How to obtain the quasi-particle band structure of a bulk material: h-BN

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In this tutorial you will learn how to:

  • Calculate quasi-particle corrections in the Hartree-Fock approximation
  • Calculate quasi-particle corrections in the GW approximation
  • Choose the input parameters for a meaningful converged calculation
  • Plot a band structure including quasi-particle corrections

We will use bulk hBN as an example system. Before starting, you need to obtain the appropriate tarball. See instructions on the main tutorials page.
We strongly recommend that you first complete the First steps: a walk through from DFT to optical properties tutorial.

The aim of the present tutorial is to obtain quasiparticle correction to energy levels using many-body perturbation theory (MBPT).
The general non-linear quasiparticle equation reads:


As a first step we want to evaluate the self energy Σ entering in the quasiparticle equation. In the GW approach the self-energy can be separated into two components: a static term called the exchange self-energy (Σx), and a dynamical term (energy dependent) called the correlation self-energy (Σc):


We will treat these two terms separately and demonstrate how to set the most important variables for calculating each term. In practice we will compute the quasi-particle corrections to the one particle Kohn-Sham eigenvalues obtained through a DFT calculation.

The steps are the following:

Step 1: The Exchange Self Energy or HF quasi-particle correction

We start by evaluating the exchange Self-Energy and the corresponding Quasiparticle energies (Hartree-Fock energies). Follow the module on Hartree Fock and then return to this tutorial How to obtain the quasiparticle band structure of a bulk material: h-BN.

Step 2: The Correlation Self-Energy and Quasiparticle Energies

Once we have calculated the exchange part, we next turn our attention to the more demanding dynamical part. The correlation part of the self-energy in a plane wave representation reads:


In the expression for the correlation self energy, we have (1) a summation over bands, (2) an integral over the Brillouin Zone, and (3) a sum over the G vectors. In contrast with the case of Σx, the summation over bands extends over all bands (including the unoccupied ones), and so convergence tests are needed. Another important difference is that the Coulomb interaction is now screened so a fundamental ingredient is the evaluation of the dynamical dielectric matrix. The expression for the dielectric matrix, calculated at the RPA level and including local field effects, has been already treated in the Local fields tutorial.

In the following, we will see two ways to take into account the dynamical effects. First, we will see how to set the proper parameters to obtain a model dielectric function based on a widely used approximation, which models the energy dependence of each component of the dielectric matrix with a single pole function. Secondly, we will see how to perform calculations by evaluating the dielectric matrix on a regular grid of frequencies.

Once the correlation part of the self-energy is calculated, we will check the convergence of the different parameters with respect to some final quantity, such as the gap.

After computing the frequency dependent self-energy, we will discover that in order to solve the quasiparticle equation we will need to know its value at the value of the quasiparticle itself. In the following, unless explicitly stated, we will solve the non-linear quasi-particle equation at first order, by expanding the self-energy around the Kohn-Sham eigenvalue. In this way the quasiparticle equation reads:


where the normalization factor Z is defined as:


The Plasmon Pole approximation

As stated above, the basic idea of the plasmon-pole approximation is to approximate the frequency dependence of the dielectric matrix with a single pole function of the form:


The two parameters RGG' and ΩGG' are obtained by a fit (for each component), after having calculated the RPA dielectric matrix at two given frequencies. Yambo calculates the dielectric matrix in the static limit ( ω=0) and at a user defined frequency called the plasmon-pole frequency (ω=iωp). Such an approximation has the big computational advantage of calculating the dielectric matrix for only two frequencies and leads to an analytical expression for the frequency integral of the correlation self-energy.

Input file generation

Let's start by building up the input file for a GW/PPA calculation, including the calculation of the exchange self-energy. From yambo -H you should understand that the correct option is yambo -x -p p -g n:

$ yambo -x -p p -g n -F

Let's modify the input file in the following way:

HF_and_locXC                 # [R XX] Hartree-Fock Self-energy and Vxc
ppa                          # [R Xp] Plasmon Pole Approximation
gw0                          # [R GW] GoWo Quasiparticle energy levels
em1d                         # [R Xd] Dynamical Inverse Dielectric Matrix
EXXRLvcs = 40         Ry    # [XX] Exchange RL components
Chimod= "Hartree"                   # [X] IP/Hartree/ALDA/LRC/BSfxc
% BndsRnXp
  1 | 10 |                 # [Xp] Polarization function bands
NGsBlkXp= 1            RY    # [Xp] Response block size
% LongDrXp
 1.000000 | 1.000000 | 1.000000 |        # [Xp] [cc] Electric Field
PPAPntXp = 27.21138     eV    # [Xp] PPA imaginary energy
  1 | 40 |                 # [GW] G[W] bands range
GDamping=  0.10000     eV    # [GW] G[W] damping
dScStep=  0.10000      eV    # [GW] Energy step to evaluate Z factors
DysSolver= "n"               # [GW] Dyson Equation solver ("n","s","g")
%QPkrange        # [GW] QP generalized Kpoint/Band indices
 7|  7|  8|  9|

Brief explanation of some settings:

  • Similar to the Hartree Fock study, we will concentrate on the convergence of the direct gap of the system. Hence we select the last occupied (8) and first unoccupied (9) bands for k-point number 7 in the QPkrange variable.
  • We also keep EXXRLvcs at its converged value of 40 Ry as obtained in the Hartree Fock tutorial.
  • For the moment we keep fixed the plasmon pole energy PPAPntXp at its default value (=1 Hartree).
  • We keep fixed the direction of the electric field for the evaluation of the dielectric matrix to a non-specific value: LongDrXp=(1,1,1).
  • Later we will study convergence with respect to GbndRnge, NGsBlkXp, and BndsRnXp; for now just set them to the values indicated.

Understanding the output

Let's look at the typical Yambo output. Run Yambo with an appropriate -J flag:

$ yambo -F -J 10b_1Ry

In the standard output you can recognise the different steps of the calculations: calculation of the screening matrix (evaluation of the non interacting and interacting response), calculation of the exchange self-energy, and finally the calculation of the correlation self-energy and quasiparticle energies. Moreover information on memory usage and execution time are reported:

<---> [05] Dynamic Dielectric Matrix (PPA)
<08s> Xo@q[3] |########################################| [100%] 03s(E) 03s(X)
<08s> X@q[3] |########################################| [100%] --(E) --(X)
<43s> [06] Bare local and non-local Exchange-Correlation
<43s> EXS |########################################| [100%] --(E) --(X)
<43s> [07] Dyson equation: Newton solver
<43s> [07.01] G0W0 (W PPA)
<45s> G0W0 (W PPA) |########################################| [100%] --(E) --(X)
<45s> [07.02] QP properties and I/O
<45s> [08] Game Over & Game summary

Let's have a look at the report and output. The output file o-10b_1Ry.qp contains (for each band and k-point that we indicated in the input file) the values of the bare KS eigenvalue, its GW correction and the correlation part of the self energy:

#  K-point    Band       Eo         E-Eo       Sc|Eo
 7.000000   8.000000  -0.411876  -0.563191   2.322443
 7.000000   9.000000   3.877976   2.413822  -2.232241

In the header you can see the details of the calculations, for instance it reports that NGsBlkXp=1 Ry corresponds to 5 Gvectors:

#  X G`s            [used]:  5

Other information can be found in the report file r-10b_1Ry_em1d_ppa_HF_and_locXC_gw0, such as the renormalization factor defined above, the value of the exchange self-energy (non-local XC) and of the DFT exchange-correlation potential (local XC):

[07.02] QP properties and I/O
 Legend (energies in eV):
 - B  : Band       - Eo  : bare energy
 - E  : QP energy  - Z   : Renormalization factor
 - So : Sc(Eo)     - S   : Sc(E)
 - dSp: Sc derivative precision
 - lXC: Starting Local XC (DFT)
 -nlXC: Starting non-Local XC (HF)
 QP [eV] @ K [7] (iku): 0.000000 -0.500000  0.000000
  B=8 Eo= -0.41 E= -0.98 E-Eo= -0.56 Re(Z)=0.81 Im(Z)=-.2368E-2 nlXC=-19.13 lXC=-16.11 So= 2.322
  B=9 Eo=  3.88 E=  6.29 E-Eo=  2.41 Re(Z)=0.83 Im(Z)=-.2016E-2 nlXC=-5.536 lXC=-10.67 So=-2.232

