I’m delighted to announce the launch of “Galaxy Zoo: 3D” today – this is a small project from a subset of the Galaxy Zoo team where we ask you to help us identify in detail the locations of internal structures seen in a sample of about 30,000 galaxies.
What’s special about these galaxies is that they have been selected to potentially be observed (or in some cases have already been observed) by the “MaNGA” project.
MaNGA (which stands for “Mapping Nearby Galaxies at Apache Point Observatory” – sorry about that!), is a spectroscopic mapping survey that I have been working with for the last several years. This one of the current surveys which form part of the 4th generation of Sloan Digital Sky Surveys.
SDSS retired its camera in 2012 (its in the basement of the Smithsonian Museum in Washington, D.C!), and is now focusing on measuring spectra of things in space. Instead of taking images of galaxies in just a couple of filters, MaNGA takes spectral images – each of up to hundreds of points in the galaxy has a full spectrum measured, which means we can decode the types of stars and gas found in that part of the galaxy. We can also recover the motions of the stars and gas in the galaxy making use of the Doppler shift (the redshift or blue shift we see in light which comes from moving sources).
MaNGA will ultimately do this for about 10,000 of the total list (this is how many we can manage in 6 years of operations), and since 2015 has already measured these data for a bit more than 3000 galaxies. To help us interpret this vast quantity of data we’re asking you to draw on the galaxies to mark the locations of spiral arms and bars. We also want to double check the galaxy centres are recorded correctly, and that we have found all the foreground stars which might be getting in the way of the galaxy.
Now one thing you know all about as Galaxy Zoo volunteers is the benefit of human eyes on large samples of galaxies. When we first launched Galaxy Zoo we made use of the “Main Galaxy Sample” from the Sloan Digital Sky Survey as the input list of galaxies. This is a sample of 1 million galaxies automatically identified from the SDSS images, and which had their distances (redshifts) measured in SDSS-I/II. However (perhaps ironically) the algorithm which selected this sample wasn’t very good at finding the biggest most nearby galaxies. Specifically it tended to “shred” them into what it thought were multiple galaxies. My favourite demonstration of this is the Pinwheel galaxy (M101), which the first SDSS galaxy detection algorithm interpreted as a cluster of galaxies.
(Don’t worry – ever resourceful, astronomers have made plenty of use of these galaxies which have multiple spectra measured – it turns out to be really useful).
By the time MaNGA came along this problem was well known, and instead of making use of the standard SDSS galaxy catalogues, MaNGA targeted nearby galaxies by making use of the “NASA Sloan Atlas“- a NASA funded project to make a more careful list of nearby bright galaxies in the SDSS images.
So what we discovered when putting together the sample for Galaxy Zoo: 3D is that not all MaNGA galaxies have Galaxy Zoo classifications. In fact about 10% are missing, and we also found some more galaxies we missed first time round. It turns out that by relying on automatic galaxy finding there were a quite a few galaxies which had been missed before.
So these are back in the main site right now.
In Galaxy Zoo: 3D we will only ask you to draw spiral arms on galaxies you have previously said have spiral arms, so we’ll be making use of the new classifications to sort out the last 10% of MaNGA galaxies. We’ll also create a complete Galaxy Zoo classification list for the MaNGA sample, which will be really useful for people working with that sample.
To tempt you to give it a go, here are some interesting and beautiful MaNGA galaxies being discussed in Talk by our beta testers (the purple hexagon indicates the part of the galaxy where MaNGA can measure spectra). More than half of all the galaxies in MaNGA them are nearby galaxies with lots of structure. I think you’re really going to enjoy exploring them, and at the same time really help us learn a lot about galaxies.
Following on from the excellent summary of the hi-lights in 2015 for the Radio Galaxy Zoo project, here’s a similar post about results from Galaxy Zoo.
This year we collected 4,755,448 classifications on 209,291 different images of galaxies. You continue to amaze us with your collective efforts. Thank you so much for each and everyone of of these classifications.
The year started with Galaxy Zoo scientists at Mauna Kea observing galaxies, and reported in this wonderful series of blog posts by (former) Zooniverse developer Ed Paget.
We celebrated 8 years of Galaxy Zoo back in July, with this blog series of all things 8-like about Galaxy Zoo.
Back in May we finished collecting classifications on the last of our Hubble Space Telescope images. At the AAS in Florida this week, Kyle Willett and Brooke Simmons presented posters on the planned data releases for the classifications.
