Parallelized event chain algorithm for dense hard sphere and polymer systems

Abstract

We combine parallelization and cluster Monte Carlo for hard sphere systems and present a parallelized event chain algorithm for the hard disk system in two dimensions. For parallelization we use a spatial partitioning approach into simulation cells. We find that it is crucial for correctness to ensure detailed balance on the level of Monte Carlo sweeps by drawing the starting sphere of event chains within each simulation cell with replacement. We analyze the performance gains for the parallelized event chain and find a criterion for an optimal degree of parallelization. Because of the cluster nature of event chain moves massive parallelization will not be optimal. Finally, we discuss first applications of the event chain algorithm to dense polymer systems, i.e., bundle-forming solutions of attractive semiflexible polymers.

Hard-sphere melting and crystallization with event-chain Monte Carlo

“…We conclude that ECMC with well-chosen chain lengths is far superior to LMC, although it can be implemented just as easily 29,30 . Even with respect to molecular dynamics, it performs very well.…”

Efficient equilibration of hard spheres with Newtonian event chains

“…16 Chain moves can be performed rejection-free in the form of event chain Monte Carlo. [17][18][19][20][21][22][23] In an event a) Electronic mail: marco.klement@fau.de b) Electronic mail: michael.engel@fau.de chain, a randomly selected particle is displaced until it collides with another particle. Next, the collision partner is displaced until it collides with yet another particle and the process iterated.…”

Event-chain Monte Carlo for classical continuous spin models

“…In the present work, we show that the novel eventchain Monte Carlo (ECMC) paradigm [14][15][16], that has already been very successful in particle systems [17][18][19][20], can also be applied to the XY model and the XY spin glass model. The paradigm breaks all three principles of the conventional Markov-chain scheme: Moves are infinitesimal rather than finite, although an event-driven scheme allows to recover finite displacements [16].…”