Extended information can be also found in the output activating in the input the ExtendOut flag. This is an optional flag that can be activated by adding the -V qp verbosity option when building the input file. The plasmon pole screening, exchange self-energy and the quasiparticle energies are also saved in databases so that they can be reused in further runs:

$ ls ./10b_1Ry
ndb.pp ndb.pp_fragment_1 ... ndb.HF_and_locXC ndb.QP

Convergence tests for a quasi particle calculation

Now we can check the convergence of the different variables entering in the expression of the correlation part of the self energy.
First, we focus on the parameter governing the screening matrix you have already seen in the RPA/IP section. In contrast to the calculation of the RPA/IP dielectric function, where you considered either the optical limit or a finite q response (EELS), here the dielectric matrix will be calculated for all q-points determined by the choice of k-point sampling.

The parameters that need to be converged can be understood by looking at expression of the dielectric matrix:

Yambo tutorial image

where χGG' is given by

Yambo tutorial image

and χ0GG' is given by

Yambo tutorial image
  • NGsBlkXp : The dimension of the microscopic inverse matrix, related to Local fields
  • BndsRnXp : The sum on bands (c,v) in the independent particle χ0GG'

Converging Screening Parameters

Here we will check the convergence of the gap starting from the variables controlling the screening reported above: the bands employed to build the RPA response function BndsRnXp and the number of blocks (G,G') of the dielectric matrix ε-1G,G' NGsBlkXp. In the next section we will study convergence with respect to the sum over states summation (sum over m in the Σc expression); here let's fix GbndRnge to a reasonable value (40 Ry).

Let's build a series of input files differing by the values of bands and block sizes in χ0GG' considering BndsRnXp in the range 10-50 (upper limit) and NGsBlkXp in the range 1 to 5 Ry. To do this by hand, file by file, open the file in an editor and change to:

NGsBlkXp = 2 Ry

while leaving the rest untouched. Repeat for 3 Ry, 4 Ry etc. Next, for each NGsBlkXp change to:

% BndsRnXp
  1 | 20 |                 # [Xp] Polarization function bands

and repeat for 30, 40 and so on. Give a different name to each file: with X=10,20,30,40 and Y=1,2,3,4,5 Ry.

This is obviously quite tedious. However, you can automate both the input construction and code execution using bash or python scripts (indeed later you will learn how to use the the Yambo-pythontool for this task). For now, you can use the simple bash script to generate the required input files (after copying the script you need to type $ chmod +x ).

Finally launch the calculations:

$ yambo -F -J 10b_1Ry
$ yambo -F -J 10b_2Ry
$ yambo -F -J 40b_5Ry

Once the jobs are terminated we can collect the quasiparticle energies for fixed BndsRnXp in different files named e.g. 10b.dat, 20b.dat etc. for plotting, by putting in separate columns: the energy cutoff; the size of the G blocks; the quasiparticle energy of the valence band; and that of the conduction band. To do this e.g. for the 10b.dat file you can type:

$ cat o-10b* | grep "8.000" |  awk '{print $3+$4}' 

to parse the valence band quasiparticle energies and

$ cat o-10b* | grep "9.000" |  awk '{print $3+$4}' 

for the conduction band; and put all the data in the 10b.dat files. As there are many files to process you can use the script to create the 10b.dat file and edit the script changing the number of BndsRnXp for the other output files.

Once we have collected all the quasiparticle values we can plot the gap, or the valence and conduction band energies separately, as a function of the block size or energy cutoff:

$ gnuplot
gnuplot> p "10b.dat" u 1:3 w lp t " Valence BndsRnXp=10", "20b.dat" u 1:3 w lp t "Valence BndsRnXp=20",.. 
gnuplot> p "10b.dat" u 1:4 w lp t " Conduction BndsRnXp=10", "20b.dat" u 1:4 w lp t "Conduction BndsRnXp=20",..
gnuplot> p "10b.dat" u 1:($4-$3) w lp t " Gap BndsRnXp=10", "20b.dat" u 1:($4-$3) w lp t "gap BndsRnXp=20",..  

or both using e.g. the ppa_gap.gnu gnuplot script:


Looking at the plot we can see that:

  • The two parameters are not totally independent (see e.g. the valence quasiparticle convergence) and this is the reason why we converged them simultaneously
  • The gap (energy difference) converge faster than single quasiparticle state
  • The convergence criteria depends on the degree of accuracy we look for, but considering the approximations behind the calculations (plasmon-pole etc.), it is not always a good idea to enforce too strict a criteria.
  • Even if not totally converged we can consider that the upper limit of BndsRnXp=30, and NGsBlkXp=3Ry are reasonable parameters.

Converging the sum over states in the correlation self-energy

From now on we will keep fixed these parameters and will perform a convergence study on the sum over state summation in the correlation self-energy (Σc) GbndRnge.

In order to use the screening previously calculated we can copy the plasmon pole parameters saved in the 30b_3Ry directory in the SAVE directory. In this way the screening will be read by Yambo and not calculated again:

$ cp ./30b_3Ry/ndb_pp* ./SAVE/.

(Note: you may have to delete these files before running the BSE tutorials)

In order to use the database we have to be sure to have the same plasmon-pole parameters in our input files. Edit and modify GbndRnge to order to have a number of bands in the range from 10 to 80 inside different files named, etc. You can also run the the bash script to generate the required input files.

Next, launch yambo for each input:

$ yambo -F -J Gbnd10
$ yambo -F -J Gbnd20

and as done before we can inspect the obtained quasiparticle energies:

$ grep 8.00 o-Gbnd*  | awk '{print $4+$5}'

for the valence bands, and

$ grep 9.00 o-Gbnd*  | awk '{print $4+$5}' 

for the conduction band.

Collect the results in a text file Gbnd_conv.dat containing: the number of Gbnd, the valence energy, and the conduction energy. Now, as done before we can plot the valence and conduction quasiparticle levels separately as well as the gap, as a function of the number of bands used in the summation:

$ gnuplot
gnuplot> p "Gbnd_conv.dat" u 1:2 w lp lt 7  t "Valence"
gnuplot> p "Gbnd_conv.dat" u 1:3 w lp lt 7  t "Conduction"
gnuplot> p "Gbnd_conv.dat" u 1:($3-$2) w lp lt 7  t "Gap"


Inspecting the plot we can see that:

  • The convergence with respect to GbndRange is rather slow and many bands are needed to get converged results.
  • As observed above the gap (energy difference) converges faster than the single quasiparticle state energies.

Accelerating the sum over states convergence in the correlation self-energy

In general the convergence with respect the sum over states can be very cumbersome. Here we show how it can be mitigated by using a technique developed by F. Bruneval and X. Gonze [1]. The basic idea relies in replacing the eigenenergies of the states that are not treated explicitly by a common energy, and take into account all the states, which are not explicitly included in the calculation through the closure relation. To apply this technique in Yambo we need to activate the optional terminator variable GTermKind. We can activate it by adding the quasiparticle verbosity to the command line when generating the input file:

$ yambo -p p -g n -F -V qp

and you can edit the input file by setting:

GTermKind= "BG"

or simply you can add by hand this line in all the other input files. Now we can repeat the same calculations

$ yambo -F -J Gbnd10_term
$ yambo -F -J Gbnd20_term

and collect the new results:

$ grep 8.000 *term.qp  | awk '{print $4+$5}'
$ grep 9.000 *term.qp  | awk '{print $4+$5}' 

in a new file called Gbnd_conv_terminator.dat. Now we can plot the same quantities as before by looking at the effect of having introduced the terminator.

gnuplot> p "Gbnd_conv.dat" u 1:2  w lp t "Valence", "Gbnd_conv_terminator.dat" u 1:2 w lp t "Valence with terminator"
gnuplot> p "Gbnd_conv.dat" u 1:3  w lp t "Conduction", "Gbnd_conv_terminator.dat" u 1:3 w lp t "Conduction with terminator"
gnuplot> p "Gbnd_conv.dat" u 1:($3-$2)  w lp t "Gap", "Gbnd_conv_terminator.dat" u 1:($3-$2) w lp t "Gap with terminator"


We can see that:

  • The convergence with respect to GbndRange is accelerated in particular for the single quasiparticle states.
  • From the plot above we can see that GbndRange=40 is sufficient to have a converged gap

Beyond the plasmon pole approximation: a full frequency approach - real axis integration

