Using SDSS Navigator


Let's look at the properties of Abell 2065.  The cluster's sky position is

(RA,Dec) = (230.62156, +27.70763)

where both coordinates are given in decimal degrees.


Go to SDSS Skyserver: http://skyserver.sdss.org/dr16/ and click on Navigate (under Data Access).

Go to Navigate, and put in the cluster coordinates. Click "Search".  Hopefully you'll see a cluster.

If you click on "Grid" (in Drawing Options), you'll get a scale bar which helps you work out the angular scale of the image. You can zoom in and out using the magnifying class +/- buttons, and you can pan by click-dragging.

Note: Clicking "Invert Image" often helps you see things better.

Click on a galaxy. Over to the right, you'll see the galaxy in a little zoomed-in window, with the ugriz magnitudes given above it. If you click the "Explore" button underneath the zoom window, a new webpage will open up with more detailed properties of the galaxy, including (if it exists) a spectrum.

If you go back to the Navigate page, and (under Drawing Options) click "Objects with Spectra", it will highlight all sources that have spectroscopy, and you can click on one of them, click on Explore again, and you will see both photometry and spectroscopy data.

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:


VERY IMPORTANT: When Navigate says an object has type = STAR, that does not mean it is actually a star. It only means that it is an unresolved point source. It might be a star, but it could also be a small, unresolved galaxy.


Working with SDSS data


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

Instructions for downloading data
Jupyter notebook to get you started on analysis

Try a few of these things:


(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.)
  1. Plot r mag uncertainty versus r mag. If you want your mags accurate to 10% or better, what is the rough magnitude limit of your analysis?

  2. Plot dec vs ra (so a sky map) of resolved sources (type=3) brighter than r=20. Make another for unresolved sources (type=6) brighter than r=20. Think about the differences.

  3. Plot redshift versus r-band magnitude for galaxies that have a measured redshift and are within 30 arcminutes of the cluster center. Using the plot as a guide, work out a quantitative, statistical estimate of the cluster redshift. If you wanted to define a "spectroscopically confirmed cluster member", how might you do it?

    Tip: Look at the redshift plot, decide what range of redshifts define the cluster. Make a selection on galaxies with redshifts in that range, and calculate the average redshift of those objects.

  4. Plot g-r color versus r magnitude for all resolved sources projected within 1 Mpc of the cluster center -- this is a color-magnitude diagram (CMD) for galaxies.

    Tip: Given the redshift you calculate above, use the astropy code in the sample workbook to work out the angular radius (in arcseconds) that encompasses 1 Mpc in the cluster. Then make a selection on galaxies with a radial distance less than that angular radius, and plot the color-magnitude diagram for those clusters.

  5. Plot the CMD, then overplot in a different color the CMD for spectroscopically confirmed cluster members. Again, restrict it to resolved sources projected within 1 Mpc of the center.

    Tip: Do a dual selection: galaxies within the 1 Mpc projected radius AND within the range of redshifts that you defined for the cluster. Then plot the CMD for those galaxies on top of the one you made in the previous step for all objects projected within 1 Mpc.

  6. Identify the bluest spectrosocopically confirmed galaxies, find their ra and dec, and then find them using Skyserver's "Navigate" function. What do they look like morphologically? Spectroscopically?

    Tip: Define a new column of data for the SDSS data table to hold the g-r color:
    SDSS['g-r']=SDSS['g']-SDSS['r']. The do a show_in_browser call on objects within the cluster redshift range. Sort on the g-r column to find the bluest objects and look at their coordinates. Then find them using Navigate.

  7. Identify the most luminous spectroscopically confirmed galaxies and look at them in Navigator. What do they look like morphologically? Spectroscopically?

    Tip: Now sort your show_in_browser table on the r-magnitude and look at the coordinates of the brightest object. Then find it using Navigate.

  8. Identify the highest redshift objects in the field (they won't be in the cluster, obviously!) and find them in Navigator. What do they look like, morphologically and spectroscopically?

    Tip: This time do a show_in_browser call on all objects with a redshift (whether or not they are in the cluster redshift range), and sort on the redshift to find the coordinates of the highest redshift object.

Feel free to try other things, even if they might seem non-sensical at first. If a pattern shows up, think about it! And remember, there are other source properties available in the SDSS database; you can browse the PhotoObj and SpecObj tables to see what else is there and add them to your download request if you want.

Plotting and Slicing tips

want=(SDSS['g']<20) # for selecting objects with a g mag brighter than 20
or
want=(np.abs(SDSS['redshift']-0.1)<0.05) # for selecting objects in the redshift range 0.005 to 0.015
or
want=(SDSS['modelMagErr_r']<0.2) # for selecting objects with an r magnitude uncertainty less than 0.2
etc.....
followed by, for example,
scatter(SDSS['r'], SDSS['g']-SDSS['r'], s=1) # if you want to plot the whole sample
scatter(SDSS['r'][want], SDSS['g'][want]-SDSS['r'][want], s=20,color='red')
# to then overplot the subsample
want=SDSS['g']<18 # bright
want=np.logical_and(want, SDSS['g']-SDSS['r']>0.7) # red
want=np.logical_and(want, SDSS['redshift'] != -999)
# has redshift

which would give you a "want" selection that is bright red galaxies with measured redshifts