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.
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