All the calculations performed up to now were based on the plasmon pole approximation (PPA). Now we remove this approximation by evaluating numerically the frequency integral in the expression of the correlation self-energy (Σc). To this aim we need to evaluate the screening for a number of frequencies in the interval depending on the electron-hole energy difference (energy difference between empty and occupied states) entering in the sum over states. Let's build the input file for a full frequency calculation by simply typing:

$ yambo -F -g n 

and we can set the variable studied up to now at their converged value:

1 | 30 |
NGsBlkXd=3 Ry
1 | 40 |
EXXRLvcs=40 Ry
% LongDrXd 
1.000000 | 1.000000 | 1.000000 |        # [Xd] [cc] Electric Field

and next vary in different files (name them etc.) the number of frequencies we evaluate for the screened coulomb potential. This is done by setting the values of ETStpsXd=10 , 20, 50 , 100, 150, 200, 250. You can also run the the bash script to generate the required input files.

Next launch yambo:

$ yambo -F -J ff10
$ yambo -F -J ff50


Clearly as we are evaluating the screening for a large number of frequencies these calculations will be heavier than the case above where the calculation of the screening was done for only two frequencies (zero and plasmon-pole). As before, collect the valence and conduction bands as a function of the number of frequencies in a file called gw_ff.dat and plot the behaviour of the conduction and valence bands and the gap.

$ gnuplot
gnuplot> p "gw_ff.dat" u 1:2  w lp t "Valence"
gnuplot> p "gw_ff.dat" u 1:3  w lp t "Conduction"
gnuplot> p "gw_ff.dat" u 1:($3-$2)  w lp t "Gap"


We can see that:

  • Oscillations are still present, indicating that even more frequencies have to be considered. In general, a real-axis calculation is very demanding.
  • The final result of the gap obtained up to now does not differ too much from the one obtained at the plasmon-pole level (~50 meV)

Secant Solver

The real axis integration permits also to go beyond the linear expansion to solve the quasi particle equation. The QP equation is a non-linear equation whose solution must be found using a suitable numerical algorithm.


The mostly used, based on the linearization of the self-energy operator is the Newton method that is the one we have used up to now. Yambo can also perform a search of the QP energies using a non-linear iterative method based on the Secant iterative Method.

In numerical analysis, the secant method is a root-finding algorithm that uses a succession of roots of secant lines to better approximate a root of a function f. The secant method can be thought of as a finite difference approximation of Newton's method. The equation that defines the secant method is:


The first two iterations of the secant method are shown in the following picture. The red curve shows the function f and the blue lines are the secants.


To see if there is any non-linear effect in the solution of the Dyson equation we compare the result of the calculation using the Newton solver as done before with the present case. In order to use the secant method you need to edit one of the the previous files e.g. and substitute:

DysSolver= "g"


DysSolver= "s"

Repeat the calculations in the same way as before:

$ yambo -F -J ff100

Note than now the screening will not be calculated again as it has been stored in the ffN directories as can be seen in the report file:

[05] Dynamical Dielectric Matrix

Comparing the output files, e.g. for the case with 100 freqs:

o-ff100.qp Newton Solver:

#  K-point    Band       Eo         E-Eo       Sc|Eo
  7.00000    8.00000   -0.41188   -0.05933    2.94162
  7.000000   9.000000   3.877976   1.393774  -3.446402

o-ff100.qp_01 Secant Solver:

#  K-point    Band       Eo         E-Eo       Sc|Eo
  7.00000    8.00000   -0.41188   -0.05950    2.95728
  7.000000   9.000000   3.877976   1.373645  -3.759375

From the comparison we see that the effect is of the order of 20 meV, of the same order of magnitude of the accuracy of the GW calculations.

Step 3: Interpolating Band Structures

Up to now we have checked convergence for the gap. Now we want to calculate the quasiparticle corrections across the Brillouin zone in order to visualize the entire band structure along a path connecting high symmetry points.

