DESARROLLO DEL CONTENIDO SOBRE VERTIDOS LÍQUIDOS

In total, all correction terms that need to be applied to the zero-point, determined in a 50 pixels diameter aperture are

ZP = ZP 50 + ∆ZP_COG:1000_→90800+ ∆ZP_Ghosts+ ∆ZPPan−STARRS (16.7)

= ZP 50 + 0.0785mag + 0.0192mag + 0.0178mag (16.8)

= 0.1155mag (16.9)

A cross-check for a random sample of 10 BCG SB profiles measured on fully calibrated WWFI g0-band data and SDSS g-band data shows

∆ZPWWFI→SDSS= 0.023 ± 0.019mag (16.10)

This is inconsistent with the correction for point sources: g0− g = −0.012 − 0.139(g − r) = −0.12 for (g − r) = 0.78 (Tojeiro et al., 2013).

SDSS magnitudes are calibrated using an aperture correction out to only r = 7.400. Since we do not have the extended SDSS PSF SB profile at hand, we can make an order of magni- tude approximation for the correction using our WWFI PSF SB profile. Outside of a circular aperture with that same radius of r = 7.400 leaks 6.8% of the PSF’s light. That corresponds to a brightness difference of 0.077 mag, which must be added to the SDSS SB profiles. Con- sequently, an error of only 0.02 mag arcsec−2 remains.

16.6. SUMMARY AND COMPARISON TO SDSS 101

29.5

30

30.5

31

31.5

12

14

16

18

20

22

ZP25 = 29.9965

ZP [mag]

stellar brightness [mag]

29.5

30

30.5

31

31.5

12

14

16

18

20

22

ZP50 = 30.0449

ZP [mag]

stellar brightness [mag]

Figure 16.1: Examples for the determination of the zero-points in a stack. The aperture diameter is 500= 25px in the top panel and 1000= 50px in the bottom panel. Black dots show the calculated zero-points for individual stars. The upward curvature for faint sources is due to blending. The red line indicates the best-fit value, which is also given in the label. The two vertical lines show the region in which the fit is performed.

0 0.2 0.4 0.6 0.8 1 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 2r = 25 pixels 2r = 50 pixels

I(

<

r)

(r [arcsec])

Figure 16.2: The curve of growth of a g0-band PSF. The integrated luminosity fraction at I(r < 12.5px)/Itot=

Chapter

17

Removal of bright stars

The PSF wings of bright stars add a background pattern that is fixed in celestial coordi- nates. It can be subtracted from the single images before any of the background subtraction methods, described in Sec. 18, is applied. The procedure is split into three steps: 1) mod- eling/subtraction of ghosts using rmhalos.sh, 2) modeling of the circularly symmetric PSFs using modelpsfs.sh and 3) subtraction of those modeled PSFs using substars.sh.

Since bright stars often saturate in WWFI exposures, literature catalogs can be used to obtain the coordinates and brightnesses of the stars in consideration. A table file containing these information can easily be created using the program DS9 (http://ds9.si.edu):

cd /data/wst/u/mkluge/WWFI/reduced/A1656/final/ ds9 A1656_V191209_g_1.fits

# Analysis --> Catalogs --> Optical --> Tycho-2

# Copy the table to the clipboard by clicking on the dark gray table head row with the labels "_RAJ2000 _DEJ2000 recno ..."

# Paste the clipboard into a file called, e.g., stars_tycho.txt in the final/ folder

Since the TYCHO-2 catalog only contains BT and VT magnitudes, color transformations

need to be applied in order to transform these magnitudes into Johnson BJ and VJ (ESA,

1997) and then into g and r magnitudes (Jester et al., 2005).

VJ = VT − 0.09(B − V )T, (17.1)

(B − V )J = 0.85(B − V )T (17.2)

g = VJ + 0.60(B − V )J − 0.12 (17.3)

r = VJ − 0.42(B − V )J + 0.11. (17.4)

Color transformations are not available for the u0-, i0-, z0-, and L-bands. Bright star modeling is therefore only implemented in the pipeline for the g0- and r0-bands.

Alternatively, or in combination with the TYCHO-2 catalog, the SDSS catalog can also be used to create such a table file for intermediately bright sources by choosing the catalog ”SDSS Release 12” instead of ”Tycho-2”. Since there is some overlap between the two catalogs, it is possible to parse both tables to the scripts rmhalos.sh and modelpsfs.sh, which then

discard duplicates from the TYCHO-2 table if the separation to any star in the SDSS table is lower than 400. Contrary to TYCHO-2, SDSS covers only a part of the sky. In the lucky case that the field of view is covered by SDSS, it advised to filter the SDSS results in DS9 for only the brightest sources before copying the table. That can be done by typing e.g., $gmag<12 into the ”Filter” field and pressing ”Retrieve” to select only stars whose g-band brightness is brighter than 12 mag. The workflow is demonstrated by the following code:

cd /data/wst/u/mkluge/WWFI/reduced/A1656/final/

# create bright star tables stars_tycho.txt and/or stars_sdss.txt modelpsfs.sh auto A1656_V191209_g_1.fits stars_tycho.txt tycho modelpsfs.sh auto A1656_V191209_g_1.fits stars_sdss.txt sdss # or

