You say that the flipping difference (p - n) is 0 in pre-edge and far post-edge regions, which is as it should be, but then say that the
slopes of p- and n- post-edges, considered separately, are different. I must be misunderstanding because those two statements would seem to be
inconsistent. I wonder if the sensitivity of the TEY changes with magnetic field because of the effect of the field on the trajectories of
the outgoing electrons, which would explain the differing curves. A possibility - if you divide the p-XAS by n-XAS, do you get something
which is a smooth curve everywhere but where MCD is expected? Does that curve match in pre- and far post-edge regions? If that miracle occurs,
then perhaps you could fit that to a polynomial, except in the MCD region, then divide the p-XAS by that polynomial, to remove the effect of
the differing sensitivities.
There are people here at ALS, such as Elke Arenholz
The question of whether it is appropriate to use flattened data for quantitative analysis is something I've been thinking about a lot recently. In my specific case, I am analyzing XMCD data at the Co L-edge. To obtain the XMCD, I measure XAS with total electron yield detection using a ~70% left or right circularly polarized beam and flip the magnetic field on the sample at every data point. The goal then, is to subtract the XAS measured in a positive field (p-XAS) from XAS measured in a negative field (n-XAS) and get something (the XMCD) that is zero in the pre-edge and post-edge regions. I often find that after removal of a linear pre-edge, the spectra still have a linearly increasing post edge (with EXAFS oscillations superimposed on it), and the slope of the n-XAS and p-XAS post-edge lines are different. In this case simply multiplying the n-XAS and p-XAS by constants will never give an XMCD spectrum that is zero in the post edge region. There is then some component of t
he
XAS background that is not accounted for by linear subtraction and multiplication by a constant. It seems to me that flattening could be a good way to account for such a background. So is flattening a reasonable thing to do in a case such as this, or is there a better way to account for such a background?
Thanks, George
On Wed, May 15, 2013 at 11:41 AM, Matthew Marcus
mailto:mamarcus@lbl.gov> wrote: The way I commonly do pre-edge is to fit with some form plus a power-law singularity representing the initial rise of the edge, then subtract out that "some form". Now, that form can be either linear, linear+E^(-2.7) (for transmission), or linear+ another power-law singularity centered at the center passband energy of the fluorescence detector. That latter is for fluorescence data which is affected by the tail of the elastic/Compton peak from the incident energy. Whichever form is taken gets subtraccted from the whole data range, resulting in data which is pre-edge-subtracted but not yet post-edge normalized. The path then splits; for EXAFS, the usual conversion to k-space, spline fitting in the post-edge, subtraction and division is done, all interactively. Tensioned spline is also available due to request of a prominent user. For XANES, the post-edge is fit as previously described. Thus, there's no distinction made between data above and below E0 in XANES, whereas there is such a distinction in EXAFS. mam
On 5/15/2013 8:25 AM, Matt Newville wrote:
Hi Matthew,
On Wed, May 15, 2013 at 9:57 AM, Matthew Marcus
mailto:mamarcus@lbl.gov> wrote: What I typically do for XANES is divide mu-mu_pre_edge_line by a linear function which goes through the post-edge oscillations. This division goes over the whole data range, including pre-edge. If the data has obvious curvature in the post-edge, I'll use a higher-order polynomial. For transmission data, what sometimes linearizes the background is to change the abscissa to 1/E^2.7 (the rule-of-thumb absorption shape) and change it back afterward. All this is, of course, highly subjective and one of the reasons for taking extended XANES data (300eV, for instance). For short-range XANES, there isn't enough info to do more than divide by a constant. Once this is done, my LCF programs allow a slope adjustment as a free parameter, thus muNorm(E) = (1+a*(E-E0))*Sum_on_ref{x[ref]__*muNorm[ref](E)}. A sign that this degree of freedom may be being abused is if the sum of the x[ref] is far from 1 or if a*(Emax-E0) is large. Don't get me started on overabsorption :-) mam
Thanks -- I should have said that pre_edge() can now do a victoreen-ish fit, regressing a line to mu*E^nvict (nvict can be any real value).
Still, it seems that the current flattening is somewhere between "better" and "worse", which is unsettling... Applying the "flattening" polynomial to the pre-edge range definitely seems to give poor results, but maybe some energy-dependent compromise is possible.
And, of course, over-absorption is next on the list!
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