Let's look at the properties of Abell 2065

Abell 2065
RA
Dec
Redshift
Degrees
230.7
+27.7
0.07
(These are rough properties, you will need to refine them with the SDSS data!)

Go to SDSS Skyserver: http://skyserver.sdss.org/dr12/en/home.aspx

Go to Navigate, and put in the cluster coordinates. Click "get image." Play around. Scroll, zoom, click on galaxies and hit "Explore", etc. Look at a few spectra of galaxies in the field. Work out the following:

Download and examine a fits image. Pick an object, hit explore, then under PhotoObj, hit FITS. Grab one of the g-band corrected frames, open it up in ds9, and see if you can match it up to the navigate view.

OK, so now you have a feel for the cluster, lets get some data and try and work out some quantitative analysis.

Go back to Skyserver main page.

Go to Search, Imaging Query, and do a search for galaxies within a radius of 30 arcmin of the cluster center that you found. Don't select stars (look over the search form to see how you can do this). Make sure you set "Limit number of output rows" to zero so that you get everything, and tell it to give the data to you in a FITS table.

Highlight the following information and execute the search:

Imaging
Spectroscopy
radec
z
modelmags
zErr
modelmagerr

lnLExp_g
lnLDeV_g

(If you need a copy of the fits table on your laptop, you can regenerate it using the procedure above, or just use the version I downloaded: A2065SDSS.fits.)

Grab this template python code for reading in the SDSS fits table and plotting data. And try making the following plots:

(Note: when I say plot "this" versus "that", "this" goes on the y-axis and "that" goes on the x-axis. So "plot color versus magnitude" means that color goes on the y-axis and magnitude goes on the x-axis.)
Other exercises to try:


Plotting tips

want=(g<20) # for selecting objects with a g mag brighter than 20
or
want=(np.abs(z1-0.1)<0.05) # for selecting objects in the redshift range 0.005 to 0.015
or
want=(rerr<0.2) # for selecting objects with an r magnitude uncertainty less than 0.2
etc.....
followed by, for example,
scatter(r,gmr,s=1) # if you want to plot the whole sample
scatter(r[want],gmr[want],s=20,color='red')
# to then overplot the subsample