2014-01-26 Jakub Krajniak <[email protected]>:
> On Sunday, 26 January 2014 21:02:58 UTC+1, Christoph Junghans wrote:
>>
>> 2014-01-26 Jakub Krajniak <[email protected]>:
>> >> (...)
>> >>
>> >> > 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).
1.) Your target distribution is really noisy, which will lead to a
very noisy initial potential, maybe a bigger spacing would help.
2.) It seems the first update makes the A-A potential too attractive,
hence you get the really high peak at x=0.42, maybe you will need to
scale the update with a factor like 0.1 (postupd scale).

Also it is not uncommon that the convergence take a couple of
iterations until it starts to decrease continuously.

Christoph

>
> Jakub
>
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-- 
Christoph Junghans
Web: http://www.compphys.de

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