mirror of https://github.com/triqs/dft_tools
Adding links to reference manual. Minor updates.
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Manuel Zingl
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@ -7,13 +7,13 @@ This section explains how to use some tools of the package in order to analyse t
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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.dos_wannier_basis>` for the density of states of the Wannier orbitals and
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* :meth:`partial_charges <pytriqs.applications.dft.sumk_dft_tools.partial_charges>` for the partial charges according to the Wien2k definition.
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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
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* :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 to use the methods:
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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.dos_parproj_basis>` for the momentum-integrated spectral function including self energy effects and
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* :meth:`spaghettis <pytriqs.applications.dft.sumk_dft_tools.spaghettis>` for the momentum-resolved spectral function (i.e. ARPES)
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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
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* :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
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@ -24,27 +24,27 @@ However, a real frequency self energy has to be provided by the user to use the
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Initialisation
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--------------
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All tools described below are collected in an extension of the :class:`SumkDFT` class and are
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loaded by importing the module :class:`SumkDFTTools`::
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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
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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`
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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` are also available here.
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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` object
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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')
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SigmaReFreq = ar['dmft_output']['Sigma_w']
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You may also have your self energy stored in text files. For this case we provide the function
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:meth:`constr_Sigma_real_axis`, which loads the data and puts it into a real frequency :class:`BlockGf` object::
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:meth:`constr_Sigma_real_axis`, which loads the data and puts it into a real frequency :class:`BlockGf <pytriqs.gf.local.BlockGf>` object::
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from pytriqs.applications.dft.build_sigma_from_txt import *
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SigmaReFreq = constr_Sigma_real_axis(SK, filename, hdf=False, hdf_dataset='SigmaReFreq',n_om=0, orb=0)
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@ -57,9 +57,8 @@ where:
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* `orb`: index of an inequivalent shell,
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* `n_om`: the number of points in the real-axis mesh (used only if `hdf=False`).
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It is important that some rules concerning the structure of the data is followed:
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* Each data file should contain the three columns: real frequency, real part and imaginary part of the self-energy in exactly this order.
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It is important that you follow some rules concerning the structure of your data files:
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* Each data file should contain three columns: real frequency, real part and imaginary part of the self energy exactly in this order.
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* If all blocks of your self energy are of dimension 1x1, you store them in `filename_(block)0.dat` files. Here `(block)` is a block name (`up`, `down`, or combined `ud`).
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* In the case when you have matrix blocks, you store them in `(i)_(j).dat` files, where `(i)` and `(j)` are the zero based orbital indices, in the `filename_(block)` directory.
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@ -74,6 +73,7 @@ and additionally set the chemical potential and the double counting correction f
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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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-----------------------------------------
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@ -92,9 +92,9 @@ the output is printed into the files
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* `DOS_wannier_(sp)_proj(i).dat`: The DOS projected to an orbital with index `(i)`. The index `(i)` refers to
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the indices given in ``SK.shells``.
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* `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 seperately for, e.g., :math:`d_{xy}`, :math:`d_{x^2-y^2}`, and so on,
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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 ouptut is returend by the function for further use in python.
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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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---------------
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@ -107,8 +107,8 @@ real frequency self energy for this purpose. The calculation is done by::
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which calculates the partial charges using the self energy, double counting, and chemical potential as set in the
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`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 Wien2k converter routines and stored automatically
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in the hdf5 archive. For the detailed structure of `dm`, see the reference manual.
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defined in the list `SK.shells`. This list is constructed by the :program:`Wien2k` converter routines and stored automatically
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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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--------------------------------------------------------------
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@ -119,7 +119,7 @@ we can execute::
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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 Wannier density of states, but with file names
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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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@ -127,12 +127,12 @@ 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()` routine to convert the required files. For a detailed description
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see :ref:`conversion`. The spectral function is then calculated by::
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option and use the :meth:`convert_bands_input <pytriqs.applications.dft.converters.wien2k_converter.Wien2kConverter.convert_bands_input>`
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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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Optional parameters are
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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.
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The default value is 0.0.
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@ -105,7 +105,7 @@ directory name):
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Now we convert these files into an hdf5 file that can be used for the
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DMFT calculations. For this purpose we
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use the python module :class:`Wien2kConverter`. It is initialised as::
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use the python module :class:`Wien2kConverter <pytriqs.applications.dft.converters.wien2k_converter.Wien2kConverter>`. It is initialised as::
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from pytriqs.applications.dft.converters.wien2k_converter import *
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Converter = Wien2kConverter(filename = case)
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@ -133,8 +133,8 @@ After this step, all the necessary information for the DMFT loop is
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stored in the hdf5 archive, where the string variable
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`Converter.hdf_filename` gives the file name of the archive.
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At this point you should use the method :meth:`dos_wannier_basis`
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contained in the module :class:`SumkDFTTools` to check the density of
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At this point you should use the method :meth:`dos_wannier_basis <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools.dos_wannier_basis>`
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contained in the module :class:`SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>` to check the density of
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states of the Wannier orbitals (see :ref:`analysis`).
