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SPIRE instrument and calibration web pages

Observing with SPIRE

Overall Calibration

Calibration files for all three instruments can be obtained here:

The available calibration trees for SPIRE are listed with details here. A .jar file can be downloaded and then read in HIPE as a calibration tree like this:
cal = spireCal(jarFile="spire_cal_5_2.jar")

The calibration trees spire_cal_5_0 and above can be retrieved in HIPE from the HSA using
cal = spireCal(calTree="spire_cal_5_0") etc. The default one can be obtained with cal = spireCal(calTree="spire_cal")

SPIRE photometer

AOT release notes

Photometer point source mode

Photometer scan map mode

Photometer small scan map mode

Calibration

  • SPIRE Photometer Beams: The theoretical and the observed SPIRE photometer beams are available from here. Please read the release note for more details. These are also available in the SPIRE calibration context and can be accessed in HIPE:
cal = SpireCal.getInstance()
beamPLW = cal.phot.refs["BeamProfList"].product.refs[0].product
beamPMW = cal.phot.refs["BeamProfList"].product.refs[1].product
beamPSW = cal.phot.refs["BeamProfList"].product.refs[2].product

  • SPIRE Photometer filter transmission curves: You can access the filter transmission curves (also known as Relative Spectral Response Function, RSRF) from here. These are also available in the SPIRE calibration context and can be accessed in HIPE:
cal = SpireCal.getInstance()
rsrf = cal.phot.rsrf

  • Neptune and Uranus models used for the SPIRE flux calibration: the ESA2 models currently used in the SPIRE calibration are available here.

Data processing

HIPE data processing documentation can all be found at:

Maps

  • Note that SPIRE maps are in units of Jy/beam, and are calibrated in the assumption of a point source having a spectral index equal to -1. To calibrate your data for other cases or convert to e.g. Jy/sr, please refer to the section 5.2 of the SPIRE Observers' Manual.
  • By default, the SPIRE pipeline uses a nšive map-maker. In this case, the error map is simply the standard deviation of all the data points falling into a given pixel. As a consequence, error maps contain increased errors associated with binning data from Gaussian sources, producing a torus shape; this is an artifact of the map-making process.

Tips to re-reduce your data (Under construction)

  • Always remember to update to the latest calibration tree compatible with the HIPE built you are using. Assuming the observation is loaded into HIPE as a variable named obs:
cal = spireCal(calTree="spire_cal")
obs.calibration.update(cal)
  • If the observation you retrieved from HSA has been reduced with SPG v. 2.x or less, than start reprocessing from level 0 (i.e., run again the engineering conversion level 0 -> 0.5)
  • Main issues you might find in your data are: undetected glitches, thermistor or detector jump, bad baseline removal.

SPIRE Fourier-Transform Spectrometer (FTS)

SPIRE spectrometer AOTs

FTS point source mode (sparse)

FTS mapping mode (intermediate, full)

FTS bright source modes

FTS calibration

Important FTS information, including calibration, point source and extended source calibration etc, is available in the SPIRE Observers' Manual, Sections 4.2 and 5.3. These two sections are a must-read for anybody processing SPIRE FTS data.

FTS data processing

  • Telescope RSRFs (daily dark sky observation) are available here for HIPE 5.x and here for HIPE 6.x. These can be used directly in the user processing script. For best results, one should use the telescope RSRF derived from a daily dark taken in the day of the observation.

-- AnthonyMarston - 24 Jan 2011

Topic attachments
I Attachment History Action Size Date Who Comment
PDFpdf aa14519-10.pdf r1 manage 1321.5 K 2011-01-24 - 09:51 AnthonyMarston SPIRE A&A paper, Griifin et al 2010
PDFpdf aa14605-10.pdf r1 manage 264.1 K 2011-01-24 - 16:48 IvanV SPIRE in-flight calibration
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Topic revision: r9 - 2011-03-03 - LucaConversi
 
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