title: Optimizing the ensemble for equilibration in broad-histogram Monte Carlo simulations.
abstract: 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 ln N](2) ) for both the ferromagnetic and the fully frustrated two-dimensional Ising model with N spins. Our algorithm thereby substantially outperforms flat-histogram methods such as the Wang-Landau algorithm.
authors.affiliation: Theoretische Physik, Eidgenössische Technische Hochschule Zürich, CH-8093 Zürich, Switzerland.
authors.forename: Simon
authors.initials: S
authors.lastname: Trebst
authors.forename: David A
authors.initials: DA
authors.lastname: Huse
authors.forename: Matthias
authors.initials: M
authors.lastname: Troyer