Before revision: We construct  zig-zag processes targeting posterior distributions arising in genetics from the Kingman coalescent and two popular models of mutation. We show that the zig-zag process can lead to efficiency gains of up to several orders of magnitude over classical Metropolis-Hastings algorithms, and that it is well suited to parallel computation for coalescent models .
After revision: We construct zig-zag processes targeting posterior distributions arising in genetics from the Kingman coalescent , showing that the zig-zag process can lead to efficiency gains of up to several orders of magnitude over classical Metropolis-Hastings algorithms, and that it is well suited to parallel computation for coalescent models .