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fix package information in doc installation and some broken links

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Alexander Hampel 2021-09-30 12:17:50 -04:00
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commit da260535d2
3 changed files with 8 additions and 8 deletions
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6
doc/install.rst
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@ -12,7 +12,7 @@ Packaged Versions of DFTTools
Ubuntu Debian packages
----------------------
We provide a Debian package for the Ubuntu LTS Versions 16.04 (xenial) and 18.04 (bionic), which can be installed by following the steps outlined :ref:`here <triqslibs:triqs_debian>`, and the subsequent command::
We provide a Debian package for the Ubuntu LTS Versions 18.04 (bionic) and 20.04 (focal), which can be installed by following the steps outlined :ref:`here <triqslibs:ubuntu_debian>`, and the subsequent command::
sudo apt-get install -y triqs_dft_tools
@ -39,9 +39,9 @@ Compiling DFTTools from source
Prerequisites
-------------
#. The :ref:`TRIQS <triqslibs:welcome>` library, see :ref:`TRIQS installation instruction <triqslibs:installation>`.
#. The :ref:`TRIQS <triqslibs:welcome>` library, see :ref:`TRIQS installation instruction <triqslibs:triqs_install>`.
In the following, we assume that TRIQS is installed in the directory ``path_to_triqs``.
#. Likely, you will also need at least one impurity solver, e.g. the :ref:`CTHYB solver <triqscthyb:welcome>`.
#. Likely, you will also need at least one impurity solver, e.g. the `CTHYB solver <https://triqs.github.io/cthyb/latest/>`_.
Installation steps
------------------

2
doc/tutorials/images_scripts/NiO_local_lattice_GF.py.rst
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@ -1,7 +1,7 @@
.. _NiO_local_lattice_GF.py:
NiO_local_lattice_GF.py
-----------
-----------------------
Download :download:`NiO_local_lattice_GF.py <./NiO_local_lattice_GF.py>`.

8
doc/tutorials/svo_elk/srvo3.rst
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@ -1,6 +1,6 @@
.. _SrVO3_elk:
This example is almost identical to the :ref:`Wien2k-TRIQS SrVO3 example <SrVO3>`. On the example of SrVO3 we will discuss now how to set up a full working calculation using Elk, including the initialization of the :ref:`CTHYB solver <triqscthyb:welcome>`. Some additional parameter are introduced to make the calculation more efficient. This is a more advanced example, which is also suited for parallel execution.
This example is almost identical to the :ref:`Wien2k-TRIQS SrVO3 example <SrVO3>`. On the example of SrVO3 we will discuss now how to set up a full working calculation using Elk, including the initialization of the :ref:`CTHYB solver <https://triqs.github.io/cthyb/latest>`_. Some additional parameter are introduced to make the calculation more efficient. This is a more advanced example, which is also suited for parallel execution.
For the convenience of the user, we provide also a full python script (:download:`dft_dmft_cthyb_elk.py <dft_dmft_cthyb_elk.py>`). The user has to adapt it to their own needs. How to execute your script is described :ref:`here<runpy>`.
@ -48,7 +48,7 @@ First, we load the necessary modules::
import triqs.utility.mpi as mpi
The last two lines load the modules for the construction of the
:ref:`CTHYB solver <triqscthyb:welcome>`.
:ref:`CTHYB solver <https://triqs.github.io/cthyb/latest/>`_.
Initializing SumkDFT
--------------------
@ -73,7 +73,7 @@ And next, we can initialize the :class:`SumkDFT <dft.sumk_dft.SumkDFT>` class::
Initializing the solver
-----------------------
We also have to specify the :ref:`CTHYB solver <triqscthyb:welcome>` related settings. We assume that the DMFT script for SrVO3 is executed on 16 cores. A sufficient set of parameters for a first guess is::
We also have to specify the :ref:`CTHYB solver <https://triqs.github.io/cthyb/latest>`_ related settings. We assume that the DMFT script for SrVO3 is executed on 16 cores. A sufficient set of parameters for a first guess is::
p = {}
# solver
@ -86,7 +86,7 @@ We also have to specify the :ref:`CTHYB solver <triqscthyb:welcome>` related set
p["fit_min_n"] = 30
p["fit_max_n"] = 60
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 :ref:`CTHYB solver <triqscthyb:welcome>` 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 :ref:`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>`.
The next step is to initialize the :class:`solver class <triqs_cthyb.Solver>`. It consist of two parts: