[Here are comments made by Matt Graham that I thought would be more readable in a post format. The beautiful picture of the Alps above is his as well. I do not truly understand what Matt’s point is, as I did not cover continuous time processes in my discussion…]
In terms of interpretation of the diffusion with non-reversible drift component, I think this can be generalised from the Gaussian invariant density case by
dx = [ – (∂E/∂x) dt + √2 dw ] + S’ (∂E/∂x) dt
where ∂E/∂x is the usual gradient of the negative log (unnormalised) density / energy and S=-S’ is a skew symmetric matrix. In this form it seems the dynamic can be interpreted as the composition of an energy and volume conserving (non-canonical) Hamiltonian dynamic
dx/dt = S’ ∂E/∂x
and a (non-preconditioned) Langevin diffusion
dx = – (∂E/∂x) dt + √2 dw
As an alternative to discretising the combined dynamic, it might be interesting to compare to sequential alternation between ‘Hamiltonian’ steps either using a simple Euler discretisation
x’ = x + h S’ ∂E/∂x
or a symplectic method like implicit midpoint to maintain reversibility / volume preservation and then a standard MALA step
x’ = x – h (∂E/∂x) + √2 h w, w ~ N(0, I)
plus MH accept. If only one final MH accept step is done this overall dynamic will be reversible, however if a an intermediary MH accept was done after each Hamiltonian step (flipping the sign / transposing S on a rejection to maintain reversibility), the composed dynamic would in general be non-longer reversible and it would be interesting to compare performance in this case to that using a non-reversible MH acceptance on the combined dynamic (this alternative sidestepping the issues with finding an appropriate scale ε to maintain the non-negativity condition on the sum of the vorticity density and joint density on a proposed and current state).
With regards to your point on the positivity of g(x,y)+π(y)q(y,x), I’m not sure if I have fully understood your notation correctly or not, but I think you may have misread the definition of g(x,y) for the discretised Ornstein-Uhlenbeck case (apologies if instead the misinterpretation is mine!). The vorticity density is defined as the skew symmetric component of the density f of F(dx, dy) = µ(dx) Q(x, dy) with respect to the Lebesgue measure, where µ(dx) is the true invariant distribution of the Euler-Maruyama discretised diffusion based proposal density Q(x, dy) rather than g(x, y) being defined in terms of the skew-symmetric component of π(dx) Q(x, dy) which in general would lead to a vorticity density which does not meet the zero integral requirement as the target density π is not invariant in general with respect to Q.
Jordan Franks just posted on arXiv his PhD dissertation at the University of Jyväskylä, where he discuses several of his works:
