From: Matthew Ralph Adendorff (mraden_at_mit.edu)
Date: Tue Aug 13 2013 - 11:38:57 CDT
I have a question regarding the fullSamples parameter for Adaptive Biasing Force runs. I am looking to run ABF on some DNA duplexes in explicit solvent and so am concerned about non-equilibrium effects in the runs. When the system enters a bin, the fullSamples parameter sets how many counts must be reached before the bias is applied to that bin. Let's say we have set fullSamples to 1000 (very small for this type of system I know). If the system were to move out of Bin A, after 1000 counts, into an adjacent Bin B under the influence of the bias and then move back into Bin A (perhaps through natural diffusion of the reaction coordinate), would another 1000 counts need to be achieved before more bias is applied? If this is the case, perhaps a blocking method could be used to determine the best value of fullSamples to ensure that the system is in fact equilibrated before more bias is added. If not, is there an effective way, perhaps through checking autocorrelation functions over time, to ensure that non-equilib
rium effects have been accounted for in sampling along the reaction coordinate? I understand how to check when a trajectory has equilibrated, however, I am unsure as to whether a biased trajectory can be treated in a similar fashion as forces are continually being added to the simulation. Any advice/referral to extra reading would be greatly appreciated.
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