4th Blog Post: Visual Classification of Galaxies

I have spent most of this week preparing for the presentation that I will be giving about the project on Tuesday, as well as writing a report about the career path of Ana Afonso, a PhD student in the XGAL group and reading and presenting a paper about the importance of tides for life on exoplanets.

I also attempted to analyse the effects of increasing the vote threshold on the Galaxy Zoo data to see if the patterns spotted last week held for galaxies that had more than 90% of the vote for being mergers, but found that there were so few of these galaxies that no pattern could be discerned.

I apologise for this post being so short!

3rd Blog Post: Visual Classification of Galaxies

This week, I have been analysing data about the type of environment in which galactic mergers happen. I have combined my results and the results of Galaxy Zoo with data about the density of galaxies in the superstructure to see whether mergers are more common in denser or less dense regions.

This animation shows the numbers of mergers at each value of ‘logdelta’ for ten intervals of 0.01 redshift between redshifts of 0.8 and 0.9.

The higher the redshift, the further back in time we look, so in a way this animation shows a progression backwards in time of the superstructure. Each of the bands at the bottom of the image represents a different ‘density bin’- the blue colour scheme shows low density, the pink colour scheme shows intermediate density and the green/blue colour scheme shows high density.

As is visible, there is a general trend towards mergers in intermediate density environments further back in time and in higher density environments further forward in time. This could be because as galaxies merge and interact there are more galaxies in a higher density environment and so more mergers happen there.

This animation shows the physical locations of the mergers that I classified going from redshift 0.8 to redshift 0.9 with the density of galaxies. The red stars represent mergers.

The above animation seems to show that the mergers usually occur in higher density areas and can be seen to ‘track’ the high-density areas as they move around. Similarly to the graph, this shows that the mergers I classified occur in intermediate to high-density areas. This would make sense given that mergers require galaxies to be near each other to occur.

This animation is similar to the previous animation, but shows galaxies that more than 50% of people said were merging and covers many more galaxies than I classified.

Again, it can be seen that the mergers roughly follow the high-density areas as the redshift changes. It is possible that this trend would be more marked if only galaxies with a higher percentage of the vote for being a merger were used, but I have not yet tested this hypothesis.

2nd Blog Post: Visual Classification of Galaxies

This week, I have finished classifying the 696 galaxies and have classified 124 extra galaxies- which turned out to all be galaxies that were part of the first set. The idea of doing this was to classify some galaxies twice (without knowing that was what I was doing) so that I can compare the results from both classifications and see how they are different. I have found that it is quite possible to disagree with yourself. I have created some graphs to analyse the results from the classification. I have also performed a similar analysis on some results from the Galaxy Zoo project (for more information go to https://www.galaxyzoo.org), which contains classifications for about 900,000 galaxies, to give a far more detailed picture of the distribution of galaxies in the local universe.

This is a 3D graph showing the spacial locations of merging galaxies in the most densely populated (or sampled) region of galaxies. The magenta dots show galaxies that are not merging and the blue dots show galaxies that are merging. Earlier results had shown that this area of the superstructure contained the highest density of mergers, and at first glance it seems that within this volume most mergers are occurring in the area that appears towards the top of this image, but further analysis will need to be performed.

This graph shows the types of galaxies that were classified in the first sample (of 696 galaxies) in red, and the second sample (of 124 galaxies), in blue. 0 represents point-like galaxies, 1 represents elliptical galaxies, 2 represents disky galaxies, 3 represents irregular galaxies, 9 represents galaxies that are too faint to classify and -9 represents images that do not contain a galaxy. As you can see, more elliptical galaxies were classified in the sample of 124 galaxies than were classified in the entire 696 galaxies the first time. I expected this because I had changed the definition I was using to classify ellipticals, but the effect of this was more dramatic than anticipated.

Finally, this graph, made using the data from Galaxy Zoo, shows the effect of a debiasing process applied by the Galaxy Zoo team on the classifications made of ellipticals. The red bars show the biased results (those collected from people classifying galaxies) and the blue bars show the unbiased results (voted on by the Galaxy Zoo team), and the curves in the corresponding colours show the distribution of each set of results. This graph demonstrates that there is a tendency in inexperienced humans to not classify elliptical galaxies as such- the same tendency I showed in my first set of classifications.

1st Blog Post: Visual Classification of Galaxies

Hello, welcome to the project blog for the visual classification of galaxies in a super-structure project. My name is Jess. Please follow the links if you would like to learn more about me or about the project.

This week, I have classified 591 galaxies (out of 696), although some of these were repeated images. I’ve found that the pace at which I can classify has got progressively faster each day. Hence, I have gone from classifying about 50 galaxies in a day to over 200 over the course of this week, which means the classification will be finished sooner than I had anticipated. Once the classification is finished, the data gathered can be analysed and perhaps you will be able to read about that in next week’s blog post.

For now, I would like to explain the system I have been using to classify galaxies and show you some of the galaxies that I found most interesting.

I classify galaxies according to their shape first- identifying whether they have a disc (a less dense area of stars around a central bright area called a bulge), are elliptical (uniform brightness in an ellipse shape), are point-like or are irregularly shaped. Discs are typical of younger galaxies that are forming stars and often show spiral patterns (which can look very pretty!), whereas ellipses can indicate an older galaxy that is not forming stars any more. I also say whether two galaxies are merging or if a galaxy has multiple bright spots, in which case it is called a clumpy galaxy, and measure its size. I can also choose or reverse the colour scheme so that I can see the galaxy more clearly, or just to prevent my eyes from tiring.

This first galaxy is a spiral with an arc-shaped clump at the bottom left. It appears to be pulled towards another galaxy but on further inspection it turns out to not be merging- the shape is interesting though.

This galaxy is interesting because it remains ambiguous for now. It looks like it might be merging or could just be clumpy but spectroscopy (analysis of the elements found in the galaxy) couldn’t decide if an interaction was taking place, so this will have to be determined by other methods.

Thanks for reading- see you next time!

Jess