SIESTA¶
Introduction¶
SIESTA is a density-functional theory code for very large systems based on atomic orbital (LCAO) basis sets.
Environment variables¶
The environment variable SIESTA_COMMAND must hold the command
to invoke the siesta calculation. The variable must be a python format
string with exactly two string fields for the input and output files.
Examples: siesta < %s > %s, mpirun -np 4 /bin/siesta3.2 < %s > %s.
A default directory holding pseudopotential files .vps/.psf can be
defined to avoid defining this every time the calculator is used.
This directory can be set by the environment variable
SIESTA_PP_PATH.
Set both environment variables in your shell configuration file:
$ export SIESTA_COMMAND="siesta < ./%s > ./%s"
$ export SIESTA_PP_PATH=$HOME/mypps
Alternatively, the path to the pseudopotentials can be given in the calculator initialization.
keyword |
type |
default value |
description |
|---|---|---|---|
|
|
|
Directory for pseudopotentials to use None means using $SIESTA_PP_PATH |
SIESTA Calculator¶
These parameters are set explicitly and overrides the native values if different.
keyword |
type |
default value |
description |
|---|---|---|---|
|
|
|
Name of the output file |
|
|
|
Mesh cut-off energy in eV |
|
|
|
Exchange-correlation functional. Corresponds to either XC.functional or XC.authors keyword in SIESTA |
|
|
|
Energy shift for determining cutoff radii |
|
|
|
Monkhorst-Pack k-point sampling |
|
|
|
Type of basis set (‘SZ’, ‘DZ’, ‘SZP’, ‘DZP’) |
|
|
|
The spin approximation used, must be
either |
|
|
|
A method for specifying a specific description for some atoms. |
|
|
|
String for picking out specific type
type of pseudopotentials. Giving
|
Most other parameters are set to the default values of the native interface.
Extra FDF parameters¶
The SIESTA code reads the input parameters for any calculation from a
.fdf file. This means that you can set parameters by manually setting
entries in this input .fdf file. This is done by the argument:
>>> Siesta(fdf_arguments={'variable_name': value, 'other_name': other_value})
For example, the DM.MixingWeight can be set using
>>> Siesta(fdf_arguments={'DM.MixingWeight': 0.01})
The explicit fdf arguments will always override those given by other keywords, even if it breaks calculator functionality. The complete list of the FDF entries can be found in the official SIESTA manual.
Example¶
Here is an example of how to calculate the total energy for bulk Silicon, using a double-zeta basis generated by specifying a given energy-shift:
>>> from ase import Atoms
>>> from ase.calculators.siesta import Siesta
>>> from ase.units import Ry
>>>
>>> a0 = 5.43
>>> bulk = Atoms('Si2', [(0, 0, 0),
... (0.25, 0.25, 0.25)],
... pbc=True)
>>> b = a0 / 2
>>> bulk.set_cell([(0, b, b),
... (b, 0, b),
... (b, b, 0)], scale_atoms=True)
>>>
>>> calc = Siesta(label='Si',
... xc='PBE',
... mesh_cutoff=200 * Ry,
... energy_shift=0.01 * Ry,
... basis_set='DZ',
... kpts=[10, 10, 10],
... fdf_arguments={'DM.MixingWeight': 0.1,
... 'MaxSCFIterations': 100},
... )
>>> bulk.set_calculator(calc)
>>> e = bulk.get_potential_energy()
Here, the only input information on the basis set is, that it should
be double-zeta (basis='DZP') and that the confinement potential
should result in an energy shift of 0.01 Rydberg (the
energy_shift=0.01 * Ry keyword). Sometimes it can be necessary to specify
more information on the basis set.
Defining Custom Species¶
Standard basis sets can be set by the keyword basis_set directly, but for
anything more complex than one standard basis size for all elements,
a list of species must be defined. Each specie is identified by atomic
element and the tag set on the atom.
For instance if we wish to investigate a H2 molecule and put a ghost atom (the basis set corresponding to an atom but without the actual atom) in the middle with a special type of basis you would write:
>>> from ase.calculators.siesta.parameters import Specie, PAOBasisBlock
>>> from ase import Atoms
>>> from ase.calculators.siesta import Siesta
>>> atoms = Atoms(
... '3H',
... [(0.0, 0.0, 0.0),
... (0.0, 0.0, 0.5),
... (0.0, 0.0, 1.0)],
... cell=[10, 10, 10])
>>> atoms.set_tags([0, 1, 0])
>>>
>>> basis_set = PAOBasisBlock(
... """1
... 0 2 S 0.2
... 0.0 0.0""")
>>>
>>> siesta = Siesta(
... species=[
... Specie(symbol='H', tag=None, basis_set='SZ'),
... Specie(symbol='H', tag=1, basis_set=basis_set, ghost=True)])
>>>
>>> atoms.set_calculator(siesta)
When more species are defined, species defined with a tag has the highest priority.