To do that we start by calculating the QP correction in the plasmon-pole approximation for all the k points of our sampling and for a number of bands around the gap. You can use a previous input file or generate a new one: yambo -F -x -p p -g n and set the parameters found in the previous tests:

EXXRLvcs=  40        Ry 
% BndsRnXp
  1 | 30 |                 # [Xp] Polarization function bands
NGsBlkXp= 3            Ry    # [Xp] Response block size
% LongDrXp
 1.000000 | 1.000000 | 1.000000 |        # [Xp] [cc] Electric Field
PPAPntXp= 27.21138     eV    # [Xp] PPA imaginary energy
% GbndRnge
  1 | 40 |                 # [GW] G[W] bands range

and we calculate it for all the available kpoints by setting:

%QPkrange                    # [GW] QP generalized Kpoint/Band indices
 1| 14|  6|11|

Note that as we have already calculated the screening with these parameters you can save time and use that database either by running in the previous directory by using -J 30b_3Ry or if you prefer to put the new databases in the new all_Bz directory you can create a new directory and copy there the screening databases:

$ mkdir all_Bz 
$ cp ./30b_3Ry/ndb.pp* ./all_Bz/

and launch the calculation:

$ yambo -F -J all_Bz

Now we can inspect the output and see that it contains the correction for all the k points for the bands we asked:

#  K-point    Band       Eo         E-Eo       Sc|Eo
 1.000000   6.000000  -1.299712  -0.215759   3.788044
 1.000000   7.000000  -1.296430  -0.238232   3.788091
 1.000000   8.000000  -1.296420  -0.239959   3.785949
 1.000000   9.000000   4.832399   0.951691  -3.679265
  1.00000   10.00000   10.76416    2.10457   -4.38743
  1.00000   11.00000   11.36167    2.48237   -3.91021

By plotting some of the 'o-all_Bz.qp" columns it is possible to discuss some physical properties of the hBN QPs. Using columns 3 and (3+4), ie plotting the GW energies with respect to the LDA energies we can deduce the band gap renormalization and the stretching of the conduction/valence bands:

$ gnuplot
gnuplot> p "o-all_Bz.qp" u 3:($3+$4) w p  t "Eqp vs Elda" 

Essentially we can see that the effect of the GW self energy is the opening of the gap and a linear stretching of the conduction/valence bands that can be estimated by performing a linear fit of the positive and negative energies (the zero is set at top of the valence band).

In order to calculate the band structure, however, we need to interpolate the values we have calculated above on a given path. In Yambo the interpolation is done by the executable ypp (Yambo Post Processing). By typing:

$ ypp -H  

you will recognize that in order to interpolate the bands we need to build a ypp input file using

$ ypp -s b

Before editing the input file and running the interpolation, it is important to know that ypp uses an algorithm [2] that cannot be used in presence of time-reversal (TR) symmetry. As a first step we therefore remove the TR symmetry by typing:

$ ypp -y

and we uncomment the corresponding line to remove the TR.

fixsyms                      # [R] Reduce Symmetries
#RmAllSymm                   # Remove all symmetries
#RmTimeRev                   # Remove Time Reversal

and launch

$ ypp

This will create a new directory called FixSymm where a SAVE directory containing the electronic structure in the absence of TR is present. We will calculate the band structure in the FixSymm directory.

$ cd FixSymmm

After having performed the usual setup


we can generate the input for the band interpolation:

$ypp -s b -F

and edit the file:

electrons                    # [R] Electrons (and holes)
bnds                         # [R] Bands
cooIn= "rlu"                 # Points coordinates (in) cc/rlu/iku/alat
BANDS_steps=0                # Number of divisions
-1 |-1 |-1 |                             # Interpolation BZ Grid
ShellFac= 20.00000           # The bigger it is a higher number of shells is used
%QPkrange                    #  generalized Kpoint/Band indices
  1| 20|  1|100|
%BKpts                       # K points of the bands circuit
0.00000 |0.00000 |0.00000 |

We modify the following lines:

%QPkrange                    #  generalized Kpoint/Band indices
  1| 20|  6|11|
%BKpts                       # K points of the bands circuit
 0.33300 |-.66667 |0.00000 |
 0.00000 |0.00000 |0.00000 |
 0.50000 |-.50000 |0.00000 |
 0.33300 |-.66667 |0.00000 |
 0.33300 |-.66667 |0.50000 |
 0.00000 |0.00000 |0.50000 |
 0.50000 |-.50000 |0.50000 |

which means we assign 30 point in each segment, we ask to interpolate 3 occupied and 3 empty bands and we assign the following path passing from the high symmetry points: K Γ M K H A L. Launching:

$ ypp -F

will produce the output file o.bands_interpolated containing:

