[Ifeffit] Re: Estimating error in XAS

[Scott Calvin]

In the anecdotal category, I've seen some fairly bizarre high-r 
behavior on beamline X23B at the NSLS, which I tentatively attribute 
to feedback problems. That line, as many of you know, can be a little 
pathological at times. I've also collected some data to examine this 
issue on X11A, a more conventional beamline, but have never gotten 
around to looking at it--I hope to soon.

In any case, I don't really understand the logic of averaging scans 
based on some estimate of the noise. For that to be appropriate, 
you'd have to believe there was some systematic difference in the 
noise between scans. What's causing that difference, if they're 
collected on the same beamline on the same sample? (Or did I 
misunderstand Michel's comment--was he talking about averaging data 
from different beamlines or something?) If there is no systematic 
changes during data collection, then the noise level should be the 
same, and any attempt to weight by some proxy for the actual noise 
will actually decrease the statistical content of the averaged data 
by overweighting some scans (i. e. random fluctuations in the 
quantity being used to estimate the uncertainty will cause some scans 
to dominate the average more heavily, which is not ideal if the 
actual noise level is the same). If, on the other hand, there is a 
systematic difference between subsequent scans, it is fairly unlikely 
to be "white," and thus will not be addressed by this scheme anyway. 
Perhaps one of you can give me examples where this kind of variation 
in data quality is found.

So right now I don't see the benefit to this method. Particularly if 
it's automated, I hesitate to add hidden complexity to my data 
reduction without a clear rationale for it.

--Scott Calvin
Naval Research Lab
Code 6344

Matt Newville wrote:

>
>I'd assumed that vibrations would actually cause fairly white noise,
>though feedback mechanisms could skew towards high frequency. Other
>effects (temperature/pressure/flow fluctuations in ion chamber gases
>and optics) might skew toward low-frequency noises.  I have not seen
>many studies of vibrations, feedback mechanism, or other
>beamline-specific effects on data quality, and none discussing the
>spectral weight of the beamline-specific noise.
>
>On the other hand, all data interpolation schemes do some smoothing,
>which suppresses high frequency components.  And it usually appears
>that the high-frequency estimate of the noise from chi_noise() or
>Feffit gives an estimate that is significantly *low*.
>
>Anyway, I think using the 'epsilon_k' that chi_noise() estimates as
>the noise in chi(k) is a fine way to do a weighted averages of data.
>It's not perfect, but neither is anything else.
>
>--Matt
>
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