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Munipack ‒ Tutorial (Classics Edition)

There are presented examples of a simple runs of Munipack's routines. A first example shows a long time photometry set and the second one is dedicated to a deep sky object (passed).

A sample data for both runs are available as munitut-blazar.tar.gz and munitut-bubble.tar.gz. Use command tar zxf munitut-blazar.tar.gz and tar zxf munitut-blazar.tar.gz to unpack it to a current directory. We will assume that the sample data are unpacked to /tmp directory as /tmp/munitut-blazar and /tmp/munitut-bubble.

Light curve of blazar 0716+714

We have a set of images, flat-fields and dark-frames for the images. Our goal is to get a light curve (a time dependence of magnitude) of the blazar. The same approach can be used for any object as a variable star, an exoplanet, etc.

FilemaskDescriptionExposure time
0716_[1-9]R.fitsscientific images120 sec
d120_[1-7].fitsdark-frames of scientific images120 sec
f10_[1-9]R.fitsflat-fields10 sec
d10_[1-9].fitsdark-frames of flat-fields10 sec

Working directory

As a first important step, we will create a working directory. For example, create /tmp/munitut by the command:

bash$ mkdir /tmp/munitut
bash$ cd /tmp/munitut

The name of the directory is arbitrary. It is highly recommended to use any empty directory to prevent unwanted replacement of any data (especially of original images!).

Mean of dark-frames

We will create a mean-dark for scientific exposures. Run the command

bash$ ls /tmp/munitut-blazar/d120_*.fits | mdark @ robust=y mask=d120.fits

The asterisk marks all images begins with d120_ together with a suffix .fits. The command ls lists images throughout a pipe | to mdark utility which is set by @ to read image names from its standard input. The mdark uses robust method of mean estimation and the mean itself is stored as d120.fits.

The parameter robust=y is optional, but highly recommended. It reduces of fluency of cosmic-rays and one-image defects. On the other side, it requires more computer resources.

In principle, this step can be omitted, but it is a good practice from a statistical point of view. The output image is frequently called as the master-dark.

d10_1.png
A randomly selected dark image.
d120.png
Mean of dark-frames (master-dark).

Dark correction

Original scientific images can be corrected for dark-frames by

bash$ ls /tmp/munitut-blazar/0716_*R.fits | darkbat @ dark=d120.fits mask=$

darkbat subtracts, the previously created mean-dark d120.fits, from every scientific exposure and produces new images stored in the current working directory with image names identical to original ones.

0716_original.png
A randomly selected scientific exposure of blazar 0716+714.
0716_dark.png
A randomly selected scientific exposure of blazar 0716+714 with the d120 dark-frame subtracted.

Running mean of flats

There is a tree step procedure for creating of the running mean of flats

bash$ ls /tmp/munitut-blazar/d10_*.fits | mdark @ robust=y mask=d10.fits
bash$ ls /tmp/munitut-blazar/f10_*R.fits | darkbat @ dark=d10.fits mask=$
bash$ ls f10_*R.fits | aflat @ mask=autoflat.fits

The first two lines are a modification of our previously described examples (The original flat-field images are corrected about their mean-dark and stored in the current directory.) Let's look on tree line. The corrected flat-fields are scaled by its mean intensity and its dispersion to a unified output level. A robust mean is made on the uniform scaled flats and an output flat is stored as autoflat.fits. The output image is frequently called as the master-flat.

The key feature of aflat is the scaling and a robust mean of single flats. The procedure is pretty effective for short series of the twilight sky's exposures when brightness rapidly decrease. Also, a long over-night series of non-identical fields (like many blazar fields) will produce excellent results.

f10_1.png
A randomly selected flat-field image.
autoflat.png
A scaled robust mean of flat-fields (master-flat).

Flat-field correction

In analogy of dark correction, scientific images (subtracted for dark) can be corrected for flats by

bash$ ls 0716_*R.fits | flatbat @ flat=autoflat.fits mask=.

We can see that the current directory images are used. With parameter mask=. the input images are replaced. It may be potentially dangerous!

0716_final.png
A randomly selected, fully corrected (dark and flat), image of blazar 0716+714.

Photometry

We can apply an aperture photometry on prepared images:

bash$ qmphot.pl -i 0716_*R.fits
bash$ ls 0716_*R.fits | muniphot @ com=.

The qmphot.pl prepares configuration files and a running script to muniphot. The photometry itself can be executed via generated shell script or by hand as the second line shows. The run will produce of some additional files.

The routine detect all stars on images and made their aperture photometry.

Matching

Matching of images, or matching of list of stars on images, will done with

bash$ ls 0716_*R.SRT | munimatch @ ref=0716_1R.SRT

Take note on type of used files. There are not images, but a sorted list of detected stars .SRT. The reference image has been choose by random selection to 0716_1R.SRT.

It is recommended to use nicer images as a reference frame. The routine derives linear transformations between single images.

List of magnitudes

On finish, find coordinates of in inspected object together with a reference (comparison) star and run

bash$ ls 0716_*R.fits | munilist @ 256,156 258,88 > lc

The text file lc contains our measured light curve. The table with Julian times and relative magnitudes (together with estimation of residuals).

lc0716.png
Output light curve