@@ -317,11 +313,9 @@ the :class:`ase.optimize.precon.lbfgs.PreconLBFGS` and
You can read more about the theory and implementation here:
| D. Packwood, J.R. Kermode; L. Mones, N. Bernstein, J. Woolley, N. Gould, C. Ortner and G. Csányi
| `A universal preconditioner for simulating condensed phase materials`__
| :doi:`A universal preconditioner for simulating condensed phase materials <10.1063/1.4947024>`
| J. Chem. Phys. *144*, 164109 (2016).
__ https://doi.org/10.1063/1.4947024
Tests with a variety of solid-state systems using both DFT and classical
interatomic potentials driven though ASE calculators show speedup factors of up
to an order of magnitude for preconditioned L-BFGS over standard L-BFGS, and the
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@@ -473,18 +467,15 @@ local optimization algorithm::
Read more about this algorithm here:
| David J. Wales and Jonathan P. K. Doye
| `Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms`__
| :doi:`Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms <10.1021/jp970984n>`
| J. Phys. Chem. A, Vol. **101**, 5111-5116 (1997)
__ https://doi.org/10.1021/jp970984n
and here:
| David J. Wales and Harold A. Scheraga
| `Global Optimization of Clusters, Crystals, and Biomolecules`__
| :doi:`Global Optimization of Clusters, Crystals, and Biomolecules <10.1126/science.285.5432.1368>`
The minima hopping algorithm was developed and described by Goedecker:
| Stefan Goedecker
| `Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems`__
| :doi:`Minima hopping: An efficient search method for the global minimum of the potential energy surface of complex molecular systems <10.1063/1.1724816>`
| J. Chem. Phys., Vol. **120**, 9911 (2004)
__ https://doi.org/10.1063/1.1724816
This algorithm utilizes a series of alternating steps of NVE molecular dynamics and local optimizations, and has two parameters that the code dynamically adjusts in response to the progress of the search. The first parameter is the initial temperature of the NVE simulation. Whenever a step finds a new minimum this temperature is decreased; if the step finds a previously found minimum the temperature is increased. The second dynamically adjusted parameter is `E_\mathrm{diff}`, which is an energy threshold for accepting a newly found minimum. If the new minimum is no more than `E_\mathrm{diff}` eV higher than the previous minimum, it is acccepted and `E_\mathrm{diff}` is decreased; if it is more than `E_\mathrm{diff}` eV higher it is rejected and `E_\mathrm{diff}` is increased. The method is used as::
from ase.optimize.minimahopping import MinimaHopping
@@ -24,9 +24,7 @@ This module contains utility functions and classes.
Symmetry equivalence checker
============================
This module compares two atomic structures to see if they are symmetrically equivalent. It is based on the recipe used in `XtalComp`__
__ https://doi.org/10.1016/j.cpc.2011.11.007
This module compares two atomic structures to see if they are symmetrically equivalent. It is based on the recipe used in :doi:`XtalComp <10.1016/j.cpc.2011.11.007>`
