Conditional independence while sampling using NUTS

I am trying to sample from a posterior distribution. The model is defined by a DAG of parameters. There are several conditional independencies among the parameters to be sampled. Does Stan automatically take advantage of this to optimize sampling of the posterior, when using NUTS/HMC?

If not, is there something I can do to specify the conditional independencies to make the sampling faster?

Welcome to the Stan forum!

To the best of my knowledge Stan does not (try to) detect conditional independencies to optimize sampling.

However, I also don’t know how excatly this optimization would work. Could you point to an article where this is done for another sampler so that people get a better idea of what you are looking after.