  An important task in the simulation of hard spheres and other hard particles
is structure prediction via equilibration. Event-driven molecular dynamics is
efficient because its Newtonian dynamics equilibrates fluctuations with the
speed of sound. Monte Carlo simulation is efficient if performed with
correlated position updates in event chains. Here, we combine the core concepts
of molecular dynamics and event chains into a new algorithm involving Newtonian
event chains. Measurements of the diffusion coefficient, nucleation rate, and
melting speed demonstrate that Newtonian event chains outperform other
algorithms. Newtonian event chains scale well to large systems and can be
extended to anisotropic hard particles without approximations.
