Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations

Details Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations

2004-01-12

arxiv.org/abs/cond-mat/0401195v3

Phys. Rev. E 70, 046701 (2004).

Physics

Condensed Matter

Statistical Mechanics

6 pages, 5 figures

Scientific paper

10.1103/PhysRevE.70.046701

We present an adaptive algorithm which optimizes the statistical-mechanical ensemble in a generalized broad-histogram Monte Carlo simulation to maximize the system's rate of round trips in total energy. The scaling of the mean round-trip time from the ground state to the maximum entropy state for this local-update method is found to be O([N log N]^2) for both the ferromagnetic and the fully frustrated 2D Ising model with N spins. Our new algorithm thereby substantially outperforms flat-histogram methods such as the Wang-Landau algorithm.

Affiliated with

Also associated with

No associations

Rating

Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-266300