On Sunday, 26 January 2014 21:02:58 UTC+1, Christoph Junghans wrote:
>
> 2014-01-26 Jakub Krajniak <[email protected] <javascript:>>: 
> >> (...) 
> >> 
> >> > 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. 
> The theory behind Boltzmann inversion assumes a Boltzmann distribution 
> (NVT). 
> Which thermostat are you using? For Espresso++ Langevin thermostat 
> should to the same as stochastic dynamics. 


Actually I have moved to Gromacs to not complicate too much. When I look on 
the
temperature, it is kept correctly during the simulation (with sd 
integrator). 

The strange thing is with rdfs. In the attachment there is a tgt and .new 
A-A.dist 
from step_001. The shapes seem similar but the y-values are different. In 
the next
steps the rdfs look totally different (and the .conv value rise enormous).

Jakub

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Attachment: A-A.dist.tgt
Description: Binary data

Attachment: A-A.dist.new
Description: Binary data

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