#   |k|        b6         b7         b8         b9         b10        b11        kx         ky         kz
    0.00000   -7.22092   -0.13402   -0.13395    4.67691    4.67694   10.08905    0.33300   -0.66667    0.00000
    0.03725   -7.18857   -0.17190   -0.12684    4.66126    4.71050   10.12529    0.32190   -0.64445    0.00000


and we can plot the bands using gnuplot:

$ gnuplot
gnuplot> p "o.bands_interpolated" u 0:2 w l, "o.bands_interpolated" u 0:3 w l, ...

and you can recognize the index of the high symmetry point by inspecting the last three columns. Note that up to now we have interpolated the LDA band structure. In order to plot the GW band structure we need to tell ypp in the input file where the ndb.QP database is found. This is achieved by adding in the file the line:

 GfnQPdb= "E < ../all_Bz/ndb.QP"

and relaunch

$ ypp -F

Now the file o.bands_interpolated_01 contains the GW interpolated band structure. We can plot the LDA and GW band structure together by using the gnuplot script bands.gnu.

  • As expected the effect of the GW correction is to open the gap.
  • Comparing the obtained band structure with the one found in the literature by Arnaud and coworkers [3] we found a very nice qualitative agreement.
  • Quantitatively we found a smaller gap: about 5.2 eV (indirect gap), 5.7 eV (direct gap) while in Ref.[3] is found 5.95 eV for the indirect gap and a minimum direct band gap of 6.47 eV. Other values are also reported in the literature depending on the used pseudopotentials, starting functional and type of self-consistency (see below).
  • The present tutorial has been done with a small k point grid which is an important parameter to be checked, so convergence with respect the k point sampling has to be validated.

Step 4: Summary of the convergence parameters

We have calculated the band structure of hBN starting from a DFT calculation, here we summarize the main variable we have checked to achieve convergence:

Number of G-vectors in the exchange. This number should be checked carefully. Generally a large number is needed as the QP energies show a slow convergence. The calcualtion of the exchange part is rather fast.

  • BndsRnXp #[Xp] Polarization function bands

Number of bands in the independent response function form which the dielectric matrix is calculated. Also this paramater has to be checked carefully,together with NGsBlkXp as the two variables are interconnected

Number of G-vectors block in the dielectric constant. Also this paramater has to be checked carefully, to be checked together with BndsRnXp. A large number of bands and block can make the calculation very demanding.

Direction of the electric field for the calculation of the q=0 component of the dielectric constant e(q,w). In a bulk can be set to (1,1,1), attention must be paid for non 3D systems.

  • PPAPntXp # [Xp] Plasmon pole imaginary energy: this is the second frequency used to fit the Godby-Needs plasmon-pole model (PPM). If results depend consistently by changing this frequency, the PPM is not adequate for your calculation and it is need to gp beyond that, e.g. Real-axis.

Number of bands used to expand the Green's function. This number is usually larger than the number of bands used to calculated the dielectricconstant. Single quasiparticle energies converge slowly with respect GbndRnge, energy difference behave better. You can use terminator technique to mitigate the slow dependence.

Small damping in the Green's function definition, the delta parameter. The final result shouuld not depend on that, usually set at 0.1 eV

Energy step to evaluate Z factors

  • DysSolver # [GW] Dyson Equation solver ("n","s","g")

Parameters related to the solution of the Dyson equation, "n" Newton linearization, 's' non linear secant method

Terminator for the self-energy[1] . We have seen how this spped up the convergence with respect empty bands.

  • QPkrange # [GW] QP generalized Kpoint/Band indices

K-points and band range where you want to calculate the GW correction. The syntax is first kpoint | last kpoint | first band | last band

Step 5: Eigenvalue only self-consistent GW0

Here we want to see how we can compute an eigenvalue only GW0 correction in Yambo. By eigenvalue only we mean that the quasiparticle wavefunctions are assumed to be the LDA wavefunctions and are not changed during the loop, but only the quasiparticle energies are updated. Moreover, we will not update the screening, but only the Green function. It is also possible to update the screening, but we leave that as an exercise.

