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.
78 lines
4.0 KiB
ReStructuredText
78 lines
4.0 KiB
ReStructuredText
What you should know
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====================
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Probably, you can hardly wait to perform your first DFT+DMFT calculation
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with the :program:`DFTTools` package. This documentation and user guide
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should make it as easy as possible to get started quickly.
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However, it is mutually important to sort out a few prerequisites first.
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What is :program:`DFTTools`?
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----------------------------
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:program:`DFTTools` connects the :ref:`TRIQS <triqslibs:welcome>` library
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to realistic materials calculations based
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on density functional theory (DFT). It allows an efficient implementation
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of DFT plus dynamical mean-field theory (DMFT) calculations and it supplies
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tools and methods to construct Wannier functions and to perform the
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DMFT self-consistency cycle in this basis set. Post-processing tools,
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such as band-structure plotting or the calculation of transport properties
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are also implemented. The package comes with a fully charge self-consistent
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interface to the Wien2k band structure code, as well as a generic interface.
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We assume that you are already know about DFT and the usage of Wien2k.
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Have a look at :ref:`DFT+DMFT page <dftplusdmft>` for a brief introduction on
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the DFT+DMFT method and on how the theory is reflected in the
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:ref:`basic structure <structure>` of the :program:`DFTTools` package.
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Understand the philosophy of :program:`DFTTools`
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------------------------------------------------
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The purpose of :program:`DFTTools` is to provide the necessary tools
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required for a DFT+DMFT calculations. Putting those tools together to a working
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DFT+DMFT implementation is the task of the user. We do not
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supply an universal script which runs with the click of a button, simply because
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each material requires a different treatment or different settings.
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Building your own script offers a great deal of flexibility and customizability.
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Additionally, the :ref:`DFTTools user guide <documentation>` is there to support you
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during this process.
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It should go without saying, but the verification of outputs and the inspection
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of results on their meaningfulness is the responsibility of the user.
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The :program:`DFTTools` package is a toolbox and **not** a black box!
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Learn how to use :ref:`TRIQS <triqslibs:welcome>` (and the :ref:`CTHYB <triqscthyb:welcome>` solver)
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----------------------------------------------------------------------------------------------------
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As :program:`DFTTools` is a :ref:`TRIQS <triqslibs:welcome>` based application
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it is beneficial to invest a few hours to become familiar with
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the :ref:`TRIQS <triqslibs:welcome>` basics first. The
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:ref:`TRIQS tutorial <triqslibs:tutorials>` covers
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the most important aspects of :ref:`TRIQS <triqslibs:welcome>`. We recommend
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downloading our hands-on training in the form of ipython notebooks from
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the `tutorials repository on GitHub <https://github.com/TRIQS/tutorials>`_.
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Tutorials 1 to 6 are on the :ref:`TRIQS <triqslibs:welcome>` library, whereas tutorials
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7 and 8 are more specific to the usage of the :ref:`CTHYB <triqscthyb:welcome>`
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hybridization-expansion solver. In general, those tutorials will take at least a full day to finish.
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Afterwards you can continue with the :ref:`DFTTools user guide <documentation>`.
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.. _ac:
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Analytic Continuation
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---------------------
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Often impurity solvers working on the Matsubra axis are used within the
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DFT+DMFT framework. However, many :ref:`post-processing tools <analysis>`,
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require a self energy on the real-frequency axis, e.g. to calculate the spectral
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function :math:`A(k,\omega)` or to perform :ref:`transport calculations <Transport>`.
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The ill-posed nature of the analytic continuation has lead to a plethora of methods,
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and conversely, computer codes. :program:`DFTTools` itself does not provide functions to perform analytic
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continuations. Within the TRIQS environment the following options are available:
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* Pade: Implemented in the :ref:`TRIQS<triqslibs:welcome>` library
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* Stochastic Optimization Method (Mishchenko): `SOM <http://krivenko.github.io/som/>`_ package by Igor Krivenko
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* Maximum Entropy Method: `TRIQS/maxent <https://triqs.github.io/maxent/master>`_ package
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