Deep Learning Hamiltonian Monte Carlo

Understand

We generalize the Hamiltonian Monte Carlo algorithm with a stack of neural network layers and evaluate its ability to sample from different topologies in a two dimensional lattice gauge theory.

• We demonstrate that our model is able to successfully mix between modes of different topologies, significantly reducing the computational cost required to generated independent gauge field configurations.
• Our implementation is available at https://github.com/saforem2/l2hmc-qcd .