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Force-based gradient descent method for ab initio atomic structure relaxation

  • Yukuan Hu
  • , Xingyu Gao
  • , Yafan Zhao
  • , Xin Liu
  • , Haifeng Song
  • Chinese Academy of Sciences
  • University of Chinese Academy of Sciences
  • Institute of Applied Physics and Computational Mathematics
  • China Academy of Engineering Physics

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

Résumé

Force-based algorithms for ab initio atomic structure relaxation, such as conjugate gradient methods, usually get stuck in the line minimization processes along search directions, where expensive ab initio calculations are triggered frequently to test trial positions before locating the next iterate. We present a force-based gradient descent method, WANBB, that circumvents the deficiency. At each iteration, WANBB enters the line minimization process with a trial step size capturing the local curvature of the energy surface. The exit is controlled by a nonrestrictive criterion that tends to accept early trials. These two ingredients streamline the line minimization process in WANBB. The numerical simulations on nearly 80 systems with good universality demonstrate the considerable compression of WANBB on the cost for the unaccepted trials compared with conjugate gradient methods. We also observe across the board significant and universal speedups as well as the superior robustness of WANBB over several widely used methods. The latter point is theoretically established. The implementation of WANBB is pretty simple, in that no a priori physical knowledge is required and only three parameters are present without tuning.

langue originaleAnglais
Numéro d'article104101
journalPhysical Review B
Volume106
Numéro de publication10
Les DOIs
étatPublié - 1 sept. 2022
Modification externeOui

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