mirror of
https://github.com/triqs/dft_tools
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dfa10dffda
* Adapt the AC parts to the new TRIQS/maxent package * Restructure the explaination on how to run the scripts * Corrections of many typos and pytriqs occurences.
132 lines
5.3 KiB
ReStructuredText
132 lines
5.3 KiB
ReStructuredText
.. _structure:
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Structure of :program:`DFTTools`
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================================
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.. image:: images/structure.png
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:width: 700
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:align: center
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The central part of :program:`DFTTools`, which is performing the
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steps for the DMFT self-consistency cycle, is written following the
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same philosophy as the :ref:`TRIQS <triqslibs:welcome>` toolbox. At
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the user level, easy-to-use python modules are provided that allow to
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write simple and short scripts performing the actual calculation.
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The usage of those modules is presented in the user guide of this
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:ref:`documentation`. Before considering the user guide, we suggest
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to read the following introduction on the general structure of
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the :program:`DFTTools` package.
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The interface layer
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-------------------
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Since the input for this DMFT part has to be provided by DMFT
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calculations, there needs to be another layer that connects the
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python-based modules with the DFT output. Naturally, this layer
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depends on the DFT package at hand. At the moment, there is an
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interface to the Wien2k band structure package, and a very light
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interface that can be used in a more general setup. Note that this
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light interface layer **does not** allow full charge self-consistent
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calculations.
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Wien2k interface
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""""""""""""""""
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This interface layer consists of two parts. First, the output from Wien2k
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is taken, and localized Wannier orbitals are constructed. This is done
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by the FORTRAN program :program:`dmftproj`. The second part consist in
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the conversion of the :program:`dmftproj` into the hdf5 file
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format to be used for the DMFT calculation. This step is done by a
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python routine called :class:`Wien2kConverter`, that reads the text output and
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creates the hdf5 input file with the necessary ingredients. Quite
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naturally, :program:`DFTTools` will adopt this converter concept also for future
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developments for other DFT packages.
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General interface
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"""""""""""""""""
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In addition to the specialized Wien2k interface, :program:`DFTTools`
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provides also a very light-weight general interface. It basically
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consists of a very simple :class:`HkConverter`. As input it requires a
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Hamiltonian matrix :math:`H_{mn}(\mathbf{k})` written already in
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localized-orbital indices :math:`m,n`, on a :math:`\mathbf{k}`-point
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grid covering the Brillouin zone, and just a few other informations
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like total number of electrons, how many correlated atoms in the unit
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cell, and so on. It converts this Hamiltonian into a hdf5 format and
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sets some variables to standard values, such that it can be used with
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the python modules performing the DMFT calculation. How the
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Hamiltonian matrix :math:`H_{mn}(\mathbf{k})` is actually calculated,
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is **not** part of this interface.
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The DMFT calculation
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--------------------
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As mentioned above, there are a few python routines that allow to
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perform the multi-band DMFT calculation in the context of real
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materials. The major part is contained in the module
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:class:`SumkDFT`. It contains routines to
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* calculate local Green functions
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* do the upfolding and downfolding from Bloch bands to Wannier
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orbitals
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* calculate the double-counting correction
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* calculate the chemical potential in order to get the electron count right
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* other things like determining the structure of the local
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Hamiltonian, rotating from local to global coordinate systems, etc.
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At the user level, all these routines can be used to construct
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situation- and problem-dependent DMFT calculations in a very efficient
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way.
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Full charge self consistency
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----------------------------
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Using the Wien2k interface, one can perform full charge
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self-consistent calculations. :class:`SumkDFT` provides routines to
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calculate the correlated density matrix and stores it in a format that
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can be read in by the :program:`lapw2` part of the Wien2k
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package. Changing a one-shot calculation in a full charge
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self-consistent one is only a couple of additional lines in the code!
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Post-processing
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---------------
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The main result of DMFT calculation is the interacting Green function
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and the self energy. However, one is normally interested in
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quantities like band structure, density of states, or transport
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properties. In order to calculate these, :program:`DFTTools`
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provides the post-processing modules :class:`SumkDFTTools`.
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It contains routines to calculate
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* (projected) density of states
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* partial charges
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* correlated band structures (*spaghettis*)
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* transport properties such as optical conductivity, resistivity,
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or thermopower.
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Note that most of these post-processing tools need a real-frequency
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self energy, and should you be using a CT-QMC impurity solver this
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comes with the necessity of performing an :ref:`analytic continuation<ac>`.
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.. _runpy:
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Executing your python scripts
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-----------------------------
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After having prepared your own python script you may run
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it on one core with
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`python MyScript.py`
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or in parallel mode
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`mpirun -np 64 python MyScript.py`
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where :program:`mpirun` launches the calculation in parallel mode on 64 cores.
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The exact form of this command will, of course, depend on the
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mpi-launcher installed, but the form above works on most systems.
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How to run full charge self-consistent DFT+DMFT calculations (in combination with Wien2k)
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is described in the :ref:`full charge self-consistency tutorial<full_charge_selfcons>` and
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the :ref:`Ce tutorial<DFTDMFTtutorial>`, as such calculations need to be launched in a different way.
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