Efficient equilibration of hard spheres with Newtonian event chains

Area of Science:

• Computational physics
• Materials science
• Statistical mechanics

Background:

• Structure prediction for hard particles is crucial for simulations.
• Event-driven molecular dynamics and Monte Carlo simulations are common but have limitations.

Purpose of the Study:

• To introduce a new simulation algorithm, Newtonian event chains.
• To enhance the efficiency and scalability of hard particle simulations.

Main Methods:

• Combining concepts from molecular dynamics and event chains.
• Developing a novel algorithm based on Newtonian dynamics and event chains.

Main Results:

• Newtonian event chains demonstrate superior performance in simulations.
• Measurements show improved diffusion coefficient, nucleation rate, and melting speed.
• The algorithm scales well for large systems and anisotropic particles.

Conclusions:

• Newtonian event chains offer a significant advancement in simulating hard particle systems.
• The algorithm is versatile and can be extended to complex particle types without approximations.