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Manuscript Title: EVO - Evolutionary algorithm for crystal structure prediction
Authors: Silvia Bahmann, Jens Kortus
Program title: EVO
Catalogue identifier: AEOZ_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 184(2013)1618
Programming language: Python.
Computer: No limitations known.
Operating system: Linux.
RAM: Negligible compared to the requirements of the electronic structure programs used
Keywords: Evolutionary algorithm, Crystal structure prediction, New materials.
Classification: 7.8.

External routines: Quantum ESPRESSO (http://www.quantum-espresso.org/), GULP (https://projects.ivec.org/gulp/)

Nature of problem:
Crystal structure search is a global optimisation problem in 3N+3 dimensions where N is the number of atoms in the unit cell. The high dimensional search space is accompanied by an unknown energy landscape.

Solution method:
Evolutionary algorithms transfer the main features of biological evolution to use them in global searchs. The combination of the "survival of the fittest" (deterministic) and the randomised choice of the parents and normally distributed mutation steps (non-deterministic) provides a thorough search.

The algorithm is in principle only restricted by a huge search space and simultaneously increasing calculation time (memory, etc.), which is not a problem for our piece of code but for the used electronic structure programs.

Running time:
The simplest provided case runs serially and takes 30 minutes to one hour. All other calculations run for significantly longer depending on the parameters like the number and sort of atoms and the electronic structure program in use as well as the level of parallelism included.