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GWR flow with convergence studies
This script shows how to compute the G0W0 corrections in silicon. More specifically, we build a flow to analyze the convergence of the QP corrections wrt to the number of bands in the self-energy. More complicated convergence studies can be implemented on the basis of this example.
import os
import sys
import abipy.data as data
import abipy.abilab as abilab
from abipy import flowtk
def build_flow(options):
# Working directory (default is the name of the script with '.py' removed and "run_" replaced by "flow_")
if not options.workdir:
options.workdir = os.path.basename(sys.argv[0]).replace(".py", "").replace("run_","flow_")
#from abipy.flowtk.psrepos import get_repo_from_name
#pseudos = get_repo_from_name("ONCVPSP-PBE-SR-PDv0.4").get_pseudos("stringent")
scf_input = abilab.AbinitInput(structure=data.cif_file("si.cif"),
pseudos=data.pseudos("14si.pspnc"))
# Global variables.
scf_input.set_vars(
ecut=6,
tolvrs=1e-8,
nband=4,
paral_kgb=1,
)
scf_input.set_kmesh(
ngkpt=[2, 2, 2],
shiftk=[0.0, 0.0, 0.0], # IMPORTANT: k-grid for GWR must be Gamma-centered.
)
flow = flowtk.Flow(workdir=options.workdir)
# GS-SCF run to get the DEN, followed by direct diago to obtain green_nband bands.
from abipy.flowtk.gwr_works import DirectDiagoWork, GWRSigmaConvWork
green_nband = -1 # -1 this means full diago
diago_work = DirectDiagoWork.from_scf_input(scf_input, green_nband)
flow.register_work(diago_work)
# Build template for GWR.
gwr_template = scf_input.make_gwr_qprange_input(gwr_ntau=6, nband=8, ecuteps=4)
# Two possibilities:
# 1) Change the value of one variable:
varname_values = ("nband", [8, 12, 14])
# or take the Cartesian product of two or more variables with e.g.:
#
#varname_values = [
# ("gwr_ntau", [6, 8]),
# ("ecuteps", [2, 4]),
#]
gwr_work = GWRSigmaConvWork.from_varname_values(
varname_values, gwr_template, den_node=diago_work[0], wfk_node=diago_work[1])
flow.register_work(gwr_work)
return flow
# This block generates the thumbnails in the AbiPy gallery.
# You can safely REMOVE this part if you are using this script for production runs.
if os.getenv("READTHEDOCS", False):
__name__ = None
import tempfile
options = flowtk.build_flow_main_parser().parse_args(["-w", tempfile.mkdtemp()])
build_flow(options).graphviz_imshow()
@flowtk.flow_main
def main(options):
return build_flow(options)
if __name__ == "__main__":
sys.exit(main())
Total running time of the script: (0 minutes 0.346 seconds)