Re: double-wide sampling with soft-core

From: Floris Buelens (floris_buelens_at_yahoo.com)
Date: Thu Jan 22 2009 - 04:58:40 CST

> No, formally this is correct. Numerically though, samples of dE are

> correlated, so you get pretty much the same statistics by storing it
> every 10 timesteps or so. You could try it - downsampling dE data from
> a calculation, and seeing how far you can go without changing the
> result.

I agree with Jerome - with linear potential scaling you can trivially extrapolate at any timestep the potential energy for any value of lambda, but as I think you already realised, you don't benefit from the cumulative averaging of the FEP dG that NAMD performs for the comparison value lamda2. You can do this yourself by post-processing; you could sample less frequently than every step, in which case you have to weigh up discarding lots of your data against the fact that the intervening values will be highly correlated. And as you imply, this approach is anyway no longer applicable when using soft core vdW.

> Again, you are right: actually this is now implemented. The problem
> is, I think, that the user's guide in CVS has not yet been updated to
> document this. There is some work being done on that side...

Actualy there's no provision for a second comparison lambda (a 'lambda3') yet, and to my knowledge all the key functionality is already documented in CVS.
I agree that double-wide sampling / Bennett acceptance ratio estimatation needs two independent comparison lambdas: the 'forward' work to the 'next' point in the transformation and the 'reverse' work to the 'previous' point in the transformation. A scheme that only calculates work from λ to λ+δλ and λ to λ-δλ appears to me to assume linear spacing of intermediates in the transformation, which for the work I do is never true...

best regards,

Floris

      

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