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Code Issues Releases Wiki Activity

[doc] backport some of the changes from 3c2821f to address issue #270

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the-hampel 2025-04-15 09:28:05 +02:00
parent 4b018a25f3
commit 864267ef8a
4 changed files with 111 additions and 118 deletions
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10
doc/tutorials/nio_csc_vasp/NiO_local_lattice_GF.py
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@ -13,17 +13,11 @@ warnings.filterwarnings("ignore", category=FutureWarning)
filename = 'vasp' filename = 'vasp'
beta = 5.0 beta = 5.0
mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=1000) mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=500)
SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False, mesh=mesh) SK = SumkDFT(hdf_file = filename+'.h5', use_dft_blocks = False, mesh=mesh)
# We analyze the block structure of the Hamiltonian
Sigma = SK.block_structure.create_gf(mesh=mesh)
SK.put_Sigma([Sigma])
# Setup CTQMC Solver # Setup CTQMC Solver
n_orb = SK.corr_shells[0]['dim'] n_orb = SK.corr_shells[0]['dim']
spin_names = ['up','down'] spin_names = ['up','down']
@ -56,7 +50,7 @@ SK.chemical_potential = mpi.bcast(SK.chemical_potential)
if block_structure: if block_structure:
SK.block_structure = block_structure SK.block_structure = block_structure
else: else:
G = SK.extract_G_loc() G = SK.extract_G_loc(transform_to_solver_blocks=False, with_Sigma=False)
SK.analyse_block_structure_from_gf(G, threshold = 1e-3) SK.analyse_block_structure_from_gf(G, threshold = 1e-3)
SK.put_Sigma(Sigma_imp = [Sigma_iw]) SK.put_Sigma(Sigma_imp = [Sigma_iw])

2
doc/tutorials/nio_csc_vasp/maxent.py
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@ -29,7 +29,7 @@ for orb in orbs:
gf = gf + G_latt['up'][iO,iO] gf = gf + G_latt['up'][iO,iO]
tm.set_G_iw(gf) tm.set_G_iw(gf)
tm.omega =LinearOmegaMesh(omega_min=-20, omega_max=20, n_points=201) tm.omega =LinearOmegaMesh(omega_min=-20, omega_max=20, n_points=201)
tm.alpha_mesh = LogAlphaMesh(alpha_min=0.01, alpha_max=20000, n_points=60) tm.alpha_mesh = LogAlphaMesh(alpha_min=0.01, alpha_max=20000, n_points=30)
tm.set_error(1.e-3) tm.set_error(1.e-3)
result=tm.run() result=tm.run()

106
doc/tutorials/nio_csc_vasp/nio.py
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@ -1,7 +1,6 @@
from itertools import * from itertools import *
import numpy as np
import triqs.utility.mpi as mpi import triqs.utility.mpi as mpi
from h5 import * from h5 import HDFArchive
from triqs.gf import * from triqs.gf import *
import sys, triqs.version as triqs_version import sys, triqs.version as triqs_version
from triqs_dft_tools.sumk_dft import * from triqs_dft_tools.sumk_dft import *
@ -18,14 +17,11 @@ warnings.filterwarnings("ignore", category=FutureWarning)
filename = 'vasp' filename = 'vasp'
beta = 5.0 beta = 5.0
mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=1000) mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=500)
SK = SumkDFT(hdf_file=filename+'.h5', use_dft_blocks=False, mesh=mesh) SK = SumkDFT(hdf_file=filename+'.h5', use_dft_blocks=False, mesh=mesh)
G = SK.extract_G_loc(transform_to_solver_blocks=False, with_Sigma=False)
Sigma = SK.block_structure.create_gf(mesh=mesh)
SK.put_Sigma([Sigma])
G = SK.extract_G_loc()
SK.analyse_block_structure_from_gf(G, threshold=1e-3) SK.analyse_block_structure_from_gf(G, threshold=1e-3)
for i_sh in range(len(SK.deg_shells)): for i_sh in range(len(SK.deg_shells)):
num_block_deg_orbs = len(SK.deg_shells[i_sh]) num_block_deg_orbs = len(SK.deg_shells[i_sh])
@ -46,7 +42,7 @@ mpi.report('Sumk to Solver: %s' % SK.sumk_to_solver)
mpi.report('GF struct sumk: %s' % SK.gf_struct_sumk) mpi.report('GF struct sumk: %s' % SK.gf_struct_sumk)
