# [AMBER] ABMD with multiple walkers

From: Qinghua Liao <scorpio.liao.gmail.com>
Date: Sat, 26 May 2018 01:00:01 +0200

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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Received on Fri May 25 2018 - 16:30:03 PDT
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