### Abstract

An adaptive algorithm which optimize the statistical-mechanical ensemble in a generalized broad-histogram Monte Carlo simulation to maximize the system's rate of round trips in total energy was presented. It was found that the scaling of the mean round-trip time from the ground state to the maximum entropy state for this local-update method was O([NInN])^{2}) for both the ferromagnetic and the fully frustrated two-dimensional Ising model with N spins. It was shown that the algorithm substantially outperforms flat-histogram methods such as the Wang-Landau algorithm. This algorithm was widely applicable to study the equilibrium behavior of complex system, such as glasses, dense fluids or polymers.

Original language | English (US) |
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Article number | 046701 |

Pages (from-to) | 046701-1-046701-5 |

Journal | Physical Review E - Statistical, Nonlinear, and Soft Matter Physics |

Volume | 70 |

Issue number | 4 2 |

DOIs | |

State | Published - Oct 1 2004 |

### All Science Journal Classification (ASJC) codes

- Statistical and Nonlinear Physics
- Statistics and Probability
- Condensed Matter Physics

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## Cite this

*Physical Review E - Statistical, Nonlinear, and Soft Matter Physics*,

*70*(4 2), 046701-1-046701-5. [046701]. https://doi.org/10.1103/PhysRevE.70.046701