) \in R^{3\times 3}
$$
Finally, to compose this, we have$M$ and the extended domain is of size $\bar{M}$ that all multiplicative constants are diagonal and of size $M \times M$ ?
$$
L = C L_2
$$
Do I have that correct? Does this generalize, that if the domain is of size
Finally, is there any case in the composition of operators where you do would not want this as a diagonal, and what is the interpretation if you don't? This may be helpful to figure out before we make it lazy
The text was updated successfully, but these errors were encountered: