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Chapter 9
Special Cases and Frequently Asked Questions

In this chapter, we provide a few references and examples of non-standard data types which highlight particular, but not frequently utilized, capabilities of FUSE. This information is primarily relevant to "Advanced" users even though "Intermediate" users might find it useful. This information might not be highly relevant to the "Casual" user.

9.1 Special Cases

9.1.1 Extended Sources

Table 9.1 gives the measured full widths of Ly β airglow lines in the LiF1A segment. An extended source in the HIRS aperture has nearly the same resolution as a point source. It is a little less because of the astigmatic curvature orthogonal to the dispersion, which degrades the overall resolution. As with point sources, the exact resolution depends on wavelength and segment.

Table 9.1: Extended Source Resolutiona
Aper. Δ v
(km s-1)
Δ λ
LWRS 106 0.362
MDRS 30 0.102
HIRS 20 0.068
a For Lyβ on LiF1A

When interpreting observations of very large extended sources (such as the Cygnus Loop or large reflection nebulae), it is also important to keep two additional facts in mind. First, for TTAG data there may be useful information in apertures other than the one specified by the observer. Spectra from these other apertures will not be extracted by CalFUSE by default, and one must return to the IDF file to extract these spectra. Second, to interpret the data from the other apertures, one needs to know their physical relationships (see Table 2.1 and Fig. 2.2). Together with the aperture position angles, these values can be used to determine the locations of the other apertures on the sky. Examples of the analysis of extended source observations can be found in the papers by Blair et al. (2002), Dixon et al. (2006), Sankrit et al. (2007a) or Ghavamian et al. (2007).

9.1.2 Time Variable Sources

Due to its ability to obtain time-tagged data and to the rapid and sequential accumulation of histogram spectra, FUSE could technically be used to study time-variable phenomena. The interested reader can find examples of time variability studies in the following references: Kuassivi & Ferlet (2005), Massa et al. (2000) and Prinja et al. (2005). Note that these studies were all performed before the introduction of the IDF files; one would now use them as the natural starting point for time variability studies. Remember that target motion in and out of one of more channels could mimic time-variability (see Section 2.3). It is therefore strongly recommended that users examine the count-rate plots (see Section before claiming detection of intrinsic source time variability.

9.1.3 Earth Limb Observations

In certain cases, FUSE was intentionally pointed toward the Earth's limb, in order to obtain airglow spectra. (This was avoided in normal FUSE science observations.) These observations are part of programs M106 and S100. These specialized airglow observations are accessible using a separate interface under the FUSEMAST main page. Users can download those data at the following link:

9.1.4 Background Limited Observations

Extremely faint extended and point sources often require additional analysis, in particular to perform the most careful background processing and subtraction. Fechner et al. (2006) provide an example of detailed analysis of a very faint point source, while Sankrit et al. (2007b) and Danforth et al. (2002) examine the problems encountered with faint extended sources.

9.1.5 Moving Targets

Moving targets were also observed by FUSE during its mission. Detailed descriptions of the data acquisition and data analysis specific to moving targets can be found in papers by Feldman et al. (2002) and Weaver et al. (2002).

9.2 Frequently Asked Questions

Q: What is the best way to combine spectra of bright targets?
A: For bright targets, the goal is to optimize spectral resolution, so you will want to cross-correlate individual exposures on narrow absorption lines before combining the spectra.For TTAG exposures of moderately-bright objects, it is occasionally beneficial to splitlong exposures into shorter time segments and coalign the individual segments before re-combining.

Q: What is the best way to combine spectra of faint targets?
A: In this case, it is best to optimize the background model, so you will want to combine IDF files for the individual exposures prior to extracting the spectrum.

Discussions regarding both techniques (bright and faint targets) are provided in the document "FUSE Tools in C" at

Q: How do I improve the background subtraction at the short-wavelength end of the SiC1B channel?
A: The LWRS spectrum of the SiC1 channel falls very near the edge of the detector (see, for example, Fig. 4.1), where the background rises steeply. The scattered-light model used by CalFUSE, when scaled to match the counts in the center of the detector, does not accurately reproduce the background near the edge, and can cause an over-subtraction of the background, with the shortest wavelengths on SiC1B being most susceptible. In principle, one could use the dark exposure data taken near the end of FUSE operations to perform a custom background fit, but this would require specific expertise and would be a difficult task. In practice, one can compare the data from the SiC1B and SiC2A channels for consistency. Only very faint targets should have a concern with this issue.

Q: What if the stim pulses are missing for one or more of my exposures?
A: In most cases the STIM pulses were turned on briefly at the beginning and end of each exposure. However, some exposures don't include any STIMs at all. If that's the case, the cf_thermal_distort routine of CalFUSE will output a warning message to the trailer file (see Appendix C of this document). Since the thermal correction of the detector pixel scale is based on the STIM positions, CalFUSE has to make an approximate correction in these cases, based on typical STIM positions. This correction will only be approximate, and thus the wavelength scale may be slightly incorrect for such exposures. The errors will be largest at times when the temperatures were changing rapidly, such as after the detector high voltage state has changed. Unless you are really interested in the most accurate wavelengths possible, you should not have to worry about this. Alternatively, one could choose to drop such exposures from the total observation when the individual exposures are combined to assess any possible impacts.

Q: How do I find and retrieve the special case of bright-earth observations?
A: There are two types: (1) The S100 program, executed in the fall of 2007, obtained several weeks of downward-looking airglow spectra. (2) Throughout the mission (particularly early on), we obtained approximately 1300 bright-earth exposures during earth occultations of some 200 targets. All of these data have the program ID of the science program and target, but have exposure numbers of 901 and above (see Chapter 4). These data can be retrieved as special cases from the MAST archive.

Q: How do I extract spectra from non-target apertures?
A: This can only be done for TTAG mode data and the exact technique depends on whether the new target is an extended or a point source:

Extracting Spectra from Non-Target Apertures: Extended Sources

  1. Run the CalFUSE pipeline normally. Delete extracted spectra and BPM files.

  2. Use cf_edit or modhead to modify background regions of the first IDF file. (Since idf_combine copies the header from the first input file into the output file, you need modify the background regions only once.)

  3. Use modhead (or some other tool) to change these keywords in all of the IDF files:
    SRC_TYPE Change point source to extended source if appropriate (PC to EC, PE to EE)
    If the original target is an extended source, then you need not modify SRC_TYPE.
    APERTURE Change to the desired aperture.

  4. Run cf_bad_pixels on all IDF files to generate bad-pixel map for the new aperture.

  5. Combine IDF and BPM files using idf_combine and bpm_combine.

  6. Run cf_extract_spectra on combined file.

Extracting Spectra from Non-Target Apertures: Point Sources

  1. You must modify the raw data files before running the pipeline.

  2. Change the header keywords (step 3 above) in the raw data files.

  3. Run the pipeline on each exposure. Delete extracted spectra.

  4. Modify the background regions in the first IDF file.

  5. Combine IDF and BPM files.

  6. Run cf_extract_spectra.

Q: How to learn how to get the most out of the FUSE IDF files?
A: The best introduction to the IDF files is probably the User's Guide to cf_edit, along with the discussion of the file format provided in Chapters 4 & 5 and Dixon et al. (2007). If heavy data processing is anticipated, "FUSE Tools in C" documentation should be consulted as well.

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