We both launched and finished classifying the first set of images of simulated galaxies from the Illustris Simulation (read more here: New Images for Galaxy Zoo: Illustris and here: Finished with First Set of Illustris Images). We also launched our first set of images from the DECaLS survey, which is using the Dark Energy Camera (New Images for Galaxy Zoo: DECaLS)
We also launched a new Galaxy Zoo side project – Galaxy Zoo Bars (one of the first projects built on the new Zooniverse Project Builder software), measuring bar lengths of galaxies in the distant Universe. The entire set were measured in less than a year, so thank you to any of you who contributed to that, and if you missed it don’t worry, we have plans for more special projects this year.
We launched a new web interface to explore the Galaxy Zoo classifications.
Our contributions to the peer reviewed astronomical literature continue. Papers number 45-48 from the team were officially published in 2015. They were:
– Galaxy Zoo: the effect of bar-driven fueling on the presence of an active galactic nucleus in disc galaxies, Galloway+ 2015.
– Galaxy Zoo: Evidence for Diverse Star Formation Histories through the Green Valley, Smethurst+ 2015.
– Galaxy Zoo: the dependence of the star formation-stellar mass relation on spiral disc morphology, Willett+ 2015.
You can access all 48 team papers using your classifications at the Zooniverse Publication Page. Remember that all Zooniverse papers published in the Monthly Notices of the Royal Astronomical Society – which includes most of the Galaxy Zoo papers – are available open access to any reader, and if we happen to publish elsewhere we always make the post-acceptance version available on the arxiv.org.
All of our papers include a version of this acknowledgement to our classifiers: “The data in this paper are the result of the efforts of the Galaxy Zoo volunteers, without whom none of this work would be possible. Their efforts are individually acknowledged at authors.galaxyzoo.org.” We all hope you all know how grateful we are for each and every one of your classifications.
This year saw publication of the first paper on Hubble observations of Voorwerpje systems accompanied by an HST press release.
One of those papers from (mostly) outside the GZ team discussed a rare examples of double radio sources from spiral hosts, something Radio Galaxy Zoo will find many more of: “J1649+2635: a grand-design spiral with a large double-lobed radio source”, Mao et al. 2015.
Another exciting thing about this year has been the number of papers from non team members using the classifications which are now public (see data.galaxyzoo.org). To date almost 300 astronomical papers have been written which cite the original description of Galaxy Zoo (Lintott et al. 2008) and the two data release papers so far (Lintott et al. 2011 for GZ1 and Willett et al. 2013 for GZ2) have 164 and 34 citations respectively. The number of papers in the Astrophysics Data System which contain the words “Galaxy Zoo” (which you can search in ADS Labs) is an astonishing 700 (409 for refereed publications).
These are just some of the high-lights I’ve pulled together. If I’ve missed your favourite feel free to add it in the comments below. All in all it’s been a great year. Here’s to an equally good 2016!
The below blog post was written by Alex Todd, an Ogden Summer Intern who spent the summer working on Galaxy Zoo related research projects at the University of Portsmouth. Alex is now off to his next adventure – starting his undergraduate degree in Natural Sciences at the University of Bath.
I have been working with the Galaxy Zoo team at the Institute of Cosmology and Gravitation, in Portsmouth, for 8 weeks this summer. I have been analysing the results of Galaxy Zoo 2, and more specifically the region of the sky known as Stripe 82. In this area, the Sloan Digital Sky Survey (SDSS) took many images of the same patch of sky, instead of only one. These images were combined to produce a single, higher quality image, which showed fainter details and objects. Both these deeper images and the standard depth images of stripe 82 were put into galaxy zoo, and I have been comparing the resulting classifications. I learned to code in python, a programming language, and used it to produce graphs from the data I downloaded from the Galaxy Zoo website. I started by comparing the results directly, comparing the number of people who said that the galaxy had features in each of the image depths.
On the graph, each blue dot is a galaxy (there are around 4,000) and the red dashed line shows the overall trend. As you can see from the graph, when the proportion of people who see features is low, there is a good match between the two image depths. However, when the proportion is high, there is a much bigger difference between the two image depths, with the proportion being higher in the deep image. This is because fainter features are visible in the deeper image.
I then plotted graphs of the difference between the proportions (P(Features)) against the brightness of the galaxy. To measure the brightness, I used the apparent magnitude, a measure of how bright the galaxy appears to us (as opposed to how bright it actually is).
