Efficient $d$-dimensional molecular dynamics simulations for studies of the glass-jamming transition

TL;DR

This paper introduces a scalable, parallel molecular dynamics algorithm in arbitrary dimensions, enabling large-scale simulations of glass and jamming transitions, revealing new insights into high-dimensional supercooled liquids.

Contribution

The authors develop and implement a versatile, efficient parallel MD algorithm in arbitrary dimensions, facilitating large-scale studies of glass and jamming phenomena.

Findings

High-dimensional supercooled liquids show increased dynamical heterogeneity.

Breakdown of the Stokes-Einstein relation is more pronounced in larger, high-dimensional systems.

Simulation capabilities surpass previous studies in system size and dimensionality.

Abstract

We develop an algorithm suitable for parallel molecular dynamics simulations in $d$ spatial dimensions and describe its implementation in C++. All routines work in arbitrary $d$; the maximum simulated $d$ is limited only by available computing resources. These routines include several that are particularly useful for studies of the glass/jamming transition, such as SWAP Monte Carlo and FIRE energy minimization. Scaling of simulation runtimes with the number of particles $N$ and number of simulation threads $n_{\rm threads}$ is comparable to popular MD codes such as LAMMPS. The efficient parallel implementation allows simulation of systems that are much larger than those employed in previous high-dimensional glass-transition studies. As a demonstration of the code's capabilities, we show that supercooled $d = 6$ liquids can possess dynamics that are substantially more heterogeneous and experience a breakdown of the Stokes-Einstein relation that is substantially stronger than previously reported, owing at least in part to the much smaller system sizes employed in earlier simulations.