> > (...) > And the convergence, I have add <post_add>convergence</post_add> so that > I > > can measure the convergence. > > 4. What should be the optimal case for the convergence? > > What I am getting: (step_001: ~300, step_002: ~232, step_003: ~133) and > then > > suddenly for step_004 it is ~8000. > > There was one step where the convergence was around 90.. but I run it > for > > 100 steps and I don't see convergence at all. > > (I used the <initial_configuration>laststep option). > It seems something went wrong here, have a look at the different > distributions to see if one of them is completely off. > If so, you might need to scale the update and/or introduce an update > cycle in do_potential. > > I have to ask about one more thing. I have noticed that when I am doing the cg simulation in NVE then the differences between target and new rdf are very small (well question is how to judge it, but it is around ~0.1). On the other hand the temperature in such simulation is very huge (I am running the atomistic one in in 298K with 1.0 pressure). If I try to turn on the thermostat to keep the temperature in average constant then the differences in rdf are not stable and well again does not lead to some convergences. What should be a correct approach? I saw in the tutorials that the cg simulation are done by using the stochastic dynamics in the desire temperature. I don't understand then why I got so strange results.
Other thing, what is exactly the purpose of update cycle in do_potential? Best, Jakub -- You received this message because you are subscribed to the Google Groups "votca" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/votca. For more options, visit https://groups.google.com/groups/opt_out.