General species with tag=None has a lower priority.
Finally, if no species apply
to an atom, the general calculator keywords are used.
Pseudopotentials¶
Pseudopotential files in the .psf or .vps formats are needed.
Pseudopotentials generated from the ABINIT code and converted to
the SIESTA format are available in the SIESTA website.
A database of user contributed pseudopotentials is also available there.
You can also find an on-line pseudopotential generator from the OCTOPUS code.
Species can also be used to specify pseudopotentials:
>>> specie = Specie(symbol='H', tag=1, pseudopotential='H.example.psf')
When specifying the pseudopotential in this manner, both absolute and relative paths can be given. Relative paths are considered relative to the default pseudopotential path.
Restarting from an old Calculation¶
If you want to rerun an old SIESTA calculation, whether made using the ASE
interface or not, you can set the keyword restart to the siesta .XV
file. The keyword ignore_bad_restart (True/False) will decide whether
a broken file will result in an error(False) or the whether the calculator
will simply continue without the restart file.
TDDFT Calculations¶
It is possible to run Time Dependent Density Functional Theory (TDDFT) using the PYSCF-NAO code together with the SIESTA code. This code allows to run TDDFT up to thousand atoms with small computational ressources. Visit the github webpage for further informations about PYSCF-NAO.
Example of code to calculate polarizability of Na8 cluster,:
from ase.units import Ry, eV, Ha
from ase.calculators.siesta import Siesta
from ase import Atoms
import numpy as np
import matplotlib.pyplot as plt
# Define the systems
Na8 = Atoms('Na8',
positions=[[-1.90503810, 1.56107288, 0.00000000],
[1.90503810, 1.56107288, 0.00000000],
[1.90503810, -1.56107288, 0.00000000],
[-1.90503810, -1.56107288, 0.00000000],
[0.00000000, 0.00000000, 2.08495836],
[0.00000000, 0.00000000, -2.08495836],
[0.00000000, 3.22798122, 2.08495836],
[0.00000000, 3.22798122, -2.08495836]],
cell=[20, 20, 20])
# Siesta input
siesta = Siesta(
mesh_cutoff=150 * Ry,
basis_set='DZP',
pseudo_qualifier='',
energy_shift=(10 * 10**-3) * eV,
fdf_arguments={
'SCFMustConverge': False,
'COOP.Write': True,
'WriteDenchar': True,
'PAO.BasisType': 'split',
'DM.Tolerance': 1e-4,
'DM.MixingWeight': 0.01,
'MaxSCFIterations': 300,
'DM.NumberPulay': 4,
'XML.Write': True})
Na8.set_calculator(siesta)
e = Na8.get_potential_energy()
freq, pol = siesta.get_polarizability_pyscf_inter(label="siesta",
jcutoff=7,
iter_broadening=0.15/Ha,
xc_code='LDA,PZ',
tol_loc=1e-6,
tol_biloc=1e-7,
freq = np.arange(0.0, 5.0, 0.05))
# plot polarizability
plt.plot(freq, pol[:, 0, 0].imag)
plt.show()
Remark:¶
The PYSCF-NAO code is still under active development and to have access to it with ASE you will need to use this PYSCF fork and use the branch nao. To summarize:
git clone https://github.com/cfm-mpc/pyscf
git fetch
git checkout nao
Then you can follow the instruction of the README. The installation is relatively easy, go to the lib directory:
cd pyscf/pyscf/lib
cp cmake_arch_config/cmake.arch.inc-your-config cmake.arch.inc
mkdir build
cd build
cmake ..