modelpsfs.sh auto A1656_V191209_g_1.fits

stars_tycho.txt,stars_sdss.txt tychosdss cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/ # subtract reflections

rmhalos.sh auto ../../final/stars_tycho.txt 1.0 tycho rmhalos.sh auto ../../final/stars_sdss.txt 1.0 sdss # or

rmhalos.sh auto

../../final/stars_tycho.txt,../../final/stars_sdss.txt tychosdss

# subtract symmetric PSF

substars.sh auto ../../final/psf_A1656_V191209_g_1.fits 1.0

The resampled files stacks/swarp <FILTER>/q*.resamp.fits must already exist before- hand, e.g., from a previous autoreduce V2.sh ... -fs=<FILTERS> execution. The reason is that the FLASCALE header keyword from those files is used by rmhalos.sh and substars.sh to undo the flux scaling.

The scaling is not always optimal due to intrinsic stellar variability and systematic zero- point errors at this intermediate stage of the data reduction. Some iteration might be neces- sary to minimize the residuals. Latter are best checked in a newly created stack. Night-sky flat and/or background subtraction routines need to be run again (see Sec. 18). If the residuals are too strong, the backup files without removed stars can be restored.

cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/ mv before_substars/* .

mv before_rmhalos/* .

The order is important. The scripts rmhalos.sh and substars.sh can then be executed again with a scaling factor chosen best somewhere between 0.85 ∼ 1.15 that substitutes the parameter 1.0 in the above examples.

Chapter

18

Background subtraction

Three different tools are available for background subtraction: SWarp, skycorr, which was developed during this PhD thesis project and skyalign, which was developed by Bianca Neureiter during her Bachelor’s thesis project. Different methods qualify as optimal depend- ing on the science case, observing strategy and observing conditions. The science case puts requirements on background flatness on certain spatial scales, e.g., for deep photometry, or it puts constraints on background similarity between exposures, e.g., for difference imaging. The observing strategy puts constraints on the achievable background flatness. For instance, the night-sky flat accuracy drops when the objects become too large compared to the dithersize. The observing conditions put constraints on the achievable background flatness or background similarity between images, e.g., passing clouds, moonlight or twilight.

In this chapter, all available methods are described in detail. Code examples for archival Coma cluster (A1656) data are provided to illustrate the how the methods are applied in practice. Moreover, a visual quality check tool for all single background-corrected images is described in Sec. 18.12.

The stacks that are created with the provided code examples are shown in Fig. 18.1 and 18.2. They illustrate the limits of each method and to give the reader an impression of the achievable background flatness quality. When the observations were taken during photometric and dark conditions, residual background inhomogeneities remain typically on a level of ∆SB ≈ 30 g0 mag arcsec−2 (see Fig. 5.1 and Sec. 18.11). These residuals decrease when more exposures are combined.

18.1

Requirements

All following scenarios require that the basic data reduction is complete and a first stack is created. Moreover, it is advised that satellites are masked and bright stars are subtracted. The following code shows the necessary steps to reach this stage.

# basic reduction

autoreduce_V2.sh -P=A1656 -p=abell1656 -rv=V191209

# mask satellites

cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/ mask_satellites_manually.sh q[134]*170125_388

# create a stack

autoreduce_V2.sh -P=A1656 -p=abell1656 -rv=V191209

-ra=12:59:36 -dec=27:57:34 -fs=g -ur=redo_all -t=0.7 # model and subtract bright stars

cd /data/wst/u/mkluge/WWFI/reduced/A1656/final/ # create a bright star table stars.txt using DS9 modelpsfs.sh auto A1656_V191209_g_1.fits stars.txt

cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/ rmhalos.sh auto ../../final/stars_obj.txt

substars.sh auto ../../final/psf_A1656_V191209_g_1.fits Or for the case that sky pointings were observed:

# basic reduction

autoreduce_V2.sh -P=A1656 -p="abell1656 abell1656_sky" -rv=V191209 -ra=12:59:36 -dec=27:57:34 -fr=g -b -f -cp=0.2 -sc cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/

mask_satellites_manually.sh q[134]*170125_388 # create a sky stack

autoreduce_V2.sh -P=A1656 -p=abell1656_sky -rv=V191209 -bs=400

-ra=12:56:39 -dec=28:08:37 -fs=g -ur=redo_all -t=0.7 # create a target stack

autoreduce_V2.sh -P=A1656 -p=abell1656 -rv=V191209

-ra=12:59:36 -dec=27:57:34 -fs=g -ur=redo_all -t=0.7 # model and subtract bright stars

cd /data/wst/u/mkluge/WWFI/reduced/A1656/final/

# create bright star tables stars_sky.txt stars_obj.txt modelpsfs.sh auto A1656_V191209_g_1.fits stars_sky.txt modelpsfs.sh auto A1656_V191209_g_2.fits stars_obj.txt cd /data/wst/u/mkluge/WWFI/reduced/A1656/V191209/stacks/ rmhalos.sh autosky ../../final/stars_sky.txt

rmhalos.sh auto ../../final/stars_obj.txt

substars.sh autosky ../../final/psf_A1656_V191209_g_1.fits substars.sh auto ../../final/psf_A1656_V191209_g_2.fits