Tasks/exercises for SPIRE data in HIPE
As an example, work through one supernova remnant from the Hi-Gal survey, G332.4+0.1. You can find more information about this object at, e.g., SIMBAD.
- Try to download the Hi-Gal data that has already been calibrated and mapped. Check the data quality to determine if you need to re-reduce or make the map again (for example, if there is some residual striping from the cross-scans).
- If you decide you need to re-reduce it, you can follow the links I’ve listed below.
- You will need the OBSID – you can look for this with the HSA Tool at http://www.cosmos.esa.int/web/herschel/science-archive
–> Input the object name or coordinates and it will return a list of observations and IDs
There will be many observations with PACS/SPIRE/HIFI. Choose the ones you want to see. The SPIRE large map obs for G332.4+0.1 were OBSID 1342192055
- MAKE SURE you are using a recent version of HIPE if you plan to reprocess the data. You will need LOTS of RAM to reduce Herschel data – aim for a machine with at least 32GB.
Data reduction pipeline in HIPE
==> See tutorials on NASA/IPAC’s site:
And the DRG for reprocessing http://herschel.esac.esa.int/hcss-doc-15.0/load/spire_drg/html/photometer_launchpad.html#d0e571
The tutorial for the SPIRE large map pipeline reprocessing:
That one is quite good – much better than was available when I started learning how to reduce SPIRE data, with many picture examples of things to look out for in your final images
They have also made available a large number of web video tutorials over the past few years:
SPIRE photometry ‘recipe’
http://herschel.esac.esa.int/hcss-doc-15.0/load/spire_drg/html/ch06s09.html –> section 184.108.40.206
Also see the HIPE Data Analyis Guide for a description of basically any analysis task you would care to do in HIPE:
Overall summary of commands from the SPIRE ‘recipe’, downloading level-2 data from the HSA:
obsid = 1342192055 # Specify the observation ID from the HSA (Kes 32) alpha = 2 #For a source with spectrum S(ν) proportional to Sα (SPIRE default pipeline assumes α = -1) array = "PSW" # Run for an individual SPIRE band: "PSW", "PMW", "PLW" obs = getObservation(obsid, useHsa=True, instrument='SPIRE') # Loading an observation of Gamma Dra from the HSA # obs = getObservation(obsid, poolName='mypool', instrument='SPIRE') # Alternative, for observation from your own local pool mapExtd = obs.level2.refs["extd"+array].product #Extract Extended (MJy/sr) calibrated maps from the Observation Context cal = spireCal() #Load the calibration tree # --> if that doesn't work: cal = spireCal(calTree="spire_cal", saveTree=1) beamCorrTable = cal.phot.refs["ColorCorrBeam"].product kCorrExtdTable = cal.phot.colorCorrKList.refs.product beamArea = beamCorrTable.meta["beamPipeline"+array.title()+"Arc"].double kCorrExtd = kCorrExtdTable.getAlphaCorrection(alpha, array) mapExtended = convertImageUnit(image=mapExtd, newUnit='Jy/pixel') # convert maps from MJy/sr to Jy/pix mapExtendedCorrected = imageMultiply(image1=mapExtended, scalar=kCorrExtd) #Color Correction ra = '244.252833' # Target RA and string values: 16h 17m 00.68s dec = '-50.799300' # Target Dec and string values: -50d 47' 57.48'' photrad = 200.0 #photometry source radius, in arcsec (I'm just making these up - you will have to choose an appropriate region) phot_ann_in = 300.0 #photometry annulus inner radius, in arcsec phot_ann_out = 300.0 #photometry annulus outer radius, in arcsec # Carry out circular/annulus Aperture Photometry annularPSW = annularSkyAperturePhotometry(image= mapExtendedCorrected, \ centerRA=ra, centerDec=dec, fractional=1, \ radiusArcsec=photrad, innerArcsec=phot_ann_in, outerArcsec=phot_ann_out) # annularSkyAperturePhotometry() #Alternatively, define the photometry regions manually flux = annularPSW.getTargetTotal() # Final target brightness in Jy/pixel print 'PSW flux = %5.3f Jy'%(flux)