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.. _analysis:
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Tools for analysis
==================
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This section explains how to use some tools of the package in order to analyse the data.
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There are two practical tools for which a self energy on the real axis is not needed, namely:
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* :meth: `dos_wannier_basis <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.dos_wannier_basis>` for the density of states of the Wannier orbitals and
* :meth: `partial_charges <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.partial_charges>` for the partial charges according to the :program: `Wien2k` definition.
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However, a real frequency self energy has to be provided by the user for the methods:
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* :meth: `dos_parproj_basis <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.dos_parproj_basis>` for the momentum-integrated spectral function including self energy effects and
* :meth: `spaghettis <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.spaghettis>` for the momentum-resolved spectral function (i.e. ARPES)
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.. warning ::
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This package does NOT provide an explicit method to do an **analytic continuation** of the
self energies and Green functions from Matsubara frequencies to the real frequency axis!
There are methods included e.g. in the :program: `ALPS` package, which can be used for these purposes.
Keep in mind that all these methods have to be used very carefully!
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Initialisation
--------------
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All tools described below are collected in an extension of the :class: `SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` class and are
loaded by importing the module :class: `SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>` ::
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from pytriqs.applications.dft.sumk_dft_tools import *
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The initialisation of the class is equivalent to that of the :class: `SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>`
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class::
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SK = SumkDFTTools(hdf_file = filename + '.h5')
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Note that all routines available in :class: `SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` are also available here.
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If required, we have to load and initialise the real frequency self energy. Most conveniently,
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you have your self energy already stored as a real frequency :class: `BlockGf <pytriqs.gf.local.BlockGf>` object
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in a hdf5 file::
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ar = HDFArchive('case.h5', 'a')
SigmaReFreq = ar['dmft_output']['Sigma_w']
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You may also have your self energy stored in text files. For this case the :ref: `TRIQS <triqslibs:welcome>` library offers
the function :meth: `read_gf_from_txt` , which is able to load the data from text files of one Greens function block
into a real frequency :class: `ReFreqGf <pytriqs.gf.local.ReFreqGf>` object. Loading each block separately and
building up a :class:´ BlockGf <pytriqs.gf.local.BlockGf>´ is done with::
from pytriqs.gf.local.tools import *
# get block names
n_list = [n for n,nl in SK.gf_struct_solver[0].iteritems()]
# load sigma for each block - in this example sigma is composed of 1x1 blocks
g_blocks = [read_gf_from_txt(block_txtfiles=[['Sigma_'+name+'.dat']], block_name=n) for n in n_list]
# put the data into a BlockGf object
SigmaReFreq = BlockGf(name_list=n_list, block_list=g_blocks, make_copies=False)
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where:
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* `block_txtfiles` is a rank 2 square np.array(str) or list[list[str]] holding the file names of one block and
* `block_name` is the name of the block.
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It is important that each data file has to contain three columns: the real frequency mesh, the real part and the imaginary part
of the self energy - exactly in this order! The mesh should be the same for all files read in and non-uniform meshes are not supported.
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Finally, we put the self energy into the `SK` object::
SK.put_Sigma(Sigma_imp = [SigmaReFreq])
and additionally set the chemical potential and the double counting correction from the DMFT calculation::
chemical_potential, dc_imp, dc_energ = SK.load(['chemical_potential','dc_imp','dc_energ'])
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SK.set_mu(chemical_potential)
SK.set_dc(dc_imp,dc_energ)
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del ar
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.. _dos_wannier:
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Density of states of the Wannier orbitals
-----------------------------------------
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For plotting the density of states of the Wannier orbitals, you type::
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SK.dos_wannier_basis(broadening=0.03, mesh=[om_min, om_max, n_om], with_Sigma=False, with_dc=False, save_to_file=True)
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which produces plots between the real frequencies `om_min` and `om_max` , using a mesh of `n_om` points. The parameter
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`broadening` defines an additional Lorentzian broadening, and has the default value of `0.01 eV` . To check the Wannier
density of states after the projection set `with_Sigma` and `with_dc` to `False` . If `save_to_file` is set to `True`
the output is printed into the files
* `DOS_wannier_(sp).dat` : The total DOS, where `(sp)` stands for `up` , `down` , or combined `ud` . The latter case
is relevant for calculations including spin-orbit interaction.
* `DOS_wannier_(sp)_proj(i).dat` : The DOS projected to an orbital with index `(i)` . The index `(i)` refers to
the indices given in `` SK.shells `` .
* `DOS_wannier_(sp)_proj(i)_(m)_(n).dat` : As above, but printed as orbitally-resolved matrix in indices
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`(m)` and `(n)` . For `d` orbitals, it gives the DOS separately for, e.g., :math: `d_{xy}` , :math: `d_{x^2-y^2}` , and so on,
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otherwise, the ouptput is returned by the function for a further usage in :program: `python` .
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Partial charges
---------------
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Since we can calculate the partial charges directly from the Matsubara Green's functions, we also do not need a
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real frequency self energy for this purpose. The calculation is done by::
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SK.put_Sigma(Sigma_imp = SigmaImFreq)
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dm = SK.partial_charges(beta=40.0, with_Sigma=True, with_dc=True)
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which calculates the partial charges using the self energy, double counting, and chemical potential as set in the
`SK` object. On return, `dm` is a list, where the list items correspond to the density matrices of all shells
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defined in the list `SK.shells` . This list is constructed by the :program: `Wien2k` converter routines and stored automatically
in the hdf5 archive. For the structure of `dm` , see also :meth: `reference manual <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.partial_charges>` .
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Correlated spectral function (with real frequency self energy)
--------------------------------------------------------------
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To produce both the momentum-integrated (total density of states or DOS) and orbitally-resolved (partial/projected DOS) spectral functions
we can execute::
SK.dos_parproj_basis(broadening=0.0, with_Sigma=True, with_dc=True, save_to_file=True)
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The variable `broadening` is an additional Lorentzian broadening (default: `0.01 eV` ) applied to the resulting spectra.
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The output is written in the same way as described above for the :ref: `Wannier density of states <dos_wannier>` , but with filenames
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`DOS_parproj_*` instead.
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Momentum resolved spectral function (with real frequency self energy)
---------------------------------------------------------------------
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Another quantity of interest is the momentum-resolved spectral function, which can directly be compared to ARPES
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experiments. First we have to execute `lapw1` , `lapw2 -almd` and :program: `dmftproj` with the `-band`
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option and use the :meth: `convert_bands_input <pytriqs.applications.dft.converters.wien2k_converter.Wien2kConverter.convert_bands_input>`
routine, which converts the required files (for a more detailed description see :ref: `conversion` ). The spectral function is then calculated by typing::
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SK.spaghettis(broadening=0.01,plot_shift=0.0,plot_range=None,ishell=None,save_to_file='Akw_')
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Here, optional parameters are
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* `shift` : An additional shift added as `(ik-1)*shift` , where `ik` is the index of the `k` point. This is useful for plotting purposes.
The default value is 0.0.
* `plotrange` : A list with two entries, :math: `\omega_{min}` and :math: `\omega_{max}` , which set the plot
range for the output. The default value is `None` , in which case the full momentum range as given in the self energy is used.
* `ishell` : An integer denoting the orbital index `ishell` onto which the spectral function is projected. The resulting function is saved in
the files. The default value is `None` . Note for experts: The spectra are not rotated to the local coordinate system used in :program: `Wien2k` .
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The output is written as the 3-column files `` Akw(sp).dat `` , where `(sp)` is defined as above. The output format is
`k` , :math: `\omega` , `value` .