Hi Carolyn, I'm not certain I have anything more useful to say about your specific problem than what Robert offered, however I do want to make a more generic comment in response to your earlier post. In that one, you said: "My understanding is that one of the benefits of fitting in R-space is that there is a local minima, whereas in k-space there are many minima." I would say that you are mistaken in this. Regardless of fitting space, the software uses a non-linear, steepest-descent, minimization algorithm. Such non-linear methods are /always/ susceptible to problems finding the correct minimum. There is absolutely nothing about doing a Fourier transform that guarantees a resolution to the problem of finding the correct minimum. In fact, that's often easy to demonstrate simply by using ridiculous initial guesses for fitting parameters. Use an initial guess of 20 for E0 and it is very likely that the fit will go to the wrong place, regardless of fitting space. When engaging in good practice (i.e. /not/ using 20 as the initial guess for E0!), EXAFS is pretty safe against the false minimum problem. Most EXAFS problems involve the sum of a small number of damped sine waves -- there's limited chance of the manifold of the fitting space having a lot of structure around the best fit values. That said, it is certainly possible to come up with interesting, complex fitting models with weird correlations between the variable parameters. There are at least two big benefits of fitting in R space -- indeed, they are the reason that R is the default in Artemis. 1. Specifying the FT range in k and the fit range in R defines the bandwidth of the signal, which allows Artemis to approximate the number of independent points in the data, which is needed for the statistical analysis. 2. When fitting in R space it is completely clear to the user which features in the data are meant to be fitted using a specific set of paths from Feff. That is, the paths used in the fitting model should provide all the Fourier components in the fitting range. When fitting in k-space, it is more challenging to tell by visual inspection when the fit is successful at capturing the details in the data. None of that really addresses your specific problem, but I was a bit worried about leaving you with what I saw as a misconception about how the fitting works in general. Cheers, B On 11/10/2015 03:13 PM, Carolyn Carr wrote:
Hi Robert,
Thanks for your reply. We have done this with standard samples and we see the same thing. And of course, we can tell qualitatively from the XANES that our sample is not 8 coordinate, and not even 6 coordinate.
We have never tried changing the temperature but we can try this the next time we go to SSRL.
We actually do fit multiple scattering features as imidazoles which is one of the things we consider as a strength of Artemis for our basic needs. This is part of why we think this is strange, because putting 8 imidazoles around a zinc seems kind of silly but it likes it. 5 imidazoles and 3 sulfurs and I have an R-factor of 0.2% every time.
If there is non standard multiple scattering that occurs in multiple unrelated proteins from different organisms then we would have no idea what this could be.
Thanks for your comments!
Carolyn Carr _______________________________________________ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit Unsubscribe: http://millenia.cars.aps.anl.gov/mailman/options/ifeffit
-- Bruce Ravel ------------------------------------ bravel@bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage: http://bruceravel.github.io/home/ Software: https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/