Analysing the properties of galaxies is where the fun really begins! However, before we could really get into some proper analysis of the spectra we had a few things which needed fixing first.
Many of the spectra we had taken in the previous week had a lot of noise, which comes from various sources, including light emitted by particles in the atmosphere and the telescope itself. As the noise appears as more, smaller emission and absorption lines in the spectra themselves it makes identifying the emissions of the fainter galaxies very hard, as the emissions get hidden in all the noise. To try to get some better spectra for the galaxies in our catalogue we found more appropriate minicube sizes for each source in our catalogue. This took a while as we had to go through the whole catalogue and see what minicube size gets the whole source and little of the background or other sources, using the noise reduced image we has produced in the first week. Once we had found better sizes and updated our catalogue to include these we altered the code to take different sizes of minicube then ran it for the whole catalogue again!
Once we had our updated spectra we had to go through each one and find and new emission lines that had appeared and from them the redshift of the galaxy, now the noise should play a smaller part in the shape of the spectra. Unfortunately the difference was not a noticeable as we had hoped, but for a few galaxies we were able to identify at least one emission line that we had been unable to see before. Some distinct emission lines are most likely from the light emitted by the atmosphere and appear in many of the spectra we have collected, these ‘Sky Lines’ can be found as distinct peaks at wavelengths 5578.75Å (with a trough at 5580Å) and three close peaks towards the end of the spectrum at 9307.5Å, 9313.75Å and 9323.75Å, the latter of which appears most often in all spectra.
Next we found the flux of distinct emissions in the spectra and calculated the Metallicity Star Formation Rate (SFR) of the galaxies. This shows you how much metal (in Astrophysics an element which not Hydrogen or Helium is called a metal) is present in the galaxy and how quickly the galaxy is creating stars, which can give you an indication of the age and size of the galaxy. Younger galaxies have more dust and gas so form more stars, and a galaxy with a low metallicity is generally smaller as it cannot retain as much metal (worth noting however, the early universe was very metal poor, so galaxies with a high redshift are could potentially have a lower metallicity as well).
Above Figure: Ignoring two points at high SFR, the other points seem to show a correlation. We hypothesised that the two points at high SFR are star forming galaxies and rest are AGN. This is because
We ran into a few issues with calculating the Metallicity of galaxies with too few emission lines, as the formula we had required H alpha, which is not visible in a lot of our spectra. So after finding some additional formulae which could be used to calculate the Metallicity, albeit with increasingly low accuracy. We also tried to calculate the Dust Extinction of the spectra (the reduction in the brightness of the galaxies due to light being scattered or absorbed by gas and dust between us and the galaxy), this involved some hazy calculations and as we got some negative values for the dust extinction I am not sure our current method for calculating it is at all useful and if we want to obtain some better values for the dust extinction we are going to need a better formula. Never the less we collected the results of the calculations into one file and tried plotting some graphs relating the quantities. These didn’t seem to show much, but did provide an interesting visual representation of the differences in the galaxies and how their properties might relate to each other.
Above Left: Plotting the extinction rate against the metallicity and removing any points at which either value cannot be found, the points appears to follow some correlation, though perhaps a none linear correlation is more accurate.
Above Right: Plotting metallicity against SFR we expected something similar to the plot of dust extinction against SFR, but with our current data it seems to have much less correlation between the Metallicity and SFR.
Next we tried Binning the spectra. This is where you average the signal over a few points and plot that value instead, which should reduce the effect of the noise. However this caused us some confusion and, as we found out when binning some spectra, this method reduces the emission peaks too far to make them visible amongst the noise as emission peaks are very narrow. Binning will however make any absorption lines in the spectra more obvious, which will help when looking at objects with more continuous spectra, as absorption lines are wider than emission lines. The differences in the width of absorption and emission lines as they come from the absorption of light by the metals in the atmospheres of stars, rather than the emissions from H II regions or other regions of ionised metals. For the moment we have not looked further into the absorption lines of the spectra we have collected, however it is worth doing as the absorption lines can tell you about the type of stars which dominate the spectrum of the galaxy, which can tell you a lot about the galaxy itself. It should be noted however, absorption lines could also come from absorption by dust and gas between us and the galaxy that produced the spectra, which means they are just more noise in our spectra.
Above Figure: Binned spectrum of a PIG, found by dividing the noise value by the square root of the width of the bin. We are unsure if this was the correct method, however it does show some more distinct absorption lines just after the continuum stops.
Some key things to look for in the absorption line of the binned spectra is the continuum stopping below a wavelength of approximately 4000Å, to the left of which are three absorption lines which come from Calcium, neutral Hydrogen and Potassium and various other absorption features will be present. This method of analysis works best when the spectrum is continuous, in other words has a distinct curve in its signal as the wavelength increases.
We had a look at the sources which produced continuous spectra, comparing the position of the source in the MUSU image and Hubble image of the same region of sky. This shows that some of the sources which gave a continuum are most likely Stars in our own galaxy. This can be seen in the Hubble image as these Stars produced diffraction spikes (where the light from the source is diffracted by the struts that hold up the secondary mirror inside the Hubble telescope into four lines out from the object in the image). Diffraction spikes are only seen when an object is point-like and very bright, so a galaxy cannot produce diffraction spikes as it needs to be very bright, which means it is no longer point like (you can see the shape of bright galaxies with Hubble), and point-like, which means it is no longer bright enough to produce diffraction spikes.
Much of what we have been is fixing problems in our Python codes and trying to get better spectra. Hopefully this will mean that we can get stuck into some proper analysis of the galaxies in our catalogue soon. The next step as well is to look into automatically finding galaxies in the data cube so we can add even more objects to the PIGEON catalogue!
As there has been a lot of methodically going over sources and their spectra which has been slow, but finding a spectra which many emission lines and looking into all the information we can find out from a single spectrum is pretty amazing. (not to mention that my coding skills are definitely improving!) I certainly look forward to investigating many of these galaxies further, and maybe we will find some very distant galaxies in our catalogue!