mpi.report('GF struct solver: %s' % SK.gf_struct_solver) mpi.report('GF struct solver: %s' % SK.gf_struct_solver)
S = Solver(beta=beta, gf_struct=gf_struct, n_iw=1000) S = Solver(beta=beta, gf_struct=gf_struct, n_iw=500)
# Construct the Hamiltonian and save it in Hamiltonian_store.txt # Construct the Hamiltonian and save it in Hamiltonian_store.txt
H = Operator() H = Operator()
@ -70,14 +66,15 @@ mpi.report('Up Matrix set to:\n%s' % Upmat)
p = {} p = {}
p["max_time"] = -1 p["max_time"] = -1
p["random_name"] = "" p["random_name"] = ""
p["random_seed"] = 123 * mpi.rank + 567 p["length_cycle"] = 400
p["length_cycle"] = 100 p["n_warmup_cycles"] = 2000
p["n_warmup_cycles"] = 8000 p["n_cycles"] = 80000
p["n_cycles"] = 200000
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_w"] = 20
p["fit_max_n"] = 50 p["fit_max_w"] = 30
p["perform_tail_fit"] = True p["perform_tail_fit"] = True
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
# Double Counting: 0 FLL, 1 Held, 2 AMF # Double Counting: 0 FLL, 1 Held, 2 AMF
DC_type = 0 DC_type = 0
@ -88,32 +85,33 @@ n_iterations = 10
iteration_offset = 0 iteration_offset = 0
if mpi.is_master_node(): if mpi.is_master_node():
ar = HDFArchive(filename+'.h5', 'a') with HDFArchive(filename+'.h5', 'a') as ar:
if not 'DMFT_results' in ar: if 'DMFT_results' not in ar:
ar.create_group('DMFT_results') ar.create_group('DMFT_results')
if not 'Iterations' in ar['DMFT_results']: if 'Iterations' not in ar['DMFT_results']:
ar['DMFT_results'].create_group('Iterations') ar['DMFT_results'].create_group('Iterations')
if not 'DMFT_input' in ar: if 'DMFT_input' not in ar:
ar.create_group('DMFT_input') ar.create_group('DMFT_input')
if not 'Iterations' in ar['DMFT_input']: if 'Iterations' not in ar['DMFT_input']:
ar['DMFT_input'].create_group('Iterations') ar['DMFT_input'].create_group('Iterations')
if not 'code_versions' in ar['DMFT_input']: if 'code_versions' not in ar['DMFT_input']:
ar['DMFT_input'].create_group('code_versions') ar['DMFT_input'].create_group('code_versions')
ar['DMFT_input']['code_versions']["triqs_version"] = triqs_version.version ar['DMFT_input']['code_versions']["triqs_version"] = triqs_version.version
ar['DMFT_input']['code_versions']["triqs_git"] = triqs_version.git_hash ar['DMFT_input']['code_versions']["triqs_git"] = triqs_version.git_hash
ar['DMFT_input']['code_versions']["cthyb_version"] = cthyb_version.version ar['DMFT_input']['code_versions']["cthyb_version"] = cthyb_version.version
ar['DMFT_input']['code_versions']["cthyb_git"] = cthyb_version.triqs_cthyb_hash ar['DMFT_input']['code_versions']["cthyb_git"] = cthyb_version.triqs_cthyb_hash
ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.version ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.version
ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.triqs_dft_tools_hash ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.triqs_dft_tools_hash
ar['DMFT_input']['sumk_block_structure'] = SK.block_structure ar['DMFT_input']['sumk_block_structure'] = SK.block_structure
if 'iteration_count' in ar['DMFT_results']: if 'iteration_count' in ar['DMFT_results']:
iteration_offset = ar['DMFT_results']['iteration_count']+1 iteration_offset = ar['DMFT_results']['iteration_count']+1
S.Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)] S.Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)]
SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)] SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)]
SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)] SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)]
SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential' + SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential' +
