Version 1.0: Change log

Generates a suitably converged k-point grid for solid-state quantum chemical calculations.

Two programs are provided: kgrid and kgrid-series

• The specified input file is read using Atomic Simulation Environment (supported formats)
  • If none is specified, looks for geometry.in (FHI-aims) in working directory
• A k-point density is selected to satisfy a given length cutoff, as described by Moreno & Soler (1992)[1]. The length cutoff corresponds to a radius about repeated images that would be needed in a gamma-point supercell calculation to achieve the same sampling.
• This k-point grid is expressed as a number of samples in each lattice vector and passed to standard output. (Note that this is NOT a Moreno-Soler grid as it does not use symmetry information to minimise the required number of points. It is a uniform grid specified with the same length parameter notation.)
• Default k-point cutoff is 10Å (generally well-converged for semiconducting or insulating materials)
• Optional arguments are implemented with conventional GNU/POSIX syntax, including -h help option

• Reports a series of "critical" cutoffs and KSPACING values with their corresponding k-point grids.
• These may be very useful for convergence testing, but users should be wary of rounding behaviour near these values.

• Developed with Python 2.7; not tested with other versions
• Atomic Simulation Environment (ASE)
• Numpy (Also a requirement for ASE.)

From the command line

    kgrid -f FILE -t TYPE -c CUTOFF

will return a suggested set of mesh dimensions. FILE can be any file format supported by ASE; if no FILE is specified, kgrid will look for a geometry.in file in the current directory. TYPE is a string specifying the format of this file; usually this argument can be left out and the correct type will be inferred by ASE. CUTOFF is the real-space cutoff parameter in Å and defaults to 10.0.

There is an internal Python function which may prove useful to ASE users, with the form

kgrid.calc_kpt_tuple(atoms, cutoff_length=10)

where atoms is an ASE atoms object and the function returns a tuple. As such, kgrid may be used while setting up a calculation with a typical ASE calculator. For example:

import kgrid
from ase.io import read
from ase.calculators.vasp import Vasp

atoms = read('my_favourite_structure.cif')
calc = Vasp(xc='PBE',
            kpts=kgrid.calc_kpt_tuple(atoms))
atoms.set_calculator(calc)
atoms.get_total_energy()

would perform a VASP calculation in the current directory with the PBE functional, using kgrid to determine the reciprocal-space sampling.

kgrid-series -file FILE -t TYPE --min MIN --max MAX

Example output:

Length cutoff  KSPACING    Samples
-------------  --------  ------------
      10.630    0.2956     2   7   4
      11.260    0.2790     2   8   4
      11.860    0.2649     2   8   5
      12.148    0.2586     3   8   5
      13.666    0.2299     3   9   5
      14.075    0.2232     3  10   5
      15.185    0.2069     3  10   6
      16.703    0.1881     3  11   6
      16.890    0.1860     3  12   6
      17.790    0.1766     3  12   7
      18.222    0.1724     4  12   7
      19.705    0.1594     4  13   7
      19.741    0.1591     4  13   8
      21.259    0.1478     4  14   8
      22.520    0.1395     4  15   8
      22.777    0.1379     4  15   9
      23.720    0.1324     4  16   9
      24.296    0.1293     5  16   9
      25.335    0.1240     5  17   9
      25.814    0.1217     5  17  10
      27.333    0.1149     5  18  10
      28.150    0.1116     5  19  10
      28.852    0.1089     5  19  11
      29.650    0.1060     5  20  11

kgrid uses setuptools; from a reasonable healthy Python environment you can use

pip install .

with the usual pip caveats:

• the --user flag is highly recommended and avoids the need for administrator privileges, but on a somewhat unhealthy Python installation the user packages location may not be on your paths yet.
• the -e flag creates an "editable" installation which links to this repository and enables easy updates with git.

kgrid is not tested on Windows but no problems are anticipated; the Anaconda Python distribution includes pip. On Mac OSX, the system Python does not include pip but there are various ways of getting a more complete distribution such as Homebrew or Anaconda.

This program is not affiliated with ASE or any particular quantum chemistry code. This program is made available under the GNU General Public License; you are free to modify and use the code, but do so at your own risk.

[1] Moreno, J., & Soler, J. (1992). Optimal meshes for integrals in real- and reciprocal-space unit cells. Physical Review B, 45(24), 13891–13898. doi:10.1103/PhysRevB.45.13891