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advanced example in docs corrected
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@ -16,20 +16,21 @@ First, we load the necessary modules::
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Then we define some parameters::
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lda_filename='srvo3'
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U = 4.0
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U = 2.7
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J = 0.65
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beta = 40
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loops = 10 # Number of DMFT sc-loops
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mix = 1.0 # Mixing factor of Sigma after solution of the AIM
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loops = 1 # Number of DMFT sc-loops
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mix = 0.8 # Mixing factor of Sigma after solution of the AIM
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Delta_mix = 1.0 # Mixing factor of Delta as input for the AIM
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dc_type = 1 # DC type: 0 FLL, 1 Held, 2 AMF
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use_blocks = True # use bloc structure from LDA input
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use_matrix = False # True: Slater parameters, False: Kanamori parameters U, U-2J, U-3J
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use_matrix = False # True: Slater parameters, False: Kanamori parameters U+2J, U, U-J
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use_spinflip = False # use the full rotational invariant interaction?
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prec_mu = 0.0001
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qmc_cycles = 20000
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qmc_cycles = 200000
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length_cycle = 200
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warming_iterations = 2000
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warming_iterations = 10000
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Most of these parameters are self-explaining. The first, `lda_filename`, gives the filename of the input files.
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The next step, as described in the previous section, is to convert the input files::
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@ -98,37 +99,33 @@ previous section, with some additional refinement::
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SK.set_dc( dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
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S.Sigma <<= SK.dc_imp[0]['up'][0,0]
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# now calculate new G0:
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if (mpi.is_master_node()):
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# We can do a mixing of Delta in order to stabilize the DMFT iterations:
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S.G0 <<= S.Sigma + inverse(S.G)
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ar = HDFArchive(lda_filename+'.h5','a')
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if ((iteration_number>1) or (previous_present)):
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mpi.report("Mixing input Delta with factor %s"%Delta_mix)
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Delta = (Delta_mix * S.G0.delta()) + (1.0-Delta_mix) * ar['DeltaF']
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S.G0 <<= S.G0 + S.G0.delta() - Delta
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ar['DeltaF'] = S.G0.delta()
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S.G0 <<= inverse(S.G0)
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del ar
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S.G0 = mpi.bcast(S.G0)
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S.G0 <<= inverse(S.Sigma + inverse(S.G))
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# Solve the impurity problem:
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S.Solve(U_interact=U,J_hund=J,n_orb=Norb,use_matrix=use_matrix,
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T=SK.T[0], gf_struct=SK.gf_struct_solver[0],map=SK.map[0],
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l=l, deg_orbs=SK.deg_shells[0], use_spinflip=use_spinflip,
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n_cycles =qmc_cycles,length_cycle=length_cycle,n_warmup_cycles=warming_iterations)
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S.solve(U_interact=U,J_hund=J,use_spinflip=use_spinflip,use_matrix=use_matrix,
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l=l,T=SK.T[0], dim_reps=SK.dim_reps[0], irep=2, deg_orbs=SK.deg_shells[0],n_cycles =qmc_cycles,
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length_cycle=length_cycle,n_warmup_cycles=warming_iterations)
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# solution done, do the post-processing:
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mpi.report("Total charge of impurity problem : %.6f"%S.G.total_density())
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S.Sigma <<=(inverse(S.G0)-inverse(S.G))
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# Solve the impurity problem:
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S.solve(U_interact=U,J_hund=J,use_spinflip=use_spinflip,use_matrix=use_matrix,
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l=l,T=SK.T[0], dim_reps=SK.dim_reps[0], irep=2, deg_orbs=SK.deg_shells[0],n_cycles =qmc_cycles,
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length_cycle=length_cycle,n_warmup_cycles=warming_iterations)
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# solution done, do the post-processing:
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mpi.report("Total charge of impurity problem : %.6f"%S.G.total_density())
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S.Sigma <<=(inverse(S.G0)-inverse(S.G))
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# Now mix Sigma and G with factor Mix, if wanted:
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if ((iteratio_number>1) or (previous_present)):
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if ((iteration_number>1) or (previous_present)):
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if (mpi.is_master_node()):
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ar = HDFArchive(lda_filename+'.h5','a')
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mpi.report("Mixing Sigma and G with factor %s"%mix)
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S.Sigma <<= mix * S.Sigma + (1.0-mix) * ar['SigmaF']
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S.Sigma <<= mix * S.Sigma + (1.0-mix) * ar['Sigma']
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S.G <<= mix * S.G + (1.0-mix) * ar['GF']
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del ar
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S.G = mpi.bcast(S.G)
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@ -138,10 +135,10 @@ previous section, with some additional refinement::
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if (mpi.is_master_node()):
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ar = HDFArchive(lda_filename+'.h5','a')
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ar['iterations'] = previous_runs + iteration_number
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ar['SigmaF'] = S.Sigma
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ar['Sigma'] = S.Sigma
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ar['GF'] = S.G
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del ar
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save_Gf(S.Sigma,'Sigma')
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# Now set new double counting:
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dm = S.G.density()
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SK.set_dc( dm, U_interact = U, J_hund = J, orb = 0, use_dc_formula = dc_type)
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