You do not have permission to delete messages in this group
Copy link
Report message
Sign in to report message
Show original message
Either email addresses are anonymous for this group or you need the view member email addresses permission to view the original message
to cp2k
Hi!
I am planning a project on constructing a machine learning potential based on CP2K calculations, and as part of this I need access to dependable partial charges. Self-consistent Hirshfeld with SHAPE_FUNCTION DENSITY seems to be the best option in CP2K as I would like to avoid post-processing of potentially hundreds of gigabytes of data.
Digging through the source code, it seems that the comp_hirshfeld_i_charges routine proceeds until the total charge residual is less than 1e-2. I am not sure this is enough to train a reliable machine learning model, however, so I would like to change it to something stricter to be on the safe side. Is this safe to do, or could that lead to e.g. numerical instabilities? Changing it to 1e-4 or 1e-5 would probably be enough for my purposes.
All the best,
Nicklas
hut...@chem.uzh.ch
unread,
Jun 16, 2021, 4:44:45 AM6/16/21
Reply to author
Sign in to reply to author
Forward
Sign in to forward
Delete
You do not have permission to delete messages in this group
Copy link
Report message
Sign in to report message
Show original message
Either email addresses are anonymous for this group or you need the view member email addresses permission to view the original message
to cp...@googlegroups.com
Hi
I don't have experience with changing that parameter. You will have
to do the tests. Probably there will be a relation to the integration
accuracy on the grid. I would suggest to go for larger cutoffs, but
also this will have to be tested.