The graph below shows the difference in P(Features) plotted against the apparent magnitude. The blue line is at y=0, and the green line represents the average value of the difference between P(Features). As you can see, there is not much difference between the values of P(Features) when the galaxy is particularly bright (Small apparent magnitude) or when it is particularly dim (large apparent magnitude). However, when the galaxy has an average brightness, the difference is quite substantial. We think this is because in bright galaxies, features can be seen in both images, whilst in dim galaxies they can be seen in neither. In medium brightness galaxies, however, they can only be seen in the deeper image. The fact that there are differences between the classifications means that it would be a good idea to classify deeper images of the rest of the sky, to hopefully improve the accuracy of the classifications.
I have greatly enjoyed my time working on at the ICG on galaxy zoo, and would certainly seize the opportunity to pursue it further.
It’s been a pleasure working with Alex this summer. He really impressed me with the speed at which he picked up programming languages. This information about the differences in perception of morphological features between deeper and shallower images is very useful to us as a science team as we plan for future generations of the Galaxy Zoo project with new, more sensitive images from current and ongoing astronomical surveys.
Next up in our series of eight blog posts celebrating eight years of Galaxy Zoo is this post from Tom Melvin, who was the lead author of the the first publication from Galaxy Zoo: Hubble, which looked at how the fraction of barred disk galaxies has evolved over the last eight billion years. Tom is also the first person to write a PhD thesis substantially based on Galaxy Zoo classifications, which he is in the process of completing final corrections for.
This was the first time the Galaxy Zoo volunteers had been asked to classify galaxies taken by the Hubble Space Telescope, which provided beautiful images of galaxies whose light has taken up to eight billion light years to reach us!
With your classifications, we were able to select a sample of disk and barred disk galaxies, as shown above in Figure 1, and explore how the fraction of disk galaxies that are barred has evolved over the last eight billion years. We found that this bar fraction has been increasing as the Universe has grown older, doubling from 11% eight billion years ago to 22% four billion years ago, which is shown below in Figure 2. We also know from Galaxy Zoo 2 that this continues to increase, with around one third of disks having a bar in our local Universe. We were able to expand on this by showing that it was the most massive disk galaxies that were the driver of this evolution.
As bars tend to only form in disk galaxies that are settled and relaxed, or ‘mature’, our results showing an increasing bar fraction over the last eight billion years tells us that the disk galaxy population has matured as the Universe has aged. As this evolution is being driven by the most massive disk galaxies, we were able to conclude that the most massive disk galaxies become mature sooner than their lower mass counterparts.
In addition to these results, we were able to identify a population of ‘red spiral’ galaxies thanks to your classifications. These red spirals’ would typically be omitted from other disk samples, as they would be classified as elliptical galaxies – but as you can see below, these are clearly beautiful red spiral galaxies! What is interesting about this population of disks is that their bar fraction of 45% is much higher than the bar fraction of the whole disk sample, which is roughly 14%.
So, thanks to your help classifying the amazing images from the Hubble Space Telescope, we were able to track the evolving bar fraction of disk galaxies over the last eight billion years. There is plenty more to be done with this sample of galaxies, so keep an eye out for future results looking at how galaxies have evolved over the past eight billion years!
At Galaxy Zoo we’re really proud of our publication record – 48 papers and counting, just from the team using your classifications. In academic research one of the most important numbers a published paper has is the number which counts how many citations that paper has – simply a count of the number of other academic publications mention your work.
And we’re not only proud of the Galaxy Zoo publication record, but the citation record is becoming impressive too (if we do say so ourselves). For this post in the lead up to the 8th anniversary of the launch of Galaxy Zoo, here are the 8 most cited of our papers:
1. Lintott et al. 2008: “Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey “(with 279 citations)
2. Bamford et al. 2009: “Galaxy Zoo: the dependence of morphology and colour on environment” (219 citations)
3. Lintott et al. 2011: “Galaxy Zoo 1: data release of morphological classifications for nearly 900 000 galaxies” (152 citations)
4. Skibba et al. 2009: “Galaxy Zoo: disentangling the environmental dependence of morphology and colour” (114 citations)
5. Schawinski et al. 2010: “Galaxy Zoo: The Fundamentally Different Co-Evolution of Supermassive Black Holes and Their Early- and Late-Type Host Galaxies” (102 citations)
6. Cardamone et al. 2009: “Galaxy Zoo Green Peas: discovery of a class of compact extremely star-forming galaxies” (101 citations)
7. Darg et al 2010: “Galaxy Zoo: the properties of merging galaxies in the nearby Universe – local environments, colours, masses, star formation rates and AGN activity” (92 citations)
8. Masters et al. 2010: “Galaxy Zoo: passive red spirals” (86 citations)
I’m personally especially proud of paper number 8 on that list, because it is one of the first papers I led making use of Galaxy Zoo classifications (and one of my most cited first author papers in fact). In that paper we explored the properties of the unusually passive (ie. not star forming) red spirals that had been noted in both Bamford et al. 2009 and Skibba et al. 2009. For astronomers this is one of the more well known discoveries from Galaxy Zoo, and these passive red spirals continue to be studied for what they can reveal about the modes of evolution of galaxies in our Universe, and that many spirals must stop forming stars before they lose their spiral structure.
(By the way for academics who might be interested the h-index of Galaxy Zoo is 24).
We’re delighted to announce that we have some new images on Galaxy Zoo for you to classify! There are two sets of new images:
1. Galaxies from the CANDELS survey
2. Galaxies from the GOODS survey
The general look of these images should be quite familiar to our regular classifiers, and we’ve already described them in many previous posts (examples: here, here, and here), so they may not need too much explanation. The only difference for these new images are their sensitivities: the GOODS images are made from more HST orbits and are deeper, so you should be able to better see details in a larger number of galaxies compared to HST.
The new CANDELS images, however, are slightly shallower than before. The main reason that these are being included is to help us get data measuring the effect of brightness and imaging depth for your crowdsourced classifications. While they aren’t always as visually stunning as nearby SDSS or HST images, getting accurate data is really crucial for the science we want to do on high-redshift objects, and so we hope you’ll give the new images your best efforts.
Both of these datasets are relatively small compared to the full Sloan Digital Sky Survey (SDSS) and Hubble Space Telescope (HST) sets that users have helped us with over the last several years. With about 13,000 total images, we hope that they’ll can be finished by the Galaxy Zoo community within a couple months. We already have more sets of data prepared for as soon as these finish – stay tuned for Part 2 coming up shortly!
As always, thanks to everyone for their help – please ask the scientists or moderators here or on Talk if you have any questions!
Since our discovery in 2010 that the red spirals identified by your classifications in the first phase of Galaxy Zoo were twice as likely to host galactic scale bars as normal blue spirals, a lot of our research time has focused on understanding which types of galaxies host bars, and why that might be.
Our research with the bars identified by you in the second phase of Galaxy Zoo continues to gives us hints that these structures in galaxies might be involved in the process which quenches star formation in spiral galaxies and through that could be part of the process involved in the reduction of star formation in the universe as a whole.
We’ve also used your classifications as part of Galaxy Zoo Hubble and Galaxy Zoo CANDELS to identify the epoch in the universe when disc galaxies were first stable enough to host a significant number of bars, finding them possibly even earlier in the Universe than was previously thought.
Last Friday I spoke at the monthly “Ordinary Meeting” of the Royal Astronomical Society, giving summary of the evidence we’re collecting on the impact bars have on galaxies thanks to your classifications (a video of my talk will be available at some point). This was the second time I’ve spoken at this meeting about results from Galaxy Zoo, and it’s a delightful mix of professional colleagues, and enthusiastic amateurs – including some Galaxy Zoo volunteers.
Prompted by that I thought it was timely to write on this blog about what these bars really are, what they do to galaxies, and why I think they’re so interesting. I wrote the below some time ago when I had a spare few minutes, and was just looking for the right time to post it.
The thing about galaxies, which is sometimes hard to remember, is that they are simply vast collections of stars, and that those stars are all constantly in motion, orbiting their common centre of mass. The structures that we see in galaxies are just a snapshot of the locations of those stars right now (on a cosmic timescale), and the patterns we see in the positions of the stars reveals patterns in their orbital motions. A stellar bar for example reveals a set of very elongated orbits of stars in the disc of a galaxy.
