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[doc] add measure_density_matrix to all cthyb tutorial using tail_fit

This commit is contained in:
the-hampel 2025-04-16 09:33:27 +02:00
parent b9ed39d59a
commit bb9567aa64
9 changed files with 35 additions and 8 deletions

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@ -49,6 +49,9 @@ p["perform_tail_fit"] = True
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_w"] = 4.0 p["fit_min_w"] = 4.0
p["fit_max_w"] = 8.0 p["fit_max_w"] = 8.0
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
# double counting correction: # double counting correction:
dc_type = 0 # FLL dc_type = 0 # FLL

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@ -52,6 +52,9 @@ p["perform_tail_fit"] = True
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_n"] = 30
p["fit_max_n"] = 70 p["fit_max_n"] = 70
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
# double counting correction: # double counting correction:
dc_type = 0 # FLL dc_type = 0 # FLL

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@ -43,6 +43,9 @@ p["perform_tail_fit"] = True
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_n"] = 30
p["fit_max_n"] = 60 p["fit_max_n"] = 60
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
# If conversion step was not done, we could do it here. Uncomment the lines it you want to do this. # If conversion step was not done, we could do it here. Uncomment the lines it you want to do this.
#from triqs_dft_tools.converters.wien2k import * #from triqs_dft_tools.converters.wien2k import *

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@ -73,6 +73,9 @@ p["fit_max_moment"] = 4
p["fit_min_w"] = 20 p["fit_min_w"] = 20
p["fit_max_w"] = 30 p["fit_max_w"] = 30
p["perform_tail_fit"] = True p["perform_tail_fit"] = True
# measure impurity density matrix to get self-energy moments for improved tail fit
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

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@ -79,6 +79,9 @@ def dmft_cycle():
p["fit_min_w"] = 20 p["fit_min_w"] = 20
p["fit_max_w"] = 30 p["fit_max_w"] = 30
p["perform_tail_fit"] = True p["perform_tail_fit"] = True
# measure impurity density matrix to get self-energy moments for improved tail fit
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

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@ -158,6 +158,9 @@ Now we have the interaction Hamiltonian for the solver, which we set up next::
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 40 p["fit_min_n"] = 40
p["fit_max_n"] = 100 p["fit_max_n"] = 100
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
The DMFT loop with automatic basis rotations The DMFT loop with automatic basis rotations

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@ -156,6 +156,9 @@ Now we have the interaction Hamiltonian for the solver, which we set up next::
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_w"] = 4.0 p["fit_min_w"] = 4.0
p["fit_max_w"] = 8.0 p["fit_max_w"] = 8.0
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
The DMFT loop with automatic basis rotations The DMFT loop with automatic basis rotations

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@ -124,6 +124,9 @@ of parameters for a first guess is::
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_n"] = 30
p["fit_max_n"] = 60 p["fit_max_n"] = 60
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
Here we use a tail fit to deal with numerical noise of higher Matsubara frequencies. Here we use a tail fit to deal with numerical noise of higher Matsubara frequencies.
For other options and more details on the solver parameters, we refer the user to For other options and more details on the solver parameters, we refer the user to

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@ -85,6 +85,9 @@ We also have to specify the `CTHYB solver <https://triqs.github.io/cthyb/latest>
p["fit_max_moment"] = 4 p["fit_max_moment"] = 4
p["fit_min_n"] = 30 p["fit_min_n"] = 30
p["fit_max_n"] = 60 p["fit_max_n"] = 60
# measure impurity density matrix to get self-energy moments for improved tail fit
p["measure_density_matrix"] = True
p["use_norm_as_weight"] = True
Here we use a tail fit to deal with numerical noise of higher Matsubara frequencies. For other options and more details on the solver parameters, we refer to the `CTHYB solver <https://triqs.github.io/cthyb/latest/reference/constr_parameters.html>`_ documentation. It is important to note that the solver parameters have to be adjusted for each material individually. A guide on how to set the tail fit parameters is given :ref:`below <tailfit>`. Here we use a tail fit to deal with numerical noise of higher Matsubara frequencies. For other options and more details on the solver parameters, we refer to the `CTHYB solver <https://triqs.github.io/cthyb/latest/reference/constr_parameters.html>`_ documentation. It is important to note that the solver parameters have to be adjusted for each material individually. A guide on how to set the tail fit parameters is given :ref:`below <tailfit>`.