New publication in Journal of Physics Condensed Matter

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The Atomic Simulation Environment is a powerful python library for setting up, running and analyzing molecular simulations. I have been using it and contributing to it since around 2002 when I used the ASE-2 version in Python 1.5! The new ase-3 version is much simpler to use, and much more powerful. This paper describes some of its design principles and capabilities. If you use ASE, please cite this paper!

@article{larsen-2017-atomic-simul,
  author =       {Ask Hjorth Larsen and Jens J{\o}rgen Mortensen and Jakob
                  Blomqvist and Ivano E Castelli and Rune Christensen and
                  Marcin Dułak and Jesper Friis and Michael N Groves and
                  Bj{\o}rk Hammer and Cory Hargus and Eric D Hermes and Paul C
                  Jennings and Peter Bjerre Jensen and James Kermode and John
                  R Kitchin and Esben Leonhard Kolsbjerg and Joseph Kubal and
                  Kristen Kaasbjerg and Steen Lysgaard and J{\'o}n Bergmann
                  Maronsson and Tristan Maxson and Thomas Olsen and Lars
                  Pastewka and Andrew Peterson and Carsten Rostgaard and Jakob
                  Schi{\o}tz and Ole Sch{\"u}tt and Mikkel Strange and Kristian
                  S Thygesen and Tejs Vegge and Lasse Vilhelmsen and Michael
                  Walter and Zhenhua Zeng and Karsten W Jacobsen},
  title =        {The Atomic Simulation Environment-A Python Library for Working
                  With Atoms},
  journal =      {Journal of Physics: Condensed Matter},
  volume =       29,
  number =       27,
  pages =        273002,
  year =         2017,
  url =          {http://stacks.iop.org/0953-8984/29/i=27/a=273002},
  abstract =     {The atomic simulation environment (ASE) is a software package
                  written in the Python programming language with the aim of
                  setting up, steering, and analyzing atomistic simulations. In
                  ASE, tasks are fully scripted in Python. The powerful syntax
                  of Python combined with the NumPy array library make it
                  possible to perform very complex simulation tasks. For
                  example, a sequence of calculations may be performed with the
                  use of a simple 'for-loop' construction. Calculations of
                  energy, forces, stresses and other quantities are performed
                  through interfaces to many external electronic structure codes
                  or force fields using a uniform interface. On top of this
                  calculator interface, ASE provides modules for performing many
                  standard simulation tasks such as structure optimization,
                  molecular dynamics, handling of constraints and performing
                  nudged elastic band calculations.},
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

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