Random batch list method for metallic system with embedded atom potential

Abstract

The embedded atom method (EAM) is one of the most widely used many-body, short-range potentials in molecular dynamics simulations, particularly for metallic systems. To enhance the efficiency of calculating these short-range interactions, we extend the random batch list (RBL) concept to the EAM potential, resulting in the RBL-EAM algorithm. The newly presented method introduces two "core-shell" lists for approximately computing the host electron densities and the force terms, respectively. Direct interactions are computed in the core regions, while in the shell zones a random batch list is used to reduce the number of interaction pairs, leading to significant reductions in both computational complexity and storage requirements. We provide a theoretical, unbiased estimate of the host electron densities and the force terms. Since metallic systems are Newton-pair systems, we extend the RBL-EAM algorithm to exploit this property, thereby halving the computational cost. Numerical examples, including the lattice constant, the radial distribution function, and the elastic constants, demonstrate that the RBL-EAM method significantly accelerates simulations several times without compromising accuracy.