Dear Ifeffit members,

I have some fundamental questions regarding noisy data, and I am wondering how to tell whether the data quality worth doing Fourier transformation/EXAFS fitting or not.

For example, the attached MnO chi(k) data becomes noisy from 7 Å-1 when it was measured up to 12 Å-1. The deglitching (left: red -> blue) mitigated the strong “dips” but the high-k end still has too much noise. I practiced the FT and fitting the 1^st and 2^nd shells by using the lower part. But My questions here are:

1) How noisy would be “too noisy”? Like the data between 8 and 10 Å-1 in the attached file, can they still be included for the FT?

2) We can choose the high-k end based on the signal-to-noise ratio, but to what extend? With data being noisy from even 5 or 6 Å-1, can they still be used?

3) For fitting the 1^st and 2^nd shells, I still lack of clear understanding how the high-k portion can influence. If I measure a set of samples, and one of them has much noisy data so a shorter k-range is picked up for background subtraction and FT. In this case, can I still consider the change or evolution in the fitted parameters “systematic”?  

Thank you in advance,

Best regards,

Yang