# [Ifeffit] k range

Kelly, Shelly D. SKelly at anl.gov
Tue Apr 27 16:03:27 CDT 2004

```Hi Steven,

> On Tue, 27 Apr 2004, Steven Sangyun Lim wrote:
>
> > My question is how low can I set the k range? Is there any minimum
> > range for reliable result? Please let me get out of this dilemma...
>

Scott and Matt both answered this question differently than I would.  I
guess I am very practical. If I was asking this question I would want a
set of rules that would help me figure it out the k-range.  So here one
way to do that.

1)  Look at the data in Athena to determine a good k-range to use. Here
is how.
1a)  As Matt suggested find a node in the chi(k) data that is around 3
inverse angstroms and set that to the kmin value.
1b)  make about 6 copies of the chi(k) data set, all with the same kmin
value.  All the other FT values should be as you used in Artemis.
(k-weight, window, dk)
1c)  highlight each data set choosing a larger and larger node for kmax.
Start really safe value around 8 inverse angstroms.  Then pick the next
node for the next copy and so forth using up all the data.  For example,
the first copy of the data set has a k-range [3.2 to 8.2] the next copy
has k-range [3.2 to 9.3] and so forth....until the last has a k-range of
[3.2 to 14]
1d)  Plot the FT of the first three data sets all together (using the
purple buttons to select them and the purple R button).  Look at the
data with the magnitude and the real or imaginary part.  With a small
k-range the FT signal will be very smooth curve in the magnitude, real
and imaginary parts.  You will tend to see two types of changes as you
increase the k-range.  1) peaks will become more resolved, larger
amplitude and thinner. --this is a good kind of change 2)  eventually
you will see noise in the FT of the data.  The noise will look like high
frequency pulses in the real and imaginary part of the spectra all over
in R.  From one data set to the next random signals will appear and
disappear as you include noise in the data.  --this is the bad kind of
change.  Keep comparing three data sets, drop the first one then add
another with slightly larger k-range.  You should be able to find the
cross over from the good kind of a change to the bad kind of a change.
1e) By using this comparison you should be able to choose a k-range that
is large but not too large.  It should result in a conservative k-range
to use as a starting point for your modeling.  Be careful about the
k-weight that you use when you make this comparison.  It needs to be the
same that you are using in Artemis to model the data.  Larger k-weights
will have smaller "good" k-ranges for the data.

2) Pull your data into Artemis.  Use the good k-range that you
determined from step one.
2b) Determine a model that works and look at the results including the
uncertainties.
2c) Increase the k-range and compare the results.  Try to decrease kmin
and increase kmax.  Do one thing at a time and see how the results vary.
You will need to make a lot of comparisons, see how your results and
uncertainties change as you adjust these values.
2d)  Decide on a k-range that gives you the "best" results.

3) You may want to go back into Athena and use a standard to adjust the
low k region of the chi(k) data, depending on how your FT looks at low