We will use the same parameters used before for the screening and number of bands. In contrast to the calculations done before now we need to calculate the correction for all the bands that will enter in the Green function so we can copy the screening from before:

$ mkdir SC
$ cp ./all_Bz/ndb.p* ./SC/.

and copy the file to in which we set:

%QPkrange               # [GW] QP generalized Kpoint/Band indices
1| 14|  6|11|

and run the first run of the cycle, exactly as before:

$ yambo -F -J SC

Once the calculation is terminated we move the QP database in the current directory

$ mv ./SC/ndb.QP .

and we modify the input file in order to tell yambo to read the quasiparticle energies calculated in the previous run instead of the KS eigenvalue. This is achieved by adding in the input file:

GfnQPdb= "E < ndb.QP"   

and launch yambo again. Next we move again the new quasi particle in the current directory and repeat the loop. Each run will last around 8 minutes in serial in the cecam cluster. We compare the output file "o-SC.qp", "o-SC.qp_01" and we stop when desired accuracy is reached. Looking for example at the last filled valence and conduction bands at Gamma point:

$ grep " 1.000000   8.000000 " o-SC.qp*
o-SC.qp:  1.000000   8.000000  -1.296420  -0.239959   3.785949
o-SC.qp_01:  1.000000   8.000000  -1.296420  -0.275293   3.745405
o-SC.qp_02:  1.000000   8.000000  -1.296420  -0.287520   3.731213
o-SC.qp_03:  1.000000   8.000000  -1.296420  -0.289822   3.728570
$ grep " 1.000000   9.000000 " o-SC.qp*
o-SC.qp:  1.000000   9.000000   4.832399   0.951691  -3.679265
o-SC.qp_01:  1.000000   9.000000   4.832399   1.115555  -3.503588
o-SC.qp_02:  1.000000   9.000000   4.832399   1.136954  -3.480806
o-SC.qp_03:  1.000000   9.000000   4.832399   1.139693  -3.477701

we can see that the calculation is converged after 4 iterations. We can now interpolate the band structure using the last ndb.QP:

$ cd FixSymm 

Edit the "" setting:

GfnQPdb= "E < ../SC/ndb.QP"

and launch

$ ypp -F

We can then compare the G0W0 with the new GW0 bands structure (you can use the gnuplot script bands.gnu substituting the new band file o.bands_interpolated_02

  • The eigenvalue self consistency in G, i.e. GW0 gives a correction of about 0.2/0.25 eV giving an indirect gap of 5.45 eV and a direct gap of 5.9 eV in agreement with the calcualation in Wirtz et al. [4])
  • Important effects on the gap are found in the literature when considering Self consistency also for the screening, e.g. N. Berseneva et al. [5]). Eigenvalue GW self consistency can be calculated with Yambo repeating the same procedure seen for the GW0 method and adding in the input file the keyword XfnQPdb= "E < ./SC/ndb.QP" and removing the ndb.PP* databases after each iteration, or alternatively redirecting the databases in different directories e.g. launching
$ yambo -F -J SC1
$ cp ./SC1/ndb.QP .
$ yambo -F -J SC2
$ cp ./SC2/ndb.QP .

Step 6: Exercise: Convergence with respect K points

As an exercise now you can check the convergence with respect the K point sampling:

  1. perform a new non-scf calculation with a bigger k point grid: 9x9x3 and 12x12x4 ...
  2. convert wave functions and electronic structure to Yambo databases in a different directory as explained in the DFT and p2y module,
  3. Initialize the Yambo databases,
  4. Redo the steps explained in this section (exchange self energy, plasmon pole GW, band structure interpolation)
  5. The PPA-GW calculation using 12x12x4 grid takes around 12 minutes in serial mode in the Cecam cluster. You can think to perform the exercise after having learned some basic on the parallelization strategy.

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  1. 1.0 1.1 1.2 1.3 F. Bruneval and X. Gonze, Physical Review B 78, 085125 (2008 )
  2. Warren E. Pickett, Henry Krakauer, and Philip B. Allen Phys. Rev. B 38, 2721
  3. 3.0 3.1 3.2 B. Arnaud, S. Lebegue,P. Rabiller, and M. Alouani Phys, Rev. Lett. 96, 026402 (2006)
  4. L. Wirtz, A. Marini, M. Gruning, A. Rubio in arXiv:cond-mat/0508421 [cond-mat.mtrl-sci]
  5. N. Berseneva, A. Gulans, AV. Krasheninnikov and R. M. Nieminen1 Phys. Rev. B 87, 035404 (2013)