The classic 1953 paper of Metropolis et al. [2] introduced to us the world of Markov Chain Monte Carlo (MCMC). In their work, MCMC was used to simulate the distribution of states for a system of idealized molecules. Not long after this, in 1959, another approach to molecular simulation was introduced by Alder and Wainwright [14], in which they used a deterministic algorithm for the motion of the molecules. This algorithm followed Newton’s laws of motion, and it can be formalized in an elegant way using Hamiltonian dynamics. The two approaches, statistical (MCMC) and deterministic (molecular dynamics), coexisted peacefully for a long time. In 1987, an extraordinary paper by Duane et al. [15] combined the MCMC and molecular dynamics approaches. They called their method Hybrid Monte Carlo (HMC).