PACS NHSC SPIRE Point Source Spectroscopy Webinar 21 March 2012 David Shupe, Bernhard Schulz, Kevin Xu on behalf of the SPIRE ICC Extracting Photometry.

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Presentation transcript:

PACS NHSC SPIRE Point Source Spectroscopy Webinar 21 March 2012 David Shupe, Bernhard Schulz, Kevin Xu on behalf of the SPIRE ICC Extracting Photometry from SPIRE Maps

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

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

The timeline-based definition leads 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 5

Use the “fine-scale” beam areas to 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 will change maps to Jy/pixel or MJy/sr 6

Divide peaks measured in maps by the pixelization correction See Sec of the SPIRE Observer’s Manual For nominal pixel sizes, divide by factors of: – (250) – (350) – (500) Curves obtained by integrating skybins/pixels over Gaussian approximations to the average beam Pixel size in arcseconds Factor by which peak is lowered ”6” 10” 14”

Applying the Relative Gains equalizes the 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 8

Single-detector Neptune maps show the gains reduce the spread in aperture photometry 9 Timeline-fitting Aperture Photometry Measured Flux (Jy) Number of Detectors in Flux Bin Neptune, Operational Day 168, PSW (250 microns) Aperture radius = 150” Aperture correction = 1.027

Color corrections are described in the SPIRE Observers’ Manual & Data Reduction Guide See Sec Multiply by the value appropriate for your source For specific cases, compute your own correction from the filter RSRFs Color Correction Factor vs. Assumed Source Spectral Index (Point Source) Source Spectral Index (in frequency) Multiplicative Correction

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

Peak-fitting is recommended for 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

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) 13

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

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 (5 th 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 15

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

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

Two source extractors are available within 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 18

The simplest operation of extractors uses 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 19

Corrections are still needed for 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) 20

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

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 22

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 23

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 24

PACS NHSC SPIRE Point Source Photometry Webinar 21 March 2012 page 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

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) 26