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Stochastic ordinary and partial differential equations generalize the concepts of ordinary and partial differential equations to the setting where the unknown is a stochastic process.

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Each diffusion SDE is associated to a *unique* family of transition kernels

there are unique corresponding forward/backward equations (Fokker Plank) to an SDE, and unique solutions for them that correspond to transition kernels. See the nice notes here Lecture 10: Forward and …
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4 votes

Gibbs measure as stationary distribution of SDEs

Here is some answers for your first two questions. answer to Q1 Yes,the SDE $${\rm d}U_t= - H'(U_t) {\rm d}t+\sqrt {2} \, {\rm d} B_t,$$ has the following Fokker-Plank equation (i.e. the pde satisfied …
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Weak uniqueness of an SDE with locally Lipschitz drift and additive noise?

For d=1, this is covered in Karatzas-Shreve in the section on Feller-tests. In particular, in exercise 5.38, they have that if $$\int_{x-\epsilon}^{x+\epsilon}b^{2}(y)dy<\infty,$$ then $dX_{t}=b(X_{t} …
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What happens when the diffusion term in an SDE becomes zero?

Following a comparison result (eg. Comparison theorem in Revuz-Yor Chap. IX §3), we will show that $X_{t}\leq b$ for all $t\geq 0$. This result requires though the Yamada-Watanabe regularity $$|\sigma …
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Decay estimate of moment of an SDE

Since we can apply Burkholder-Davis-Gundy to control the supremum of moments, we start by removing the tail simply using $1\leq \frac{|X_{t}|}{R}$. $$ \mathbb E [ |X_t|^p 1_{\{|X_t| \ge R\}} ]\leq \fr …
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3 votes
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Expectation of stochastic integral

As mentioned in an answer here and in the blog here, A sufficient condition for the integral $\int_0^t f(\omega, s)\, dB_s$ to be a martingale on $[0,T]$ is that $f(\omega,s)$ is adapted, measurable …
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Estimates on perturbation of drift of SDEs

The difference is $$X_t^1-X_t^2=\int_0^t\, \mu_1(X_s^1)-\mu_2(X_s^2)ds + \int_0^t\,\sigma(X_s^1)-\sigma(X_s^2)dW_s.$$ For the second term, you can use that it is a martingale and apply Burkholder-Davi …
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2 votes

Feynman-Kac formula with non-zero boundary condition

As mentioned in the comments here Feynman-Kac formula for domains with boundary, there is a Feyman-Kac type result for heat equation with boundary data in Theorem 4.2 in Chapter 7.4 in the book "Sto …
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2 votes

Stochastic inverse

The LHS might not make sense if g is very irregular. Consider, pth-Holder function $g(x)=x^{p}$ for $0<p<1$ and $\frac{1}{p}$ odd integer and Brownian motion $X_{t}=B_{t}$, then the process $g(X_{t})= …
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2 votes

Textbook definition for "path measure" or "probability measure over paths"

since I don't see any other answers, I will turn my comment into answer. One Wiener measure and path integrals reference is "Quantum Physics: a Functional Integral Point of View" from here https://mat …
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2 votes

What is the formal definition of a stochastic PDE and a solution to a stochastic PDE?

Since I don't see any other answers, I move my comments to answer. Here are some good introductory references for SPDEs, by Hairer: hairer.org/notes/SPDEs.pdf, Bréhier: hal.archives-ouvertes.fr/hal-00 …
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2 votes

Blow up limits for SDE

First for the case of $\sigma\neq 0$ to get convergence as paths. As described here https://almostsuremath.com/2010/05/17/sdes-under-changes-of-time-and-measure/, the above process is a time-changed B …
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How to obtain this differential relation about moments of a stochastic process?

I believe you meant lemma 3.8. Here at the final step of your calculation, you just apply Lebesgue-differentiation theorem since those quantities are continuous and the integral is Lebesgue. That will …
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Uniqueness of the solution to stochastic differential equation

First for the case of time-independent coefficients (autonomous). A good setting for this question is the Feller-explosion test (see here Is this process strictly positive? for related question). The …
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2 votes

Stochastic Stokes flow: where to start from?

In the 2d-case a lot of results have been proved already: see textbook by Sergei Kuksin, Armen Shirikyan "Mathematics of Two-Dimensional Turbulence" (see equation 2.100 for Stochastic Stokes). In term …
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