diff --git a/doc/guide/analysis.rst b/doc/guide/analysis.rst index f84a14ef..913ba182 100644 --- a/doc/guide/analysis.rst +++ b/doc/guide/analysis.rst @@ -21,30 +21,9 @@ However, a real frequency self energy has to be provided by the user to use the 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! -Most conveniently, you have your self energy already stored as a real frequency :class:`BlockGf` object -in a hdf5 file, which can be easily loaded:: - - ar = HDFArchive(filename+'.h5','r') - SigmaReFreq = ar['SigmaReFreq'] - del ar - .. note:: - What happens if one has a self energy only in text files...? - -You may also store it in text files. If all blocks of your self energy are of dimension 1x1, you store them in `fname_(block)0.dat` files. Here `(block)` is a block name (`up`, `down`, or combined `ud`). In the case when you have matrix blocks, you store them in `(i)_(j).dat` files, where `(i)` and `(j)` are the orbital indices, in the `fname_(block)` directory. - -This self energy is loaded and put into the :class:`SumkDFT` class by the function:: - - SK.constr_Sigma_real_axis(filename, hdf=True, hdf_dataset='SigmaReFreq',n_om=0) - -where: - - * `filename`: the name of the hdf5 archive file or the `fname` pattern in text files names as described above, - * `hdf`: if `True`, the real-axis self energy will be read from the hdf5 file, otherwise from the text files, - * `hdf_dataset`: the name of dataset where the self energy is stored in the hdf5 file, - * `n_om`: the number of points in the real-axis mesh (used only if `hdf=False`). - -The chemical potential as well as the double counting correction were already read in the initialisation process. + Add the doc for loading the self energy from a data file. We have to provide this option, because + in general the user won't has it stored in h5 file!! Initialisation -------------- @@ -61,45 +40,51 @@ class:: Note that all routines available in :class:`SumkDFT` are also available here. -If required, the real frequency self energy is set with:: - - SK.put_Sigma(Sigma_imp = [ SigmaReFreq ]) +If required, a self energy is load and initialise in the next step. Most conveniently, +your self energy is already stored as a real frequency :class:`BlockGf` object +in a hdf5 file:: + + ar = HDFArchive(filename+'.h5','r') + SigmaReFreq = ar['SigmaReFreq'] + SK.put_Sigma(Sigma_imp = [ SigmaReFreq ]) + del ar + +Additionally, the chemical potential and the double counting correction are set with:: + + SK.chemical_potential = chemical_potential + SK.dc_imp = dc_imp Density of states of the Wannier orbitals ----------------------------------------- -For plotting the -density of states of the Wannier orbitals, you simply type:: +For plotting the density of states of the Wannier orbitals, you type:: - SK.check_input_dos(om_min, om_max, n_om) + SK.dos_wannier_basis(broadening=0.03, mesh=[om_min, om_max, n_om], with_Sigma=False, with_dc=False, save_to_file=True) -which produces plots between the real frequencies `om_min` and `om_max`, using a mesh of `n_om` points. There -is an optional parameter `broadening` which defines an additional Lorentzian broadening, and has the default value of -`0.01` by default. +which produces plots between the real frequencies `om_min` and `om_max`, using a mesh of `n_om` points. The parameter +`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`. Partial charges --------------- Since we can calculate the partial charges directly from the Matsubara Green's functions, we also do not need a -real-frequency self energy for this purpose. The calculation is done by:: +real frequency self energy for this purpose. The calculation is done by:: - ar = HDFArchive(SK.hdf_file) - SK.put_Sigma([ ar['SigmaImFreq'] ]) - del ar - dm = SK.partial_charges() + SK.put_Sigma(Sigma_imp = SigmaImFreq) + dm = SK.partial_charges(beta=40.0 with_Sigma=True, with_dc=True) -which calculates the partial charges using the data stored in the hdf5 file, namely the self energy, double counting, and -chemical potential. Here we assumed that the final self energy is stored as `SigmaImFreq` in the archive. -On return, `dm` is a list, where the list items correspond to the density matrices of all shells +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 defined in the list `SK.shells`. This list is constructed by the Wien2k converter routines and stored automatically in the hdf5 archive. For the detailed structure of `dm`, see the reference manual. -Correlated spectral function (with self energy) ------------------------------------------------ +Correlated spectral function (with real frequency self energy) +-------------------------------------------------------------- With this self energy, we can now execute:: - SK.dos_partial(broadening=broadening) + SK.dos_parproj_basis(broadening=broadening) This produces both the momentum-integrated (total density of states or DOS) and orbitally-resolved (partial/projected DOS) spectral functions. The variable `broadening` is an additional Lorentzian broadening applied to the resulting spectra. @@ -112,8 +97,8 @@ The output is printed into the files * `DOScorr(sp)_proj(i)_(m)_(n).dat`: As above, but printed as orbitally-resolved matrix in indices `(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. -Momentum resolved spectral function (with self energy) ------------------------------------------------------- +Momentum resolved spectral function (with real frequency self energy) +--------------------------------------------------------------------- Another quantity of interest is the momentum-resolved spectral function, which can directly be compared to ARPES experiments. We assume here that we already converted the output of the :program:`dmftproj` program with the