Dear Bruce,
thank you very much for your quick and thorough answer.
I used to do I/V-LEED to do structural characterization of surfaces and
there it was pretty common to get stuck in local minima. So my fear was
that this negative R-factor corresponds to a local minimum and that
there is actually a better minimum with reasonable values.
I have noticed that there is some dependence of the fitting results on
the start values used. Also, in one of the very useful videos of you
giving talks about EXAFS you mentioned that the Levenberg-Marquardt
algorithm can end up in a local minimum. However, I'm starting to get
the feeling that this is much less of a problem in EXAFS analysis than
in my previous field. I guess one of the reasons might be that a fit in
IFEFFIT/Artemis takes seconds whereas a single datapoint (i.e. a fully
dynamical scattering calculation for one trial structure) in I/V-LEED
would take ~30 mins.
After having done some systematic variation of parameters with a little
script I wrote (more on that in the respective thread) I'm starting to
realize that the hyperspace in EXAFS fitting seems rather shallow (at
least for my samples).
I don't think that the reason for the physically unreasonable results is
a systematic error, as I have a number of different samples measured in
one beamtime and some of them are fine while others have varying issues
(mostly with too high/low sigma^2 and it's correlation with N).
With kind regards
Felix
On 17/06/2017 00:10, Bruce Ravel wrote:
Felix,
When you fit your EXAFS data using Artemis + Ifeffit or Larch, you are
using a Levenberg-Marquardt non-llinear, steepest descent algorithm.
The fit does kn ow anything /at all/ about what you are trying to do.
It doesn't know what a sensible value for sigma^2 or any other
parameter is. All it knows is that you have data and a model that you
are throwing at the data.
Armed with data and model, the algorithm optimizes the parameters that
you have flagged as the variables. It changes those values until it
makes the sum of the paths look as much like the data as possible.
It's goal is to make the red line look like the blue line. That's it.
That's all it does. That's how sigma^2 can come out as a negative
number.
A negative sigma^2 or any other nonsensical parameter doesn't
represent a failure of Artemis. It is information that is useful to
you, the person doing the fit.
A nonsense parameter is trying to tell you about a way that the model
you have proposed does not represent the data that you have measured.
And it is a hint about what changes you need to explore in your model
to more properly represent the data.
An example: suppose you have an unknown oxide phase and you have
reason to believe it is some sort of highly disordered phase. Just to
pull an example out of the air, you might think that your sample is
filled with FeO(OH) when in fact it is filled with FeO. FeO(OH) is
pretty disordered, whereas FeO is rocksalt. If you run Feff on
Feo(OH), you will get a spread of paths at several distances for the
first shell. When you make the fit with the FeO(OH) model, the
structural contribution to the disorder is MUCH higher than in the
actual sample. The fit is likely to use a negative sigma^2 to
counteract that effect.
That's a simple and contrived "explaining example", but it makes the
point (I hope). Artemis didn't fail. The fit is trying to tell you
that you assumptions were not realized in the data.
In short, I agree that your results make no sense, but I suggest that
the problem is that you are making a poor assumption in your fitting
model.
It also might be the case that there is a problem with the measurement
of your data that introduces a systematic error that the fit
compensates for by applying a weird parameter value.
Or maybe you have a sulfide instead of the oxide you were expecting.
Or maybe you ran Feff for the Pt K edge rather than the Pt L3 edge.
(Oops! I actually do that with embarrassing frequency)
Or something else I haven't thought of
HTH,
B
On 06/16/2017 02:09 AM, Felix E. Feiten wrote:
Dear all,
I have the following problem:
In some fits using Artemis (Demeter 0.9.25) I will get negative
values for parameters where it makes no sense at all.
For example, when trying to fit two first shell paths, Pt-Pt and
Pt-O, for a Pt nanoparticle,
sigma^2 for the Pt-O path becomes negative.
Obviously, sigma^2 has to be a positive number.
My questions:
1. Why does the fit algorithm do this?
2. What can I do to avoid this?
I know that there are most likely significant problems with my fit if
this behaviour occurs.
As far as I know it's possible to impose restrictions in Artemis and
if anyone could point me
towards a tutorial explaining how to implement restrictions that
might be a first step in the right direction.
Currently, the chapter "Constraints and restraints" in the Artemis
documentation is "Coming