Another extraordinary thing about a disc galaxy is how thin it is. To put this is perspective I’ll give you a real world example. In the Haus der Astronomie in Heidelberg you can walk around inside a scale model of the Whirlpool galaxy. The whole building was laid out in a design which reflects the spiral arms of this galaxy. However it’s not an exact scale model – to properly represent the thickness of the disc of the Whirlpool galaxy the building (which in actual fact has 3 stories and hosts a fairly large planetarium in its centre) would have to be only 90cm tall…..
Such an incredibly thin disc of stars floating independently in space would be quite unstable dynamically (meaning its own gravity should cause it to buckle and collapse on itself). This instability would immediately manifest in elongated orbits of stars, which would make a stellar bar (as part of this process of collapse). Simple computer models of disks of stars immediately form bars. Of course we now know that galaxy discs are submerged in massive halos of dark matter. So my first favourite little fact about bars is
(1) the fact that not all disc galaxies have bars was put forward as evidence that the discs must be embedded in massive halos before the existence of dark matter was widely accepted.
Now we can model dark matter halos better we discover that even with a dark matter halo, as long as that halo can absorb angular momentum (ie. rotate a bit) all discs will eventually make a bar. So my second favourite little fact is that
(2) we still don’t understand why not all disc galaxies have bars.
What this second fact means is that perhaps what I should really be doing is studying the galaxies you have identified as not having bars to figure out why it is they haven’t been able to form a bar yet. It should really be the properties of these which are unexpected….. We find that this is more likely to happen in blue, intermediate mass spirals with a significant reservoir of atomic hydrogen (the raw material for future star formation). In fact this last thing may be the most significant. Including realistic interstellar gas in computer simulation of galaxies is very difficult, but people do run what is called “smooth particle hydrodynamic” simulations (basically making “particles” of gas and inserting the appropriate properties). If they add too much gas into these simulations they find that bar formation is either very delayed, or doesn’t happen in the time of the simulation…..
Anyway I hope this has given you a flavour of what I find interesting about bars in galaxies. I think it’s fascinating that they give us a morphological way to identify a process which is so dynamical in nature. And it’s a very complex process, even though the basic physics (just orbits of stars) is very simple and well understood. Finally, I have become convinced though tests of the bars identified by you in Galaxy Zoo compared to bars identified by other methods, that if you want a clean sample of very large bars in galaxies that multiple independent human eyes will give you the best result. You are much less easy to trick that automated methods for finding galactic bars.
So thanks again for the classifications, and keep clicking. 🙂
Seasons Greetings for the end of 2014, and many thanks for all the classifications you provided for us at Galaxy Zoo this year!
I am very happy to present the results from the first published paper based on your classifications of the HST-CANDELS Images.
Galaxy Zoo: CANDELS combined optical and infrared imaging from the Hubble Space Telescope, which allows us to probe galaxies back to when the universe was only around 3 billion years old (early than we could do with optical HST images alone). So we are looking at galaxies whose light has taken over 10 billion years to reach us!
Our first area of research with this data is to look at disk and barred disk galaxies, as the title suggests…….
This work is based on an initial sample of 876 disk galaxies, which are from the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS). We want to explore what happens to barred disk galaxies beyond eight billion years ago, building on our work looking at the evolving bar fraction with Galaxy Zoo: Hubble.
When we began this work, we were unsure what we would find when looking so far back. From our Galaxy Zoo: Hubble work we had identified that 10% of disk galaxies hosted a galactic bar eight billion years ago, but beyond this our knowledge of disks was limited to a single simulation of disk galaxies. This simulation predicted that bars in disk galaxies were very rare beyond the epoch we had observed to, as the Universe would be to young for disk galaxies to
have settled down enough to form barred structures.
As Figure 1 shows, we actually find that roughly 10% of all disk galaxies host a bar, even back to when the Universe was only 3 billion years old! This is a very exciting result, as it shows that disk galaxies were able to settle at much earlier times than originally believed.
What we need to understand now is how do these disk galaxies form their bars? Could they be completely settled disk galaxies which have naturally formed bars, even during this epoch of violent galaxy evolution where galaxy mergers are more frequent? Or were these bars formed by a galaxy-galaxy interaction, as seen by some simulations? The answer could be one or the other, or most likely a combination of these two theories. Either way, we hope to explore this population of barred disk galaxies in greater detail over the coming months!
So there is a summary of the first Galaxy Zoo: CANDELS paper. If you would like to see this in more detail, please take a look at the paper here, and why not check out the RAS press release too! Thank you all for your hard work, and keep classifying!
Posted on behalf of Tom Melvin.