Efficient event-driven simulations of hard spheres

Abstract

Hard spheres are arguably one of the most fundamental model systems in soft matter physics, and hence a common topic of simulation studies. Event-driven simulation methods provide an efficient method for studying the phase behavior and dynamics of hard spheres under a wide range of different conditions. Here, we examine the impact of several optimization strategies for speeding up event-driven molecular dynamics of hard spheres, and present a light-weight simulation code that outperforms existing simulation codes over a large range of system sizes and packing fractions. The presented differences in simulation speed, typically a factor of five to ten, save significantly on both CPU time and energy consumption, and may be a crucial factor for studying slow processes such as crystal nucleation and glassy dynamics.1 It should be noted that variations on EDMD that simulate Brownian[49] or Langevin [50] dynamics have been developed as well.

Self-assembly of dodecagonal and octagonal quasicrystals in hard spheres on a plane

“…The simulation algorithm is a variant of the methods described in Ref. [20]. Initial configurations consisting of N L + N S = 2000 particles at different packing fractions were obtained by starting in a dilute state at the desired composition, and then performing an EDMD simulation in which the particle diameters grow until the desired packing fraction is reached.…”

“…As such, colloidal hard spheres have been instrumental in enhancing our understanding of crystal nucleation [1,2], crystallization in confinement [3][4][5][6][7][8][9], two-dimensional melting [10,11], glassy dynamics [12][13][14][15][16], crystal defects [17][18][19], among many others. Their important role in soft matter science stems not only from their theoretical simplicity and the ease and speed at which they can be simulated [20,21], but also from the fact that they can be quantitatively explored in the lab [22][23][24][25].…”