SMURF update (June 4th 2010)

We've been making incremental changes to SMURF over the last few weeks so here are a few highlights that have not been covered in other blog entries.

• We've updated the extinction correction parameters that scale from CSO to the relevant filter to use the number just calculated by Jessica Dempsey. You can override these values by setting ext.taurelation.filtname in your map-maker config files to the two coefficients "(a,b)" that you want to use (where filtname is the name of the filter). The defaults are listed in $SMURF_DIR/smurf_extinction.def. We have also added a slight calibration tweak to WVM-derived values to correct them to the CSO scale.
• We have changed the calling interface for the sc2clean command so that it now takes a map-maker config file as input rather than individual command line parameters. This should make it easier to compare what the map-maker is doing to what sc2clean is doing.
• Two new (experimental) models have been added to the iterative map-maker. They are slow and they are experimental:
• SMO will do a boxcar smooth to each time series to calculate the low frequency variation. This might be more reliable than using the FLT model if the only aim is to remove low frequencies.
• PLN will fit and remove a plane from each time slice.
• There have been some enhancements to the step finding code so that it not only finds the steps more accurately but can also find correlated steps that occur at the same place for all bolometers.
• The map-maker has a new ast.zero_notlast parameter that can be set to true when used in conjunction with ast.zero_lowhits to disable the final iteration from being forced to zero.

All these changes are available in the 64-bit linux stardev rsync location and also in the most recent Mac Snow Leopard tar ball.

Extinction correction factors for SCUBA-2

Analysis of the SCUBA-2 skydips and heater-tracking data from the S2SRO data has allowed calculation of the opacity factors for the SCUBA-2 450μm and 850μm filters to be determined.

Some background: the Archibald et al (2002) paper describes how the CSO(225GHz) tau to SCUBA opacity terms were determined for the different SCUBA filters. It was assumed for commissioning and S2SRO that the new SCUBA-2 filters were sufficiently similar to the wide-band SCUBA filters that these terms could be used for extinction correction. For reference the SCUBA corrections were:

Tau(450μm) = 26.2 * (Tau(225GHz) - 0.014)

and

Tau(850μm) = 4.02 * (Tau(225GHz) - 0.001)

The JCMT Water vapour radiometer (WVM) now is calibrated to provide a higher-frequency opacity value which has been scaled to the CSO(225GHz) tau. The WVM (not the CSO 225GHz tipper) data was used for this analysis.

The new filter opacities as determined by the skydip data are as follows:

Tau(450μm) = 19.04 * (Tau(225GHz) - 0.018)

and

Tau(850μm) = 5.36 * (Tau(225GHz) - 0.006)

A follow-up post to this will show analysis of the difference applying the new corrections can make to data combined from multiple observations taken in differing extinction conditions.

It is worth noting that if an individual science map and corresponding calibrator observation is already reduced with the old factors (and your source and calibrator are at about the same airmass and if the tau did not change appreciably), any errors in extinction correction should be cancelled out in the calibration.

Applying FCFs to calibrate your data

Calculating SCUBA-2 Flux Conversion Factors (FCF's)

Currently SCUBA-2 reduction software: the pipeline and the PICARD recipes produce three separate FCF values. Details of the PICARD recipes can be found on Andy's PICARD page.

For calibration from point sources the FCFs and NEFD's have been calculated as follows:

1. The PICARD recipe SCUBA2_FCFNEFD takes the reduced map, crops it and runs background removal (and surface fitting parameters are changable in the parameter file).
2. It then runs the Kappa beamfit program on the specified point source. Calibrators such as CRL618, HLTAU, Uranus and Mars are already hard-coded into the recipe. If it is not, then you can add a line to your parameter file with the known flux: FLUX_450 = 0.050 or FLUX_850=0.005 for example. Beamfit will calculate the peak flux, the integrated flux over a requested aperture (30 arcsec radius default), and the FWHM etc.
3. It then uses the above to calculate three FCF terms described below.

FCF (arcsec)

FCF(arcsec) = Total known flux (Jy) / [Measured integrated flux (pW) * (pixsize²)]

which will produce an FCF in Jy/arcsec²/pW.

This FCF(arcsec) is the number to multiply your map by when you wish to use the calibrated map to do aperture photometry.  

FCF(beam)  

FCF(beam) = Peak flux (Jy/beam) / [Measured peak flux (pW)] 

producing an FCF in units of Jy/beam/pW.

The Measured peak flux here is derived from the Gaussian fit applied by beamfit. The peak value is susceptible to pointing and focus errors, and we have found this number to be somewhat unreliable, particularly at 450μm. This FCF(beam) is the number to multiply your map by when you wish to measure absolute peak fluxes of discrete sources.

To overcome the problems encountered as a result of the peak errors, a third FCF method has been derived, where the FCF(arcsec) is taken and modeled with a Gaussian beam with a FWHM equivalent to that of the JCMT beam at each wavelength. The resulting FCF calculates a 'equivalent peak' FCF from the integrated value assuming that the point source is a perfect Gaussian.

FCF (beamequiv)  

FCF(beamequiv) = Total flux (Jy) x 1.133 x FWHM² / [Measured integrated flux (pW) * pixsize²] 

 or more conveniently:  

FCF(beamequiv) = FCF(arcsec) x 1.133 x FWHM² 

where FWHM is 7.5'' and 14.0'' for the 450μm and 850μm respectively. This produces an FCF in units of Jy/beam/pW. 

This FCF(beamequiv) and FCF(beam) should agree with each other, however this is often not the case when the source is distorted for the reasons mentioned above. FCF(beamequiv) has been found to provide more consistent results and it is advised to use this value when possible, in the same way as FCF(beam). 

Methodology for calibrating your data: 

So you have a reduced map for a given date. Each night of S2SRO should have at least one if not more calibrator observations that were taken during the night. A website with this list is currently in the works and I'll add it to the blog when it is completed. For now it is relatively easy to search the night's observations for these. Primary calibrators were Uranus and Mars, and the  secondary calibrators are listed on the SCUBA secondary calibrators page. In addition to these, Arp 220, V883 Ori, Alpha Ori and TW Hydrae were tested as calibrators. Their flux properties were investigated with SCUBA (see SCUBA potential calibrators) .

1. Run your selected calibration observation through the mapmaker using the same dimmconfig as your science data used.
2. Use PICARD's recipe SCUBA2_FCFNEFD on your reduced calibration observation. This will produce information to the screen and a logfile log.fcfnefd with the three FCFs as mentioned above, and an NEFD for the observation. PICARD by default uses fixed FCF's to calculate the NEFD. (450um: 250 and 850um: 750). If you wish to get an NEFD using the FCF calculated for the calibrator add USEFCF=1 to your parameter file. 
3. Take your selected FCF and multiply your map by it using KAPPA cmult.

Things become slightly more complicated if you wish to use PICARD's matched filter recipe to enhance faint point sources. Again see Andy's PICARD page (link above) for details on the matched filter recipe. If you are normalising the matched filter peak, you will need to run this filter over your calibrator image with the same parameters you used for your science map.

Note: You cannot, at this point, use the FCF(beamequiv) number to calibrate your match-filtered data. This number will now be (usually) disproportionate and just wrong. The FCF(beam) value however, should be preserved by this method.  

The peak is truly preserved by this method so two numbers, the FCF(beamequiv) pre-match-filter and the FCF(beam) post-match filter should be close to the same and either of these values can be used to calibrate your match-filtered science map. 

It is also worth noting (though perhaps obvious) that after running the match-filter script in peak-normalisation mode, only the peak flux values (and not the integrated sum over an aperture) will be correct. The reverse is true if using sum-normalisation.