# Well-posedness of Fokker-Planck equation

Consider the following equation on $[0,T]\times\mathbb{R}^n$ \begin{eqnarray} &\partial_t\rho=\mathrm{div}(\rho\nabla V)+\Delta\rho\\ &\rho|_{t=0}=\rho^0, \end{eqnarray} where $V\in C^2(\mathbb{R}^n;\mathbb{R})$. Typical $V$ are of the form $V(x)=x^2$. Further the initial data $\rho^0\in L^1(\mathbb{R}^n;\mathbb{R})$.

Question: How would one prove the existence of solutions of this equation by using standard techniques?

My feeling is that this should work since it is a nice enough parabolic equation, however with somewhat nasty initial data. Such a question has been answered in Jordan-Kinderlehrer-Otto-98 where they use the gradient flow structure of the equation. They assume additionally that the initial data has bounded moments which could be done here as well.

It should also be noted that the above PDE is the Fokker-Planck equation associated to the stochastic differential equation $$$$dX_t=-\nabla V(X_t)dt+\sqrt{2} dW_t,$$$$ where $W_t$ denotes an $n$-dimensional Wiener-process. And since the drift $-\nabla V$ is sufficiently regular, standard results suggest that this equation has a solution. However, I do not yet understand what this result implies for the corresponding Fokker-Planck equation.

The argument in JKO (short for Jordan-Kinderlehrer-Otto-98) is based on a Lyapunov function for the Fokker-Planck equation. As such, it requires that this Lyapunov function evaluated at $\rho^0$ be finite. (The main result of JKO assumes this condition.) This is a strong constraint on $\rho^0$: it seems to require, e.g., that the support of $\rho^0$ be $\mathbb{R}^n$. For your convenience here is the Lyapunov function from JKO: $$F(\rho) = \int_{\mathbb{R}^n} \rho \; ( V - \underbrace{(- \log \rho )}_{\text{free energy of \rho}} ) dx$$
• $V$ is of class $C^2$;
• the transition probability of $X(t)$ admits a probability density function that is twice differentiable for $t>0$; and,
• the probability law of $X(0)$ has a continuous probability density function on $\mathbb{R}^n$.