# Re: [AMBER] ABMD with multiple walkers

From: Feng Pan <fpan3.ncsu.edu>
Date: Sat, 26 May 2018 22:16:09 -0400

Hi, Qinghua

the selection score is the ratio of the replica selection weight over the
total weight,
so if you have 8 replicas here, and the score is below 1/8, the walker will
keep
itself. If the score is between 1/8 and 2/8, the walker will be copied to 2
walkers, as
shown like => 2 walkers.

When the entropy is above the threshold, the selection will be calculated,
but if
every selection score is below 1/8, there will be no resampling, every
walker will
be kept just itself.

Best
Feng

On Fri, May 25, 2018 at 7:00 PM, Qinghua Liao <scorpio.liao.gmail.com>
wrote:

> Hello Amber developers,
>
> Currently, I am running ABMD with multiple walkers, but I have some
> questions regarding interpreting the output.
> Here is my input for the multiple walkers:
>
> selection_freq = 500
> selection_constant = 0.00001
> selection_epsilon = 0.0
>
> And here are some output from the simulations:
> #
> NFE : selection score for walker 1 is 0.930991 / 7.992304 = 0.116 => 0
> walker(s)
> NFE : selection score for walker 2 is 0.881570 / 7.992304 = 0.110 => 1
> walker(s)
> NFE : selection score for walker 3 is 0.945704 / 7.992304 = 0.118 => 1
> walker(s)
> NFE : selection score for walker 4 is 0.951837 / 7.992304 = 0.119 => 1
> walker(s)
> NFE : selection score for walker 5 is 0.973335 / 7.992304 = 0.122 => 1
> walker(s)
> NFE : selection score for walker 6 is 1.103148 / 7.992304 = 0.138 => 1
> walker(s)
> NFE : selection score for walker 7 is 0.967854 / 7.992304 = 0.121 => 1
> walker(s)
> NFE : selection score for walker 8 is 1.237866 / 7.992304 = 0.155 => 2
> walker(s)
> NFE : Selection entropy 0.005597 is greater than threshold 0.000000
> NFE : Selection resampling : new 1 comes from 2
> #
> #
> NFE : selection score for walker 1 is 1.042757 / 7.817606 = 0.133 => 1
> walker(s)
> NFE : selection score for walker 2 is 0.956335 / 7.817606 = 0.122 => 1
> walker(s)
> NFE : selection score for walker 3 is 0.775833 / 7.817606 = 0.099 => 1
> walker(s)
> NFE : selection score for walker 4 is 0.906343 / 7.817606 = 0.116 => 1
> walker(s)
> NFE : selection score for walker 5 is 0.938005 / 7.817606 = 0.120 => 1
> walker(s)
> NFE : selection score for walker 6 is 0.851424 / 7.817606 = 0.109 => 1
> walker(s)
> NFE : selection score for walker 7 is 1.232238 / 7.817606 = 0.158 => 1
> walker(s)
> NFE : selection score for walker 8 is 1.114672 / 7.817606 = 0.143 => 1
> walker(s)
> NFE : Selection entropy 0.009795 is greater than threshold 0.000000
> #
>
> How should I understand the selection score, how is it calculated? What
> does "=>0 (1,2) walker(s)" mean?
> For the first assessment, the selection entropy is 0.005597,
> which is greater than the threshold 0.0, and then there is a selection
> resampling (new 1 comes from 2). For the second
> assessment, the selection entropy is also greater than the threshold,
> but there is no resampling. Why is this different?
>
> I appreciate any of your responds.
>
>
> All the best,
> Qinghua
>
> _______________________________________________
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> AMBER.ambermd.org
> http://lists.ambermd.org/mailman/listinfo/amber
>

```--
Feng Pan
Ph.D.
North Carolina State University
Department of Physics
Email:  fpan3.ncsu.edu
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Received on Sat May 26 2018 - 19:30:01 PDT
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