psphot Galaxy Parameter Measurements

Bill Sweeney 2014-12-03

For PV3 we plan to add some additional measurements of extended sources in psphotStack. This note describes these measurements and includes some results from a test on the SAS2 region.

Asymmetry Indices

In Section 5.6 of a paper published in 2002 ​Luc Simard et al. described two measurements for use in the morphological classification of galaxies. See equations 11a and 11b in section 5.6.

The measurements are performed on residual images created by subtracting a galaxy model fits from the input images. The model used was the combination of bulge (de Vaucouleurs) + disk (exponential). These Asymmetry indices "provide an estimate of the overall smoothness of the galaxy image with respect to the fitting model". The program used to make these measurements is called GIM2D. It is performed on the results of processing by SExtractor. Since the indices consist of sums of absolute values of the residuals a positive signal will result even in the prescence of noise. So the algorithm subtracts off randomly selected "background pixels" which in the GIM2D program are chosen from the SExtractor segmentation image.

A later paper published in ​2009 defined the parameter S2 = Rt + Ra where Rt and Ra are measured for 2 half light radii. In ​2011 Simard, et al. applied these methods to SDSS images.

In the most recent version of psphotStack I have attempted to implement these measurements. Since we do not fit a bulge + disk model we have chosen to use our sersic model fits. The measurements are preformed independently on each filter's sources as follows.

1 At the beginning of the function the input image has all sources subtracted. The first step for each source is to add the subtracted model back in.

2. Next if the source's model is not the Sersic model fit, the model is temporarily changed to make it so.

The indices consist of sums over a specific radius. Following Simard 2009 and 2011 the radius chosen is 2 times the half light radius for which the value that we have chosen is the major axes of the Sersic fit.

3 The next step is to determine the background pixels. psphotStack doesn't have a segmentation image so the background pixels are selected using the "footprints" measured during source detection. A pixel that is not part of any footprint is considered a background pixel. The source's pixels are examined and a vector of background and mirror background pixels are saved. During this loop the sum of the source's pixels is made as well.

4. The Sersic model is subtracted from the images.

5. The sums in the formulas for Rt and Ra are performed.

The new code was used in psphotStack for SAS.37.