I think this works just fine. I’ve replaced the target likelihood \pi(x) by the product distribution \Pi(X) = \prod_{j=1}^n \pi(x_j), so HMC converges in probability to a sample over \Pi(X) - i.e., n i.i.d. samples from \pi(x).
I think this works just fine. I’ve replaced the target likelihood \pi(x) by the product distribution \Pi(X) = \prod_{j=1}^n \pi(x_j), so HMC converges in probability to a sample over \Pi(X) - i.e., n i.i.d. samples from \pi(x).