# Re: ABF

From: Giacomo Fiorin (giacomo.fiorin_at_gmail.com)
Date: Thu Apr 04 2013 - 11:24:57 CDT

Those are two extremes: like in many situations, the best choice lies in
the middle.

fullSamples is not the number of steps after which convergence is
guaranteed on one bin of the PMF (and it shouldn't be).

In case I, you clearly don't have a very accurate estimate of the biasing
force after fullSamples steps. But if you run for longer, your statistics
improves, and eventually you converge.

In case II, your estimate of the biasing force is very accurate, but you
barely cover the entire range of the reaction coordinate once. Ideally,
you want to sweep this range multiple times.

If you're concerned that case I is too inaccurate and case II is too slow,
how about choosing a fullSamples that is the geometric average of the two
cases (i.e. fullSamples = 10000)?

Giacomo

On Thu, Apr 4, 2013 at 11:53 AM, karthik kumar <karthik3327_at_gmail.com>wrote:

> Hi NAMD users,
>
> I'm very much new to ABF method. I would like to know few things.
>
>
> *case I* : fullsamples 100
> width 0.1 A
>
> reaction coordinate length 10 A
>
>
> so there will be 100 bins approx and it will take roughly
> 100*100 timesteps to scan the full reaction coordinate..
>
> At this point , PMF will no be converged. For the convergence of PMF we
> will be extending the trajectory
>
>
> After some timesteps , say 100 million time steps PMF has converged
>
> *case II* : fullsamples is 1 million timesteps
>
> width 0.1 A
>
> Approximately after 100 miliion timesteps , full reaction coordinate is
> reached.
>
> Can I expect to get converged PMF similar to PMF obtained from case I
>
>
>
> comparing case I and case II.. which has advantage and why??
>
>
> Thanks,
>
> Karteek Kumar
>

This archive was generated by hypermail 2.1.6 : Wed Dec 31 2014 - 23:21:05 CST