Fast geometry optimization with the FIRE minimizer

Geometry optimization is a fundamental step in many molecular modeling applications, used to produce stable, realistic structures which correspond to energy minima. Many algorithms have been developed for energy minimization, and we have just released a new SAMSON Extension that implements the FIRE minimizer described by Bitzek et al.: Erik Bitzek, Pekka Koskinen, Franz Gähler, Michael Moseler, and Peter Gumbsch, Structural Relaxation Made Simple. Physical Review Letters, Vol. 97, 170201 (2006)

FIRE, which stands for Fast Inertial Relaxation Engine, is an efficient optimizer for molecular structures.

Add the FIRE State Updater Extension it to your SAMSON installation by clicking the Add button (you need to be signed in). Then, restart SAMSON and the newly added SAMSON Extensions will be automatically installed.

In order to use FIRE, open a molecular system and apply a new simulator to it (Simulation / Add simulator). Select the interaction model you want to use, and select FIRE in the list of state updaters.

Three settings are available:

  1. Step size: this is the initial step size given to the algorithm
  2. Steps: this is the number of steps between two successive viewport updates
  3. Fixed: forces the time step to be constant (not necessarily needed)

You may press the ‘Reset’ button if you manually move atoms during minimization and want to clear the FIRE history.

FIRE is significantly faster than the steepest descent algorithm, in particular for large-scale motions that do not affect much the potential energy:

FIRE Relaxation

Steepest Descent Relaxation

In the example above, the user needs to increase the ‘Steps’ parameter (i.e. the number of minimization steps between two viewport updates) in order to be able to see minimization happen.

Since the FIRE minimizer is implemented as a SAMSON state updater, you may use it in any application that relies on an optimization algorithm.
If you have any questions or feedback, please use the SAMSON forum.

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