[Ifeffit] background subtractions

[Scott Calvin]

Hi all,

My two cents, FWIW:

I prefer not to use the background found by Artemis in final fits 
(well, actually I'm still using FEFFIT, but I think the issues Bruce 
discussed haven't changed).

The correlations reported by IFEFFIT or FEFFIT, while very useful, 
only really probe the area of fitting space right around one pair of 
variables. In complex fits, there are often multiple minima in 
fitting space, or nonlinear effects that involve more than one set of 
variables. Just because a background subtracted during the fitting 
process doesn't report a high correlation doesn't necessarily mean 
that it hasn't influenced the fit. I  came up again this issue when I 
was doing multiple-dataset fits on a temperature series; if I let the 
background refine in this way for the spectrum at each temperature, I 
sometimes destroyed temperature trends in things like lattice 
parameters that showed up perfectly well without the second 
background subtraction...and the effect of the background did not 
show up in the reported correlation coefficients.

In terms of the "not cheating" argument (the number of knots is the 
same as the number of independent points), I need to be convinced 
that it is really OK on data that has already been through Athena. 
After all, haven't two splines been subtracted from the data? So why 
doesn't that gobble up twice as many of the independent points?

Currently, I do use the background feature during the fitting 
process, because it does help guide me as to where rbkg should go in 
the way Bruce describes. But then I run AUTOBK (basically the routine 
used by Athena) with the rbkg at the value I've determined is 
appropriate and leave it at that. That way, I'm comfortable that rbkg 
has been chosen in some rational, defensible way (the big selling 
point for using Artemis to further refine the background), but I 
don't have to think about what it means to use a two-pass background 
subtraction.

--Scott Calvin
Naval Research Lab
Code 6344
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