1.1 Overview Photometric Calibration

This section gives a quick summary of how photometric calibration can be achieved in Astro-WISE. Hyperlinks refer to more detailed how-tos on the photometric calibration.

Photometric calibration in AstroWise is done by comparing the counts in standard stars on images to their magnitudes as listed in a reference catalog of standard star present in AstroWise. The final result is a PhotometricParameters object which contains photometric information such as zeropoint and extinction. This object can then be used to photometrically calibrate your ReducedScienceFrames. A PhotometricParameters is obtained via the following steps:

STEP 1.
The starting point is a single observation of a standard star field which has been debiased and flatfielded, (i.e., a ReducedScienceFrame object) and for which an astrometric solution has been derived (i.e., an AstrometricParameters object exists).

STEP 2.
Create a Photometric Source Catalog, a PhotSrcCatalog object, which crossmatches standard stars listed in a Photometric Reference Catalog (a PhotRefCatalog object) with stars on the ReducedScienceFrame observation. An example command from the awe-prompt using a standard recipe is:

awe> r_in = ['Sci-GVERDOES-WFI-------#844-ccd53-Red---Sci-53751.6824560.fits',
     ...'Sci-GVERDOES-WFI-------#843-ccd53-Red---Sci-54066.0858679-efd5fec21b47bd7bf1f5dab473b463fc54f70bd9.fits']
awe> task = PhotcatTask(instrument = 'WFI',red_filenames = r_in, 
     ...transform=1,inspect=1,commit=0)
awe> task.execute()
red_filenames is a list of the filenames of the ReducedScienceFrames of the standard star observations. transform=1 ensures that differences between the passbands of the instrument and the standard photometric system are accounted for. inspect=1 means a plot will be created to inspect the resulting crossmatch (default inspect=0). commit=1 ensures the result is saved in the AstroWise database (default commit=0). The above command uses default settings for process parameters such as the standard stars to use and the configuration of the source extraction algorithm. Please read HOW-TO Photometric Source Catalog for more details. Please read Photometric Reference Catalog and Extinction Curve how to select a subset of the Photometric Reference Catalog or how to define your own Photometric Reference Catalog.

STEP 3.
Create a Photometric Parameters Catalog, a PhotometricParameters object, which contains photometric parameters, such as zeropoint and exintction. An example command from the awe-prompt using a standard recipe is:

awe> r_in = ['Sci-GVERDOES-WFI-------#844-ccd53-Red---Sci-53751.6824560.fits',
     ...'Sci-GVERDOES-WFI-------#843-ccd53-Red---Sci-54066.0858679-efd5fec21b47bd7bf1f5dab473b463fc54f70bd9.fits']
awe> task = PhotomTask(instrument = 'WFI', red_filenames = r_in,
     ... sigclip=3.5, inspect=1, commit=0)
where red_filenames, inspect and commit have the same meaning as for the Photometric Source Catalog. sigclip=3.5 removes individual standard star measurements which differ by more than 3.5 standard deviations from the median from the calculation of the zeropoint. The above command uses default settings of process parameters and a default atmospheric extinction correction. Please read Extinction and Zeropoint section for the various ways to make your own atmospheric extinction correction and details for deriving a Photometric Parameters Catalog.

Upon completion of these steps ReducedScienceFrames which contain your scientific targets can be photometrically calibrated using the PhotometricParameters object. Upon making a RegriddedFrame out of a ReducedScienceFrame the most recent valid PhotometricParameters is used by default to photometrically calibrate the ReducedScienceFrame resulting in a RegriddedFrame.

For certain instruments scattered light (and potentially other effects) cause varations in the illumination as a function of location on the CCD. Determining this illumination variation requires an appropriate set of dithered standard star observations. If such a set is available, a correction for the illumination variation can be determined using a standard recipe from the awe-prompt , for example :

awe> task = IlluminationVerifyTask(raw='WFI.1999-06-18T06:02:14.059',
     ... commit=0)
awe> task.execute()
where raw is the rootname of the set of RawScienceFrames of a single pointing (e.g., rootname WFI.1999-06-18T06:02:14.059 for the filenames WFI.1999-06-18T06:02:14.059_(1...8).fits of the 8 RawScienceFrames which make up a WFI imaging plane). commit=1 ensures the result is saved in the AstroWise database (default commit=0). This correction can then converted into an illumination flat which in turn can be applied to your RawScienceFrames to create ReducedScienceFrames corrected for illumination variations. An example command from the awe-prompt to create an illumination flat using a standard recipe:
   
awe> task = IlluminationTask(date='1999-06-17', chip='ccd54',
     ... filter='#844', instrument='WFI', commit=0)
awe> task.execute()
where date is the date when the observing night started, chip is the name of the chip for which the correction needs to be determined, filter its filter name. commit=1 ensures the result is saved in the AstroWise database (default commit=0). Please read HOW-TO Illumination Correction for details on deriving and applying an illumination correction.

page generated Tue Apr 4 14:29:41 CEST 2017