I have seen different versions and formulations of Hörmander's theorem for SDEs, and I'm a bit unclear on the whole subject and am seeking some clarifications.
Notations, and definition of Lie bracket
Let $M$ be a $C^\infty$-smooth manifold, and let $\mathcal{V}$ be the set of $C^\infty$ vector fields on $M$. For any $\mathcal{S} \subset \mathcal{V}$ and $x \in M$, let $$ \mathcal{S}(x) = \{v(x) : v \in \mathcal{S}\}\text{.} $$ For any chart $\varphi \colon U \to \mathbb{R}^D$ on $M$ and any $v \in \mathcal{V}$, define $v_\varphi$ to be the expression of $v$ in the coordinates given by $\varphi$; that is, \begin{align*} &v_\varphi \colon \varphi(U)\to \mathbb{R}^D \\ &v_\varphi(y) = \left.\mathrm{d}\varphi\right|_{\varphi^{-1}(y)}(v(\varphi^{-1}(y)))\text{.} \end{align*} With this, define the Lie bracket $[\boldsymbol{\cdot},\boldsymbol{\cdot}] \colon \mathcal{V} \times \mathcal{V} \to \mathcal{V}$ by $$ [u,v]_\varphi(y) = v_\varphi'(y)u_\varphi(y) - u_\varphi'(y)v_\varphi(y) $$ where the prime $'$ denotes the Jacobian matrix. A Lie subalgebra of $\mathcal{V}$ is a vector subspace of $\mathcal{V}$ that is closed under the Lie bracket.
SDEs and Hörmander conditions
Consider on $M$ the SDE $$ dX_t = b(X_t) dt + \sum_{i=1}^k \sigma_i(X_t) \circ dW_t^i $$ where $b,\sigma_1,\ldots,\sigma_k \in \mathcal{V}$, and $(W_t^1,\ldots,W_t^k)$ is a $k$-dimensional standard Brownian motion. (There is not necessarily any relationship between $k$ and the dimension $D$ of $M$.)
Let
- $\mathcal{V}_1$ be the smallest vector subspace of $\mathcal{V}$ with the properties that $\sigma_1,\ldots,\sigma_k \in \mathcal{V}_1$ and for all $v \in \mathcal{V}_1$, $[v,b],[v,\sigma_1],\ldots,[v,\sigma_k] \in \mathcal{V}_1$;
- $\mathcal{V}_2$ be the smallest Lie subalgebra of $\mathcal{V}$ with the properties that $\sigma_1,\ldots,\sigma_k \in \mathcal{V}_2$ and for all $v \in \mathcal{V_2}$, $[v,b] \in \mathcal{V}_2$.
[I have sometimes seen the condition for "Hörmander's theorem" formulated as $\mathcal{V}_1(x)=T_xM$ for all $x \in M$ (the "parabolic Hörmander condition"). But I have also seen "Hörmander's condition on a collection of vector fields": Ignoring $b$ by setting $b=0$, "Hörmander's condition for vector fields $\sigma_1,\ldots,\sigma_k$" is sometimes defined as $\mathcal{V}_1(x)=T_xM$ for all $x$, and sometimes defined as $\mathcal{V}_2(x)=T_xM$ for all $x$ (and sometimes both, as though it is obvious that the two conditions are equivalent).]
Questions.
When we refer to "the Lebesgue measure on $M$", we can refer to any measure $\lambda$ on $M$ such that for any chart $\varphi \colon U \to \mathbb{R}^D$, the pushforward $\varphi_\ast(\lambda|_{\mathcal{B}(U)})$ has strictly positive $C^\infty$ density with respect to the Lebesgue measure on $\varphi(U)$.
For each $x \in M$ and $T \geq 0$, define $E_{x,T}$ to be the event that a strong solution of the SDE starting at $X_0=x$ exists over $t \in [0,T]$. If $\mathbb{P}(E_{x,T})>0$, then over the restricted probability space $(E_{x,T},\mathbb{P}(\boldsymbol{\cdot}|E_{x,T}))$ define the random variable $X_T^x$ to be the location at time $T$ of the strong solution starting at $X_0=x$.
- It is clear that $\mathcal{V}_1 \subset \mathcal{V}_2$, but is it necessarily the case that $\mathcal{V}_1=\mathcal{V}_2$?
- If not, do we at least have that $(\mathcal{V}_2(x)=T_xM \ \forall x) \Rightarrow (\mathcal{V}_1(x)=T_xM \ \forall x)$?
- If $\mathcal{V}_2(x)=T_xM$ for all $x \in M$, does it follow that for each $x \in M$ and $t > 0$, if $\mathbb{P}(E_{x,t})>0$ then the law of $X_t^x$ has $C^\infty$ density w.r.t. Lebesgue?
- Going further than this: If $\mathcal{V}_2(x)=T_xM$ for all $x \in M$, does it follow that for each $x \in M$ and $t > 0$, we have $\mathbb{P}(E_{x,t})>0$ and provided $M$ is connected, the density of the law of $X_t^x$ is strictly positive everywhere in $M$? (Or at least, strictly positive Lebesgue-almost everywhere in $M$?)
- If the answer to any part of the above two questions is no, then are there any stronger conditions that make the answer yes (e.g. changing $\mathcal{V}_2$ to $\mathcal{V}_1$, and/or adding a boundedness or growth control condition on the vector fields $b,\sigma_1,\ldots,\sigma_k$ in the case that $M$ is non-compact)?
- Or alternatively, can the conclusions be weakened so that the answer is yes (e.g. only requiring that the law of $X_t^x$ is equivalent to the Lebesgue measure, without requiring any smoothness on the density.)
- Do the answers to any of the above change if we restrict to the case that $b=0$?
Remark. To answer the first question, it is probably sufficient just to determine the answer the following. Allowing ourselves (for simplicity) to take $b=0$ and $k=4$:
Is it necessarily the case that $ [[\sigma_1,\sigma_2],[\sigma_3,\sigma_4]] \in \mathcal{V}_1$?
[Sorry for asking several questions in one post. I know that it is not generally preferred practice on the StackExchange network to do so, but in this case it seems obviously natural to put these questions together.]