Notes on Fe feature centroid energy

Introduction

This follows up on the discovery by Richard and Brian of a detector gain dependence on livetime fraction. The question is, of course, can we calibrate this well enough to use the data for observing subtle solar effects such as ionization state? I have now checked a couple of the important points and almost have enough information to be able to make a calibration and parameter fits for the shutter-out data at least.

Variation with livetime

The plot below shows G9 data for a two-minute integration on the early phase of the April 21 event. The fitting is as I have been doing it, namely a polynomial fit to the background under the Fe feature, then a Gaussian fit to the feature itself.

A couple of points are worth making. First, the variation shows a good linear fit. The raw data here were binned from 10-msec integrations and so resolve the whole modulation. A view of 5 sec of data at 50 msec binning is in the plot below, so that you can see how the data gaps and livetime variations look.

I think that the linear dependence is a good thing, because in practice we must deal with 4-sec integrations for which the modulation will do whatever it wants to do. The degree of linearity here looks good enough so that there may not be much bias even early on when we had more dead time than we needed. A second point is that the statistics are good, bearing out the relatively low scatter that I was seeing before in all those 2-sec and 4-sec integrations.

Variation with time

We do not know what the feature energy really should be, because it is model-dependent. Thus there is every reason to expect variations as a function of time. Also, of course, the apparent energy of the Fe feature will depend on the gain calibration, which is subject to variations as it is maintained on the basis of incoming data. The plot below shows a set of fits starting with the April 21 event and going on until May 2003. The error bars are a bit hokey. The points refer to the intercept at zero dead time for each fit. Once I have a robust fitting program this could be automated. Some points:

  • The error bars are pretty small for April 21 and one or two other events. This seems to depend mainly upon counting statistics, and it is much worse during decimation level 2 or worse.

  • There does not seem to be much long-term variation resolved here. The points with small error bars all agree pretty well on 6.75 keV. Ignoring error bars completely, the mean is 6.743 keV and the sigma is 0.037 keV.

    Things to be done

  • Look at G8, G6, G4, G3... At first glance there is not much perceptible difference.

  • Look at shutter-in data. I can do this but I want to make sure my fitting is suitable. Recall that we thought that there might be differences in the way the electronics handle shutter-out spectra, where the peak in the pulse-height spectrum is below the fast analysis threshold, and shutter-in data where it is not.

  • (morbid interest) Look at some shutter-out data with huge deadtimes during major flares.


    Hugh Hudson, 13-jul-2003