str(iteration_offset-1)].real str(iteration_offset-1)].real
ar['DMFT_input']["dmft_script_it"+str(iteration_offset)] = open(sys.argv[0]).read() ar['DMFT_input']["dmft_script_it"+str(iteration_offset)] = open(sys.argv[0]).read()
iteration_offset = mpi.bcast(iteration_offset) iteration_offset = mpi.bcast(iteration_offset)
S.Sigma_iw = mpi.bcast(S.Sigma_iw) S.Sigma_iw = mpi.bcast(S.Sigma_iw)
SK.dc_imp = mpi.bcast(SK.dc_imp) SK.dc_imp = mpi.bcast(SK.dc_imp)
@ -146,10 +144,11 @@ for it in range(iteration_offset, iteration_offset + n_iterations):
# Solve the impurity problem # Solve the impurity problem
S.solve(h_int=H, **p) S.solve(h_int=H, **p)
if mpi.is_master_node(): if mpi.is_master_node():
ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p with HDFArchive(filename+'.h5', 'a') as ar:
ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p
ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw
ar['DMFT_results']['Iterations']['Sigma_uns_it'+str(it)] = S.Sigma_iw ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau
ar['DMFT_results']['Iterations']['Sigma_uns_it'+str(it)] = S.Sigma_iw
# Calculate double counting # Calculate double counting
dm = S.G_iw.density() dm = S.G_iw.density()
SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type, use_dc_value=DC_value) SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type, use_dc_value=DC_value)
@ -165,13 +164,14 @@ for it in range(iteration_offset, iteration_offset + n_iterations):
mpi.report('Total charge of Gloc : %.6f' % S.G_iw.total_density()) mpi.report('Total charge of Gloc : %.6f' % S.G_iw.total_density())
if mpi.is_master_node(): if mpi.is_master_node():
ar['DMFT_results']['iteration_count'] = it with HDFArchive(filename+'.h5', 'a') as ar:
ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw ar['DMFT_results']['iteration_count'] = it
ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw
ar['DMFT_results']['Iterations']['G0loc_it'+str(it)] = S.G0_iw ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw
ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp ar['DMFT_results']['Iterations']['G0loc_it'+str(it)] = S.G0_iw
ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp
ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ
ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential
mpi.report('-------------')
if mpi.is_master_node():
del ar

109
doc/tutorials/nio_csc_vasp/nio_csc.py
View File

@ -1,7 +1,6 @@
from itertools import * from itertools import *
import numpy as np
import triqs.utility.mpi as mpi import triqs.utility.mpi as mpi
from h5 import * from h5 import HDFArchive
from triqs.gf import * from triqs.gf import *
import sys, triqs.version as triqs_version import sys, triqs.version as triqs_version
from triqs_dft_tools.sumk_dft import * from triqs_dft_tools.sumk_dft import *
@ -25,13 +24,11 @@ def dmft_cycle():
Converter.convert_dft_input() Converter.convert_dft_input()
beta = 5.0 beta = 5.0
mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=1000) mesh = MeshImFreq(beta=beta, S='Fermion', n_iw=500)
SK = SumkDFT(hdf_file=filename+'.h5', use_dft_blocks=False, mesh=mesh) SK = SumkDFT(hdf_file=filename+'.h5', use_dft_blocks=False, mesh=mesh)
Sigma = SK.block_structure.create_gf(mesh=mesh) G = SK.extract_G_loc(transform_to_solver_blocks=False, with_Sigma=False)
SK.put_Sigma([Sigma])
G = SK.extract_G_loc()
SK.analyse_block_structure_from_gf(G, threshold=1e-2) SK.analyse_block_structure_from_gf(G, threshold=1e-2)
for i_sh in range(len(SK.deg_shells)): for i_sh in range(len(SK.deg_shells)):
num_block_deg_orbs = len(SK.deg_shells[i_sh]) num_block_deg_orbs = len(SK.deg_shells[i_sh])
@ -52,7 +49,7 @@ def dmft_cycle():
mpi.report('GF struct sumk: %s' % SK.gf_struct_sumk) mpi.report('GF struct sumk: %s' % SK.gf_struct_sumk)
