# Efficient Equilibration of Hard Spheres with Newtonian Event Chains

## TL;DR

This paper introduces Newtonian event chains, a novel algorithm that combines molecular dynamics and event chains, significantly improving the efficiency of simulating hard sphere systems and capable of handling large and anisotropic particles.

## Contribution

The paper presents a new algorithm called Newtonian event chains that outperforms existing methods in simulating hard particles, with scalable performance and applicability to anisotropic shapes.

## Key findings

- Newtonian event chains outperform other algorithms in diffusion, nucleation, and melting simulations.
- The method scales well to large systems.
- It can be extended to anisotropic particles without approximations.

## Abstract

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.