A UHRF Data Reduction Example

This section provides an outline of the steps used to reduce UHRF data taken for the source 1Sco, observed by Ted Snow on 18th June 1997.

Observing information

Data Reduction Summary

1. Start up Figaro:
   

   unix: figaro
   unix: setenv D /vaxdata/ccd_2/970618
   unix: cd /data/sse/1/jmc/970618
   figaroy: figdisp
   figaro: soft/xdisp
   

2. Examine file headers:

   figaro: fitskeys

3. Reorientate the ThAr arc frame:

   figaro: rotate
   figaro: irevx.

   The standard orientation for Figaro files is for the dispersion direction to be aligned horizontally with wavelength increasing from left to right and from bottom to top.

4. Reorientate the object frame in the same way.

5. Form the median bias frame and re-orientate it using

   figaro: medsky, rotate, irevx
   output median bias frame = medbiasrx

6. Check the bias statistics:

   figaro: istat
   This gave a mean = 167 and sigma = 1.32

7. Subtract bias from object and arc:

   figaro: isub soc28rx medbiasrx sco28rxb
   figaro: isub arc30rx medbiasrx arc30rxb

8. Examine object frame:

   Note that the order is tilted but the spectral lines are parallel to the edge without the curvature typical of UCLES spectra. This is because the cross-dispersers for UHRF are located AFTER the echelle.

9. If necessary straighten the spectrum:

   figaro: sdist
   figaro: cdist

10. Clean the object frame to remove cosmic rays.
    figaro: bclean scro28rxb sco28rxbc .

11. Flat field the data:

    Form the median flat field and re-orientate it as for the bias frames:

    Output flat field frame = medflatrx

    Subtract the median bias frame from the median flat field frame:

    figaro: isub medflatrx medbiasrx.

    Smooth ff frame:

    figaro: ixsmooth
    output = medflatsrxbs

    Divide the flat field by smoothed flat field:

    figaro: idiv medflatsrxb medflatsrxbs flatf

    Divide the object frame by the final flat field frame:

    Output = sco28rxbcf

12. Sky Subtraction: The measured signal = source + noise + bias + sky. To fit the sky level, use a region on the frame which is outside of the slicer.

    Take spatial cut for one pixel:

    figaro: ystract

    Determine mean sky level:

    figaro: istat

    Subtract sky level pixel by pixel from object frame:<

    figaro: icsub
    Output = scorxbcfs.

13. Estimate the signal/noise: To convert counts to photons - multiple by the gain factor. For the TEK1024 with a SLOW readout speed the gain factor = 1.36.

    figaro: icmult
    Output = scorxbcfsm

    Estimate count rates:

    figaro: extract
    For single y pixel - max counts = 60 so S/N ~ 8 per pixel

    Do extraction over a suitable range of rows (used 70 to 210):

    figaro: extract

    plot spectrum - counts = 5000 so S/N ~ 70

    Plot the extracted spectrum:

    figaro: splot.

    For this source - the absorption was saturated in line centre - so counts in the line centre were zero as expected.

14. Wavelength Calibration: Make sure that initial arcs have at least two well identified lines. If necessary take several stepped frames and append/overlap. Then do fit to intermediate lines. Once have sufficient lines :

    * Set wavelengths of identified lines in the THAR spectrum:

    figaro: arc.

    Hit Q to quit the arc routine and enter filename for calibrated arc spectrum

    Copy wavelength calibration from arc frame to object frame:

    figaro: xcopy

15. Linearise spectrum: It is not really necessary to linearise UHRF spectra since the wavelength range covered is so small. If you want to do this:

    figaro: scrunch
    

    set minimum and maximum lambdas for the ends of the spectrum and the desired number of channels.