mpi.report('GF struct solver: %s' % SK.gf_struct_solver) mpi.report('GF struct solver: %s' % SK.gf_struct_solver)
S = Solver(beta=beta, gf_struct=gf_struct, n_iw=1000) S = Solver(beta=beta, gf_struct=gf_struct, n_iw=500)
# Construct the Hamiltonian and save it in Hamiltonian_store.txt # Construct the Hamiltonian and save it in Hamiltonian_store.txt
H = Operator() H = Operator()
@ -75,14 +72,16 @@ def dmft_cycle():
p = {} p = {}
p["max_time"] = -1 p["max_time"] = -1
p["random_name"] = "" p["random_name"] = ""
p["random_seed"] = 123 * mpi.rank + 567 p["length_cycle"] = 400
p["length_cycle"] = 100
p["n_warmup_cycles"] = 2000 p["n_warmup_cycles"] = 2000
p["n_cycles"] = 20000 p["n_cycles"] = 80000
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_w"] = 20
p["fit_max_n"] = 50 p["fit_max_w"] = 30
p["perform_tail_fit"] = True p["perform_tail_fit"] = True
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
# Double Counting: 0 FLL, 1 Held, 2 AMF # Double Counting: 0 FLL, 1 Held, 2 AMF
DC_type = 0 DC_type = 0
@ -93,32 +92,32 @@ def dmft_cycle():
iteration_offset = 0 iteration_offset = 0
if mpi.is_master_node(): if mpi.is_master_node():
ar = HDFArchive(filename+'.h5', 'a') with HDFArchive(filename+'.h5', 'a') as ar:
if not 'DMFT_results' in ar: if 'DMFT_results' not in ar:
ar.create_group('DMFT_results') ar.create_group('DMFT_results')
if not 'Iterations' in ar['DMFT_results']: if 'Iterations' not in ar['DMFT_results']:
ar['DMFT_results'].create_group('Iterations') ar['DMFT_results'].create_group('Iterations')
if not 'DMFT_input' in ar: if 'DMFT_input' not in ar:
ar.create_group('DMFT_input') ar.create_group('DMFT_input')
if not 'Iterations' in ar['DMFT_input']: if 'Iterations' not in ar['DMFT_input']:
ar['DMFT_input'].create_group('Iterations') ar['DMFT_input'].create_group('Iterations')
if not 'code_versions' in ar['DMFT_input']: if not 'code_versions' not in ar['DMFT_input']:
ar['DMFT_input'].create_group('code_versions') ar['DMFT_input'].create_group('code_versions')
ar['DMFT_input']['code_versions']["triqs_version"] = triqs_version.version ar['DMFT_input']['code_versions']["triqs_version"] = triqs_version.version
ar['DMFT_input']['code_versions']["triqs_git"] = triqs_version.git_hash ar['DMFT_input']['code_versions']["triqs_git"] = triqs_version.git_hash
ar['DMFT_input']['code_versions']["cthyb_version"] = cthyb_version.version ar['DMFT_input']['code_versions']["cthyb_version"] = cthyb_version.version
ar['DMFT_input']['code_versions']["cthyb_git"] = cthyb_version.triqs_cthyb_hash ar['DMFT_input']['code_versions']["cthyb_git"] = cthyb_version.triqs_cthyb_hash
ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.version ar['DMFT_input']['code_versions']["dft_tools_version"] = dft_tools_version.version
ar['DMFT_input']['code_versions']["dft_tools_git"] = dft_tools_version.triqs_dft_tools_hash ar['DMFT_input']['code_versions']["dft_tools_git"] = dft_tools_version.triqs_dft_tools_hash
ar['DMFT_input']['sumk_block_structure'] = SK.block_structure ar['DMFT_input']['sumk_block_structure'] = SK.block_structure
if 'iteration_count' in ar['DMFT_results']: if 'iteration_count' in ar['DMFT_results']:
iteration_offset = ar['DMFT_results']['iteration_count']+1 iteration_offset = ar['DMFT_results']['iteration_count']+1
S.Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)] S.Sigma_iw = ar['DMFT_results']['Iterations']['Sigma_it'+str(iteration_offset-1)]
SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)] SK.dc_imp = ar['DMFT_results']['Iterations']['dc_imp'+str(iteration_offset-1)]
SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)] SK.dc_energ = ar['DMFT_results']['Iterations']['dc_energ'+str(iteration_offset-1)]
SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential' + SK.chemical_potential = ar['DMFT_results']['Iterations']['chemical_potential' +
str(iteration_offset-1)].real str(iteration_offset-1)].real
ar['DMFT_input']["dmft_script_it"+str(iteration_offset)] = open(sys.argv[0]).read() ar['DMFT_input']["dmft_script_it"+str(iteration_offset)] = open(sys.argv[0]).read()
iteration_offset = mpi.bcast(iteration_offset) iteration_offset = mpi.bcast(iteration_offset)
S.Sigma_iw = mpi.bcast(S.Sigma_iw) S.Sigma_iw = mpi.bcast(S.Sigma_iw)
SK.dc_imp = mpi.bcast(SK.dc_imp) SK.dc_imp = mpi.bcast(SK.dc_imp)
@ -151,10 +150,11 @@ def dmft_cycle():
# Solve the impurity problem # Solve the impurity problem
S.solve(h_int=H, **p) S.solve(h_int=H, **p)
if mpi.is_master_node(): if mpi.is_master_node():
ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p with HDFArchive(filename+'.h5', 'a') as ar:
ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw ar['DMFT_input']['Iterations']['solver_dict_it'+str(it)] = p
ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau ar['DMFT_results']['Iterations']['Gimp_it'+str(it)] = S.G_iw
ar['DMFT_results']['Iterations']['Sigma_uns_it'+str(it)] = S.Sigma_iw ar['DMFT_results']['Iterations']['Gtau_it'+str(it)] = S.G_tau
ar['DMFT_results']['Iterations']['Sigma_uns_it'+str(it)] = S.Sigma_iw
# Calculate double counting # Calculate double counting
dm = S.G_iw.density() dm = S.G_iw.density()
SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0,
@ -171,20 +171,21 @@ def dmft_cycle():
mpi.report('Total charge of Gloc : %.6f' % S.G_iw.total_density().real) mpi.report('Total charge of Gloc : %.6f' % S.G_iw.total_density().real)
if mpi.is_master_node(): if mpi.is_master_node():
ar['DMFT_results']['iteration_count'] = it with HDFArchive(filename+'.h5', 'a') as ar:
ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw ar['DMFT_results']['iteration_count'] = it
ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw ar['DMFT_results']['Iterations']['Sigma_it'+str(it)] = S.Sigma_iw
ar['DMFT_results']['Iterations']['G0loc_it'+str(it)] = S.G0_iw ar['DMFT_results']['Iterations']['Gloc_it'+str(it)] = S.G_iw
ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp ar['DMFT_results']['Iterations']['G0loc_it'+str(it)] = S.G0_iw
ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ ar['DMFT_results']['Iterations']['dc_imp'+str(it)] = SK.dc_imp
ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential ar['DMFT_results']['Iterations']['dc_energ'+str(it)] = SK.dc_energ
ar['DMFT_results']['Iterations']['chemical_potential'+str(it)] = SK.chemical_potential
if mpi.is_master_node(): if mpi.is_master_node():
print('calculating mu...') print('calculating mu...')
SK.chemical_potential = SK.calc_mu(precision=0.000001) SK.chemical_potential = SK.calc_mu(precision=0.000001)
if mpi.is_master_node(): if mpi.is_master_node():
print('calculating GAMMA') print('calculating charge density update')
SK.calc_density_correction(dm_type='vasp') SK.calc_density_correction(dm_type='vasp')
if mpi.is_master_node(): if mpi.is_master_node():
@ -196,10 +197,8 @@ def dmft_cycle():
SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type, use_dc_value=DC_value) SK.calc_dc(dm, U_interact=U, J_hund=J, orb=0, use_dc_formula=DC_type, use_dc_value=DC_value)
if mpi.is_master_node(): if mpi.is_master_node():
ar['DMFT_results']['Iterations']['corr_energy_it'+str(it)] = correnerg with HDFArchive(filename+'.h5', 'a') as ar:
ar['DMFT_results']['Iterations']['dc_energy_it'+str(it)] = SK.dc_energ[0] ar['DMFT_results']['Iterations']['corr_energy_it'+str(it)] = correnerg
ar['DMFT_results']['Iterations']['dc_energy_it'+str(it)] = SK.dc_energ[0]
if mpi.is_master_node():
del ar
return correnerg, SK return correnerg, SK