Source code for dmft_tools.afm_mapping

# -*- coding: utf-8 -*-
################################################################################
#
# solid_dmft - A versatile python wrapper to perform DFT+DMFT calculations
#              utilizing the TRIQS software library
#
# Copyright (C) 2018-2020, ETH Zurich
# Copyright (C) 2021, The Simons Foundation
#      authors: A. Hampel, M. Merkel, and S. Beck
#
# solid_dmft is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# solid_dmft is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE. See the GNU General Public License for more details.

# You should have received a copy of the GNU General Public License along with
# solid_dmft (in the file COPYING.txt in this directory). If not, see
# <http://www.gnu.org/licenses/>.
#
################################################################################

import numpy as np
from h5 import HDFArchive
import triqs.utility.mpi as mpi

[docs] def determine(general_params, archive, n_inequiv_shells): """ Determines the symmetries that are used in AFM calculations. These symmetries can then be used to copy the self-energies from one impurity to another by exchanging up/down channels for speedup and accuracy. """ afm_mapping = None if mpi.is_master_node(): # Reads mapping from h5 archive if it exists already from a previous run with HDFArchive(archive, 'a') as ar: if 'afm_mapping' in ar['DMFT_input']: afm_mapping = ar['DMFT_input']['afm_mapping'] elif len(general_params['magmom']) == n_inequiv_shells: # find equal or opposite spin imps, where we use the magmom array to # identity those with equal numbers or opposite # [copy Yes/False, from where, switch up/down channel] afm_mapping = [None] * n_inequiv_shells abs_moms = np.abs(general_params['magmom']) for icrsh in range(n_inequiv_shells): # if the moment was seen before ... previous_occurences = np.nonzero(np.isclose(abs_moms[:icrsh], abs_moms[icrsh]))[0] if previous_occurences.size > 0: # find the source imp to copy from source = np.min(previous_occurences) # determine if we need to switch up and down channel switch = np.isclose(general_params['magmom'][icrsh], -general_params['magmom'][source]) afm_mapping[icrsh] = [True, source, switch] else: afm_mapping[icrsh] = [False, icrsh, False] print('AFM calculation selected, mapping self energies as follows:') print('imp [copy sigma, source imp, switch up/down]') print('---------------------------------------------') for i, elem in enumerate(afm_mapping): print('{}: {}'.format(i, elem)) print('') ar['DMFT_input']['afm_mapping'] = afm_mapping # if anything did not work set afm_order false else: print('WARNING: couldn\'t determine afm mapping. No mapping used.') general_params['afm_order'] = False general_params['afm_order'] = mpi.bcast(general_params['afm_order']) if general_params['afm_order']: general_params['afm_mapping'] = mpi.bcast(afm_mapping) return general_params
def apply(general_params, icrsh, gf_struct_solver, solvers): imp_source = general_params['afm_mapping'][icrsh][1] invert_spin = general_params['afm_mapping'][icrsh][2] mpi.report('\ncopying the self-energy for shell {} from shell {}'.format(icrsh, imp_source)) mpi.report('inverting spin channels: '+str(invert_spin)) if invert_spin: for spin_channel in gf_struct_solver.keys(): if 'up' in spin_channel: target_channel = spin_channel.replace('up', 'down') else: target_channel = spin_channel.replace('down', 'up') solvers[icrsh].Sigma_freq[spin_channel] << solvers[imp_source].Sigma_freq[target_channel] solvers[icrsh].G_freq[spin_channel] << solvers[imp_source].G_freq[target_channel] solvers[icrsh].G_freq_unsym[spin_channel] << solvers[imp_source].G_freq_unsym[target_channel] solvers[icrsh].G0_freq[spin_channel] << solvers[imp_source].G0_freq[target_channel] solvers[icrsh].G_time[spin_channel] << solvers[imp_source].G_time[target_channel] if solvers[icrsh].solver_params['measure_pert_order']: if not hasattr(solvers[icrsh], 'perturbation_order'): solvers[icrsh].perturbation_order = {} solvers[icrsh].perturbation_order[spin_channel] = solvers[imp_source].perturbation_order[target_channel] solvers[icrsh].perturbation_order_total = solvers[imp_source].perturbation_order_total else: solvers[icrsh].Sigma_freq << solvers[imp_source].Sigma_freq solvers[icrsh].G_freq << solvers[imp_source].G_freq solvers[icrsh].G_freq_unsym << solvers[imp_source].G_freq_unsym solvers[icrsh].G0_freq << solvers[imp_source].G0_freq solvers[icrsh].G_time << solvers[imp_source].G_time if solvers[icrsh].solver_params['measure_pert_order']: solvers[icrsh].perturbation_order = solvers[imp_source].perturbation_order solvers[icrsh].perturbation_order_total = solvers[imp_source].perturbation_order_total if solvers[icrsh].solver_params['measure_density_matrix']: solvers[icrsh].density_matrix = solvers[imp_source].density_matrix solvers[icrsh].h_loc_diagonalization = solvers[imp_source].h_loc_diagonalization if 'measure_chi' in solvers[icrsh].solver_params and solvers[icrsh].solver_params['measure_chi'] is not None: solvers[icrsh].O_time = solvers[imp_source].O_time return solvers