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You have now everything for performing a DMFT calculation, and you can
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@ -144,7 +144,7 @@ Data for post-processing
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""""""""""""""""""""""""
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In case you want to do post-processing of your data using the module
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:class:`SumkDFTTools`, some more files
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:class:`SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>`, some more files
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have to be converted to the hdf5 archive. For instance, for
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calculating the partial density of states or partial charges
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consistent with the definition of :program:`Wien2k`, you have to invoke::
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@ -165,7 +165,7 @@ following. First, one has to do the Wien2k calculation on the given
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Again, maybe with the optional additional extra flags according to
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Wien2k. Now we use a routine of the converter module allows to read
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and convert the input for :class:`SumkDFTTools`::
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and convert the input for :class:`SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>`::
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Converter.convert_bands_input()
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@ -234,13 +234,13 @@ The interface packages are written such that all the file operations
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are done only on the master node. In general, the philosophy of the
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package is that whenever you read in something from the archive
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yourself, you have to *manually* broadcast it to the nodes. An
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exception to this rule is when you use routines from :class:`SumkDFT`
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or :class:`SumkDFTTools`, where the broadcasting is done for you.
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exception to this rule is when you use routines from :class:`SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>`
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or :class:`SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>`, where the broadcasting is done for you.
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Interfaces to other packages
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----------------------------
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Because of the modular structure, it is straight forward to extend the TRIQS package
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Because of the modular structure, it is straight forward to extend the :ref:`TRIQS <triqslibs:welcome>` package
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in order to work with other band-structure codes. The only necessary requirement is that
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the interface module produces an hdf5 archive, that stores all the data in the specified
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form. For the details of what data is stored in detail, see the
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@ -16,7 +16,7 @@ Wien2k + dmftproj
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In order to do charge self-consistent calculations, we have to tell the band structure program about the
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changes in the charge density due to correlation effects. In the following, we discuss how to use the
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:program:`TRIQS` tools in combination with the :program:`Wien2k` program.
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:ref:`TRIQS <triqslibs:welcome>` tools in combination with the :program:`Wien2k` program.
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We can use the DMFT script as introduced in section :ref:`singleshot`,
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with just a few simple
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@ -14,7 +14,7 @@ Initialisation of the calculation
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---------------------------------
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Before doing the calculation, we have to intialize all the objects that we will need. The first thing is the
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:class:`SumkDFT` class. It contains all basic routines that are necessary to perform a summation in k-space
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:class:`SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` class. It contains all basic routines that are necessary to perform a summation in k-space
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to get the local quantities used in DMFT. It is initialized by::
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from pytriqs.applications.dft.sumk_dft import *
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@ -25,7 +25,7 @@ Setting up the impurity solver
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------------------------------
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The next step is to setup an impurity solver. There are different
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solvers available within the TRIQS framework. Below, we will discuss
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solvers available within the :ref:`TRIQS <triqslibs:welcome>` framework. Below, we will discuss
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the example of the hybridisation
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expansion :ref:`CTHYB solver <triqscthyb:welcome>`. Later on, we will
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see also the example of the Hubbard-I solver. They all have in common,
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@ -62,7 +62,7 @@ iterations and the self-consistency condition::
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SK.save(['chemical_potential','dc_imp','dc_energ']) # Save data in the hdf5 archive
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These basic steps are enough to set up the basic DMFT Loop. For a detailed
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description of the :class:`SumkDFT` routines, see the reference
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description of the :class:`SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` routines, see the reference
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manual.
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After
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@ -170,11 +170,11 @@ will be stored in a separate subgroup in the hdf5 file, called
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`dmft_output`. Removing this subgroup allows you to reset your
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calculation to the starting point easily.
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Now we can use all this information to initialise the :class:`SumkDFT` class::
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Now we can use all this information to initialise the :class:`SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` class::
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SK = SumkDFT(hdf_file=dft_filename+'.h5',use_dft_blocks=use_blocks)
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The next step is to initialise the :class:`Solver` class. It consist
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The next step is to initialise the :class:`Solver <pytriqs.applications.impurity_solvers.cthyb.Solver>` class. It consist
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of two steps
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#. Calculating the multi-band interaction matrix, and setting up the
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@ -89,7 +89,7 @@ however there are also some differences. First difference is that we import the
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The Hubbard-I solver is very fast and we do not need to take into account the DFT block structure or use any approximation for the *U*-matrix.
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We load and convert the :program:`dmftproj` output and initialize the
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:class:`SumkDFT` class as described in :ref:`conversion` and
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:class:`SumkDFT <pytriqs.applications.dft.sumk_dft.SumkDFT>` class as described in :ref:`conversion` and
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:ref:`singleshot` and then set up the Hubbard-I solver ::
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S = Solver(beta = beta, l = l)
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@ -206,7 +206,7 @@ symmetries::
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Converter.convert_parpoj_input()
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To get access to analysing tools we initialize the
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:class:`SumkDFTTools` class ::
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:class:`SumkDFTTools <pytriqs.applications.dft.sumk_dft_tools.SumkDFTTools>` class ::
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SK = SumkDFTTools(hdf_file=dft_filename+'.h5', use_dft_blocks=False)
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