### Abstract

We performed Metropolis Monte Carlo and a comprehensive set of reverse Monte Carlo simulations using the same Lennard-Jones liquid to analyze the algorithmic correctness of the latter method. We found that the present reverse Monte Carlo technique is biased because it samples relatively disordered arrangements more often than ordered ones, which leads to a poor acceptance ratio and questionable relevance to the structure of the real system. On the basis of our results, we propose changes in the algorithm. To remove the deficiency we applied a combined acceptance criterion, which in addition to the very restrictive difference minimization procedure, uses an entropy related factor to select from the possible configurations. Further improvement can be achieved if the simulations are performed on the structure factor and the radial distribution function simultaneously. If the radial distribution function is the target function, incorporation of the r-dependent measurement error in the acceptance criterion is essential to obtain results similar in quality to the structure function techniques. The modifications enhance the performance of the reverse Monte Carlo method without increasing the computational effort.

Original language | English |
---|---|

Pages (from-to) | 7402-7408 |

Number of pages | 7 |

Journal | The Journal of Chemical Physics |

Volume | 107 |

Issue number | 18 |

Publication status | Published - Nov 8 1997 |

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### ASJC Scopus subject areas

- Atomic and Molecular Physics, and Optics

### Cite this

*The Journal of Chemical Physics*,

*107*(18), 7402-7408.

**Conceptual and technical improvement of the reverse Monte Carlo algorithm.** / Tóth, Gergely; Baranyai, A.

Research output: Contribution to journal › Article

*The Journal of Chemical Physics*, vol. 107, no. 18, pp. 7402-7408.

}

TY - JOUR

T1 - Conceptual and technical improvement of the reverse Monte Carlo algorithm

AU - Tóth, Gergely

AU - Baranyai, A.

PY - 1997/11/8

Y1 - 1997/11/8

N2 - We performed Metropolis Monte Carlo and a comprehensive set of reverse Monte Carlo simulations using the same Lennard-Jones liquid to analyze the algorithmic correctness of the latter method. We found that the present reverse Monte Carlo technique is biased because it samples relatively disordered arrangements more often than ordered ones, which leads to a poor acceptance ratio and questionable relevance to the structure of the real system. On the basis of our results, we propose changes in the algorithm. To remove the deficiency we applied a combined acceptance criterion, which in addition to the very restrictive difference minimization procedure, uses an entropy related factor to select from the possible configurations. Further improvement can be achieved if the simulations are performed on the structure factor and the radial distribution function simultaneously. If the radial distribution function is the target function, incorporation of the r-dependent measurement error in the acceptance criterion is essential to obtain results similar in quality to the structure function techniques. The modifications enhance the performance of the reverse Monte Carlo method without increasing the computational effort.

AB - We performed Metropolis Monte Carlo and a comprehensive set of reverse Monte Carlo simulations using the same Lennard-Jones liquid to analyze the algorithmic correctness of the latter method. We found that the present reverse Monte Carlo technique is biased because it samples relatively disordered arrangements more often than ordered ones, which leads to a poor acceptance ratio and questionable relevance to the structure of the real system. On the basis of our results, we propose changes in the algorithm. To remove the deficiency we applied a combined acceptance criterion, which in addition to the very restrictive difference minimization procedure, uses an entropy related factor to select from the possible configurations. Further improvement can be achieved if the simulations are performed on the structure factor and the radial distribution function simultaneously. If the radial distribution function is the target function, incorporation of the r-dependent measurement error in the acceptance criterion is essential to obtain results similar in quality to the structure function techniques. The modifications enhance the performance of the reverse Monte Carlo method without increasing the computational effort.

UR - http://www.scopus.com/inward/record.url?scp=0040374374&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0040374374&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0040374374

VL - 107

SP - 7402

EP - 7408

JO - Journal of Chemical Physics

JF - Journal of Chemical Physics

SN - 0021-9606

IS - 18

ER -