make
Then you need to add the pyscf directory to your PYTHONPATH
export PYTHONPATH=/PATH-TO-PYSCF/pyscf:$PYTHONPATH
Raman Calculations with SIESTA and PYSCF-NAO¶
It is possible to calulate the Raman spectra with SIESTA, PYSCF-NAO anf the vibration module from ASE. Example with CO2,:
from ase.units import Ry, eV, Ha
from ase.calculators.siesta import Siesta
from ase.calculators.siesta.siesta_raman import SiestaRaman
from ase import Atoms
import numpy as np
# Define the systems
# example of Raman calculation for CO2 molecule,
# comparison with QE calculation can be done from
# https://github.com/maxhutch/quantum-espresso/blob/master/PHonon/examples/example15/README
CO2 = Atoms('CO2',
positions=[[-0.009026, -0.020241, 0.026760],
[1.167544, 0.012723, 0.071808],
[-1.185592, -0.053316, -0.017945]],
cell=[20, 20, 20])
# enter siesta input
# To perform good vibrational calculations it is strongly advised
# to relax correctly the molecule geometry before to actually run the
# calculations. Then to use a large mesh_cutoff and to have the option
# PAO.SoftDefault turned on
siesta = Siesta(
mesh_cutoff=450 * Ry,
basis_set='DZP',
xc="GGA",
pseudo_qualifier='gga',
energy_shift=(10 * 10**-3) * eV,
fdf_arguments={
'SCFMustConverge': False,
'COOP.Write': True,
'WriteDenchar': True,
'PAO.BasisType': 'split',
"PAO.SoftDefault": True,
'DM.Tolerance': 1e-4,
'DM.MixingWeight': 0.01,
'MaxSCFIterations': 300,
'DM.NumberPulay': 4,
'XML.Write': True,
'DM.UseSaveDM': True})
CO2.set_calculator(siesta)
ram = SiestaRaman(CO2, siesta, nfree=4, label="siesta", jcutoff=7, iter_broadening=0.15/Ha,
xc_code='LDA,PZ', tol_loc=1e-6, tol_biloc=1e-7, freq = np.arange(0.0, 5.0, 0.05))
ram.run()
ram.summary(intensity_unit_ram='A^4 amu^-1')
ram.write_spectra(start=200, intensity_unit_ram='A^4 amu^-1')
Further Examples¶
See also ase/test/calculators/siesta/test_scripts for further examples
on how the calculator can be used.
Siesta Calculator Class¶
-
class
ase.calculators.siesta.base_siesta.BaseSiesta(command=None, **kwargs)[source]¶ Calculator interface to the SIESTA code.
ASE interface to the SIESTA code.
- Parameters
label (-) – The basename of all files created during SIESTA run.
mesh_cutoff (-) – Energy in eV. The mesh cutoff energy for determining number of grid points in the matrix-element calculation.
energy_shift (-) – Energy in eV The confining energy of the basis set generation.
kpts (-) – Tuple of 3 integers, the k-points in different directions.
xc (-) – The exchange-correlation potential. Can be set to any allowed value for either the Siesta XC.funtional or XC.authors keyword. Default “LDA”
basis_set (-) – “SZ”|”SZP”|”DZ”|”DZP”|”TZP”, strings which specify the type of functions basis set.
spin (-) – “UNPOLARIZED”|”COLLINEAR”|”FULL”. The level of spin description to be used.
species (-) – None|list of Species objects. The species objects can be used to to specify the basis set, pseudopotential and whether the species is ghost. The tag on the atoms object and the element is used together to identify the species.
pseudo_path (-) – None|path. This path is where pseudopotentials are taken from. If None is given, then then the path given in $SIESTA_PP_PATH will be used.
pseudo_qualifier (-) – None|string. This string will be added to the pseudopotential path that will be retrieved. For hydrogen with qualifier “abc” the pseudopotential “H.abc.psf” will be retrieved.
symlink_pseudos (-) – None|bool If true, symlink pseudopotentials into the calculation directory, else copy them. Defaults to true on Unix and false on Windows.
atoms (-) – The Atoms object.
restart (-) – str. Prefix for restart file. May contain a directory. Default is None, don’t restart.
siesta_default (-) – Use siesta default parameter if the parameter is not explicitly set.
ignore_bad_restart_file (-) – bool. Ignore broken or missing restart file. By default, it is an error if the restart file is missing or broken.
fdf_arguments (-) – Explicitly given fdf arguments. Dictonary using Siesta keywords as given in the manual. List values are written as fdf blocks with each element on a separate line, while tuples will write each element in a single line. ASE units are assumed in the input.
atomic_coord_format (-) – “xyz”|”zmatrix”, strings to switch between the default way of entering the system’s geometry (via the block AtomicCoordinatesAndAtomicSpecies) and a recent method via the block Zmatrix. The block Zmatrix allows to specify basic geometry constrains such as realized through the ASE classes FixAtom, FixedLine and FixedPlane.