In our second week we split into three pairs with one sub-project each, these are the Morphologies (Michael and Joe), Star Formation Rates (Adam and Oliver) and Active Galactic Nuclei (Cass and Dan) sub-projects. This will allow us to get more work done in the same time span and means we can each specialise on our own projects and get more in-depth research done rather than having to all know everything about each sub-project.
Within the Morphologies sub-project, we first used our mean visual classification values to check how well we each agree with it and each other. As it turns out there was a high correlation between our results and thus no individual adjustments were needed. This having been confirmed, we checked the distribution of our results. Using our mean values for the galaxies not classified as unreviewable, roughly 39% were classified as elliptical, 30% as disky, 20% as point-like and 11% as irregular (non-integer mean classifications were rounded to the nearest integer, the results were however roughly grouped about the integer values, so this seems a fair approximation to use). This would suggest that while irregular galaxies are less common, those with the more regular elliptical or spiral structure are much more commonly found in our universe (at least in the area we were observing).
We then decided to see if there was any obvious relationship between our classifications and the redshifts of each of the galaxies we looked at. As can be seen in our graph comparing the two there was a slight trend towards lower values the further away a galaxy is which is plausible as a younger galaxy is likely to be smaller and more spherical whereas an older one is more likely to have grown and developed into a spiral or irregular shape over its evolution. However, there is a very large spread about the fitted line, which is only slightly sloped so possibly this is not the most reliable of results. This isn’t particularly surprising as in using the brightest 1000 galaxies in our catalogue there are over 2000 galaxies left out of these classifications, all of which will be dimmer than those we did use, which likely skews the results and doesn’t provide a particularly accurate depiction of the full data set.
This problem can be worked around by instead using the galaxy’s Sersic profiles, which are mathematical functions that describe how the intensity of a galaxies changes with respect to the distance from its centre. The profile fitting program Galfit was used to produce our data and amongst other things it gives values for each galaxy’s half-light radius and its 20%, 50% and 80% light radii (the latter three are calculated with a different fit than the former and thus give slightly different but still useful data). Once we had calculated the means and standard deviations per redshift slice for these results were able to plot them against redshift to produce a more representative picture of how the morphologies of galaxies change with age (higher redshifts mean we are seeing the galaxies earlier in their lifetimes). As can be seen below there is a clear trend in both graphs showing that as a galaxy grows older its radius increases and it becomes larger (however the very large errors on some of the half-light radii in the latter graph should be taken into account and so the first 20%, 50% and 80% graph is probably more reliable). This would seem to confirm the conclusion obtained from the less representative results of our manual visual classifications.
Our result of the week however comes from the Star Formation Rates sub-project who produced the graph below which shows how the lyman alpha star formation rate density changes with redshift. We have chosen this result as it agrees with established theory, showing a decrease in star formation rate density as redshift increases. It should however be noted that this is not strictly the real star formation rate density as it overlooks the fact that space is mostly empty and many fainter galaxies, with lower star formation rates, will have been missed by the survey so the real average star formation rate will be lower than that which we have calculated. This problem can be overcome next week by using the distribution of star formation rates and producing and integrating a star formation rate function (number of galaxies per volume per star formation rate).