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Extracting Photometry from SPIRE Maps

Extracting Photometry from SPIRE Maps. David Shupe, Bernhard Schulz, Kevin Xu on behalf of the SPIRE ICC. SPIRE Point Source Photometry. SPIRE Calibration and Map Units Fitting Functions to Point Sources Considerations for Aperture Photometry Source Extraction

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Extracting Photometry from SPIRE Maps

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  1. Extracting Photometryfrom SPIRE Maps David Shupe, Bernhard Schulz, Kevin Xuon behalf of the SPIRE ICC

  2. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Source Extraction • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  3. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • How Calibration is Defined • Units and Beam Areas • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Source Extraction • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  4. SPIRE calibration is defined by the peak deflection when scanning Scan of detector PSWE8 over Neptune,obsid 1342187440 When a detector is scanned directly over a point source, the peak deflection of the signal timeline equals the brightness of the source.

  5. The timeline-based definitionleads to some accounting corrections • Units are in Janskys per beam • Most software wants Jy/pixel or MJy/sr • Map-making lowers the peaks… • …relative to the timelines • Calibration is for point source peaks • Some detectors have bigger areas • Calibration is for nu*Fnu = constant • Color correction for other spectral shapes

  6. Use the “fine-scale” beam areasto convert Jy/beam to other units • The fine-scale beam areas were measured from Neptune maps with 1-arcsec pixels • 250um: 423 sq arcsec • 350um: 751 sq arcsec • 500um: 1587 sq arcsec • These values may change slightly in the near future (by a few percent) • The “convertImageUnit” task willchange maps to Jy/pixel or MJy/sr

  7. Divide peaks measured in mapsby the pixelization correction Curves obtained by integrating skybins/pixelsover Gaussian approximations to the average beam 1.0 Factor by which peak is lowered 500 0.9 250 350 0.8 6” 10” 14” Pixel size in arcseconds • See Sec 5.2.11 of the SPIRE Observer’s Manual • For nominal pixel sizes, divide by factors of: • 0.951 (250) • 0.931 (350) • 0.902 (500)

  8. Applying the Relative Gains equalizesthe detector areas (instead of the peaks) Gains are provided in the SPIRE cal tree These gains are applied before destriping and map-making More details when we talk about Aperture Photometry

  9. Single-detector Neptune maps show the gains reduce the spread in aperture photometry Neptune, Operational Day 168, PSW (250 microns) Number of Detectors in Flux Bin No Relative Gains Timeline-fitting Relative Gains Applied Relative Gains Applied Aperture Photometry No Relative Gains Measured Flux (Jy) Aperture radius = 150”Aperture correction = 1.027

  10. Color corrections are described in the SPIRE Observers’ Manual & Data Reduction Guide Color Correction Factor vs. AssumedSource Spectral Index (Point Source) Multiplicative Correction 250 1.0 0.98 500 350 0.94 0.90 -2 -1 0 1 2 3 -3 Source Spectral Index (in frequency) • See Sec 5.2.8 • Multiply by the value appropriate for your source • For specific cases, compute your own correction from the filter RSRFs

  11. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Peak-fitting techniques • Estimating uncertainties • Considerations for Aperture Photometry • Source Extraction • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  12. Peak-fitting is recommendedfor point sources • Fitting Gaussians to timelines is the best method for sources visible on the maps • Jython script: bendoSourceFit_v0.9.py • Java task: timelineSourceFitterTask • Gaussian-fitting on maps is serviceable as a second choice • Java task: sourceFitting • Gaussian is good approximation for radii up to (22, 30, 42) arcsec

  13. To estimate the total uncertainty in flux,combine these terms in quadrature • Uncertainty in the fitted amplitude • Includes the instrument and confusion noise (minimum of about 5 mJy) • 7% of flux density for calibration uncertainty • 2% statistical reproducibility • 5% absolute level of Neptune model(this term does not apply to SPIRE colors)

  14. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Applying the relative gains • Aperture corrections • Source Extraction • Demos of the HIPE Photometry Tools

  15. The relative gains may be applied using a Useful Script, or the SPIA • SPIRE official pipeline scripts • applyExtendedEmissionGains option • SPIRE Useful Script: Photometer Baseline Removal and Destriper • Example is at the end (5th one) • spiaLevel2 task • Relative gains are applied by default • In the last 2 cases, the original Level 1 timelines are left untouched • The point-source calibration still based on peaks • The best of both worlds: timeline-fitting on Level 1, and aperture photometry on maps

  16. Official aperture corrections are now in the SPIRE Data Reduction Guide! • Available in the online HIPE 8 docshttp://herschel.esac.esa.int/hcss-doc-8.0/load/spire_drg/html/ch05s07.html • Not in the docs that come with HIPE 8.1 • Values in Photometry Recipe: • 1.2750 (250μm) 22” radius, sky 60”-90” • 1.1933 (350μm) 30” radius, sky 60”-90” • 1.2599 (500μm) 42” radius, sky 60”-90” • Uncertainties at 5% level

  17. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Source Extraction • Inside HIPE: DAOPhot & Sussextractor • DAOPhot Demo • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  18. Two source extractors are availablewithin HIPE • sourceExtractorDaophot • Algorithms from IDL AstroLib • FIND for detection • APER for photometry (not PSF-fitting!) • sourceExtractorSussextractor • Sussextractor algorithm (Savage & Oliver 2007) • Flux density is peak of smoothed image • Good for detecting sources

  19. The simplest operation of extractorsuses the FWHM of each band • Averages for nominal pixels: • 250um: 18.2 arcsec • 350um: 24.9 arcsec • 500um: 36.3 arcsec • You can supply your own PRF image • The fine-scale beam areas are needed (or the images must be converted) • (423, 751, 1587) sq arcsec

  20. Corrections are still neededfor extractor outputs • For sourceExtractorDaophot, need an aperture correction appropriate to radius supplied • For sourceExtractorSussextractor, the correction seems to be flux-dependent • A nice combination for sources 20 mJy and brighter, is to use Sussextractor for detection and timeline-fitting for the photometry (see demo)

  21. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Source Extraction • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  22. Checklist for timeline-fitting photometry • Use the Level 1 timelines without relative gains applied • Perform first-order baseline correction • Supply a starting position • Run the bendoSourceFit or the timelineSourceFittingTask • Apply color correction as needed

  23. Checklist for fitting on the map • Use the map made without relative gains applied • Run the sourceFitting task • Divide by the pixelization correction • Apply color correction as needed

  24. Checklist for aperture photometry • Make the map with relative gains applied (destriping recommended also) • Convert to Jy/pixel using “convertImageUnit” task • Run the annularSkyAperturePhotometry task • Apply an appropriate aperture correction • Apply color correction as needed

  25. SPIRE Point Source Photometry • SPIRE Calibration and Map Units • Fitting Functions to Point Sources • Considerations for Aperture Photometry • Source Extraction • Summary: Checklists for Astronomers • Demos of the HIPE Photometry Tools

  26. Demos of the photometry tools in HIPE Fitting Gaussians on the map (Bernhard) Timeline-fitting of Gaussians (Bernhard) Aperture Photometry (Kevin) Source detection with Sussextractor combined with timeline-fitting (David)

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