Yes, this is precisely what MCMC methods do as well. Every posterior distribution is a Boltzmann distribution for some energy function.

>However, since we initialize chains with a random prior distribution, each individual chain is individually likely to hit any mode so all modes are likely to be explored.

This is also a pretty standard technique in MCMC. But most high-dimension Bayesian models have a huge amount of modes that that cannot be explored in a reasonable number of samples/chains.