excitons on bands - 5% treshold

[malwi]

Dear Developers,

I run the example of Yambopy (exciton intro 2)
https://www.yambo-code.eu/wiki/index.ph ... _databases
I do it for my case which is a multiexciton, namely the first bright exciton has a wide multipeak amplitude over almost whole k-points (molecular crystal case).
How can I decrease the treshold of 5% that is in in Yambopy?
I obtained grey bands and no red contribution.

Best regards,
Gosia

[rreho]

Dear malwi,
You can play with the `size` in the call to `plot_ax(ax,c_bands='grey',c_weights='red',alpha_weights=0.5, size = 10)` to see if you have any "red contribution" at all.
I hope this is helpful.

If you have specific needs, you can try to return the `fig` and `ax` object in the`plot_ax` method, which is in `yambopy/plot/bandstructure.py`

Best,
Riccardo

[malwi]

Dear Riccardo,

thank you very much for the reply, however the problem is deeper.
I played with the figure options, size, axes etc.....

However, it is still not present because of data passed from the ypp
- this is what I think.

When using ypp -e a to calculate amplitude of the first bright exciton,
I needed to set 0.001 to see the contributions (via option weights_treshold)
while the default is 0.05.

I think that this 5% treshold is present in yambopy.... somehow.... I do not know how....
I hope we can fix the change to lower because it is really needed.

Best regards,
Gosia

[malwi]

Dear Riccardo,

please let me add more info:

My amp.in for ypp is:

excitons # [R] Excitonic properties
amplitude # [R] Amplitude
States= "2 - 2" # Index of the BS state(s)
BSQindex= 1 # Q-Index of the BS state(s)
Degen_Step= 0.010000 eV # Maximum energy separation of two degenerate states
Weight_treshold = 0.001 # treshold for contribution

In the result, I get 94 contributions with weights between 0.002 and 0.003
and 434 contributions between 0.002 and 0.001.

I set size = 1000 in

if Bands_Plot_Interpolate:
fig = plt.figure(figsize=(3.5,7.))
ax = fig.add_axes( [ 0.15, 0.15, 0.80, 0.80 ])

# In case of problems with the interpolation, try to increase lpratio
exc_on_bands = yexc.interpolate(yel,path,states,lpratio=10,f=None,size=1000.0,verbose=True)
exc_on_bands.plot_ax(ax,c_bands='grey',c_weights='red',alpha_weights=1.0)

ax.set_ylim(-1.5,5.0)
plt.ylabel("Energy (eV)")
fig.savefig("/net/ascratch/people/plgmalwi/Cov/c/bands-exc-3.pdf", backend='pdf')

and still only grey lines, no trace of red signal.


Please help

Gosia

[rreho]

Hi,
I see now what you want to do. However, to the best of my knowledge, there is a not a direct and easy way to tune this weight_threshold in yambopy.
I tried to add this line in the tutorial script:
```print(yexc.get_exciton_weights(states))```
and you can clearly see that you have all the weights that you want, regardless of any threshold.

Nevertheless, what I meant was to keep the size in the call to `interpolate` with a reasonable value like 0.5 or 1.0 and change the size in the call to `plot_ax`.
By changing the size in the call to 'plot_ax' I think you should also get the contribution with low weight.
Your script should look like this :
```
exc_on_bands = yexc.interpolate(yel,path,states,lpratio=10,f=None,size=0.5,verbose=True)
print(yexc.get_exciton_weights(states))
exc_on_bands.plot_ax(ax,color_bands='grey',c_weights='red',alpha_weights=0.5, size=100) # tune size here!
```
Let me know if that helps.

[malwi]

Dear Riccardo,

Thank you very much, it works!

I attach the plot.

Have a nice day,
Gosia

bands-exc-3.pdf

[rreho]

Hi,
Happy that it worked.
The plot looks reasonable to me.