We’ve won a prize! The Royal Astronomical Society has given the Galaxy Zoo team – including the volunteers who have made the project the success it is – their Group Achievement Award for 2019. I will post the citation below, but mostly I’m delighted that this award recognises all those who have worked to make Galaxy Zoo a success.
Looking at the list of previous winners – the last two are the team behind ESA’s Planck satellite and the team who made the Nobel winning discovery of gravitational waves – is humbling, so this is really something to be proud of.
We’ll make plans to make sure everyone can celebrate the award when it’s presented at the National Astronomy Meeting later in the year.
Citation for the 2019 RAS Group Achievement Award (A)
The 2019 Group Achievement Award is awarded to the Galaxy Zoo team. With over ten years of engagement under their belt, the Galaxy Zoo team have contributed significantly to our knowledge of the formation and evolution of galaxies, through strong commitment to collaboration with members of the public. They have established citizen science as a standard mode of data analysis across astrophysics, and initiated new areas of research sparked by Galaxy Zoo discoveries. Their roughly 55 papers, ranging from studies disentangling morphology, environment and colour, through to studies of individual morphological characteristics, have been enabled by the team’s careful work to create catalogues and measure systematic effects inherent in the classification, before releasing the data to the community.
The Galaxy Zoo project has also inspired many similar projects across astrophysics and beyond, through the Zooniverse platform. Perhaps Galaxy Zoo’s most notable achievement is immensely effective outreach: the more than 500,000 people who have contributed to date come from a wide range of backgrounds, making participation in scientific research possible for all. Galaxy Zoo inspires and informs, and does so on an unprecedented scale. For these reasons, the Galaxy Zoo team is awarded the Group Achievement Award.
Happy 5th birthday to Radio Galaxy Zoo!
We have now completed 84% of the project and reached 2.24 million classifications (the equivalent of ~90.2 years of work) thanks to all the hard work from our Radio Galaxy Zooites. So much has happened in the world of Radio Galaxy Zoo this year and many of the new scientific results we reported cannot have happened without your help.
In 2018, we had 4 papers accepted for publication in the Monthly Notices of the Royal Astronomical Society, doubling the number of papers that Radio Galaxy Zoo previously published. In addition, we have three more Radio Galaxy Zoo papers that have been submitted this year and are currently undergoing the refereeing process.
As always, our science papers can be freely-accessed and so I encourage you all to check out the following papers if you are interested. Here is the list of papers published this year:
1) Radio Galaxy Zoo: compact and extended radio source classification with deep learning by Vesna Lukic et al
2) Radio Galaxy Zoo: machine learning for radio source host galaxy cross-identification by Matthew Alger et al
3) Radio Galaxy Zoo: CLARAN – a deep learning classifier for radio morphologies
by Chen Wu et al
4) Radio Galaxy Zoo: observational evidence for environment as the cause of radio source asymmetry by Payton Rodman et al
As we summarise the main events this year, it would be remiss of me to not mention the retirement of our previous co-Primary Investigator (co-PI) as well as original driver of this project, Dr Julie Banfield, without whom Radio Galaxy Zoo wouldn’t be where it is today. We continue to be very grateful for her hard work and support. Finally, I would like to thank Dr Stas Shabala for agreeing to be a co-PI on this project after Julie’s departure for greener pastures.
Thank you all very much again for all your help and we shall continue to report on the science that is made possible thanks to you all. Keep up the awesome work! We hope that you all have a happy end-of-2018 and an excellent 2019.
Ivy & Stas
One of the most enduring serendipitous finds of the original Galaxy Zoo was a category of giant gas clouds shining from the energy input of active galactic nuclei (AGN) which have since faded (being a little cavalier here with time and verb tenses, since we can’t get news faster than light travels). The most famous of the is of course Hanny’s Voorwerp, whose discovery led to subprojects which turned up many more (“Voorwerpjes”). We have new results now on a related project going back to the Galaxy Zoo Forum, where we searched for gas in companions to active galaxies which is ionized by the AGN, and therefore gives us one more way to learn about how bright the AGN was tens of thousands of years before our direct view. Read More…
Radio Galaxy Zoo: what radio lobe shapes tell us about the mutual impact of jets and intergalactic gas
The following blogpost is from Stas Shabala about the Radio Galaxy Zoo paper led by his student, Payton Rodman, exploring the origin of asymmetries observed in a sample of Radio Galaxy Zoo radio galaxies.
Another Radio Galaxy Zoo paper has just been accepted for publication. “Radio Galaxy Zoo: Observational evidence for environment as the cause of radio source asymmetry” will shortly appear in Monthly Notices of the Royal Astronomical Society, and is already available on the preprint server (https://arxiv.org/abs/1811.03726). This paper, led by University of Tasmania undergraduate student Payton Rodman, looks at the properties of lobes in powerful radio galaxies. These lobes are inflated by a pair of jets, emerging in opposite directions from the accretion disk of the black hole at the centre of their host galaxy. Astronomers have known for a while that how big, bright or wide the radio lobes are depends on the properties of the intergalactic gas into which these lobes expand. Small, slow-growing lobes are usually found in galaxy clusters, while their large, rapidly expanding cousins tend to stay away from such dense environments. Radio lobes move about and heat intergalactic gas, and in this way they are thought to be responsible for regulating the formation of stars (by staving off the gravitational collapse of cold gas) in massive galaxies over the last eight billion years. Because of this, understanding how jets and lobes interact with their surroundings is important for understanding the history of the Universe. What complicates matters is that the mechanisms responsible for feeding the black hole and generating jets are also different in these two environments. So does nature or nurture determine what the lobes look like?
We decided to use the fact that all radio galaxies start out with two intrinsically identical jets propagating in opposite directions. If the two resultant lobes look different, this could only be due to the interaction with the surrounding gas – in other words, nurture. To test the nurture hypothesis, we used the first tranche of Radio Galaxy Zoo classifications. We selected all sources classified by citizen scientists to contain two clear radio lobes, and subjected this sample to a number of rigorous cuts on brightness, shape, redshift, and availability of environment information. Hot intergalactic gas is usually traced by X-ray observations, but these are unavailable for the majority of the sample. Instead, we used the clustering of optical galaxies from the Sloan Digital Sky Survey, which should be a good proxy for the underlying gas distribution. Then, for each radio galaxy, we compared the properties of the two radio lobes to how many galaxies were found near each of the lobes. We found a clear anti-correlation between the length of the radio lobe, and the number of nearby galaxies – in other words, shorter lobes have more galaxies surrounding them. These results were in excellent agreement with quantitative predictions from models (such as this hydrodynamic simulation made on the University of Tasmania’s supercomputer by PhD student Patrick Yates), which show that it is more difficult for lobes to expand into dense environments. The relationship between the luminosity of the lobes and galaxy clustering was much less clear, again consistent with models which predict a highly non-linear luminosity evolution as the lobes grow.
The excellent agreement between models and observations suggests that it is nurture, not nature, which determines lobe properties. It also opens up a new way of studying radio galaxy environments: though sensitive observations of optical galaxy clustering. With help from Zooites, we hope to expand this work to a much larger Radio Galaxy Zoo sample, which would allow us to probe the finer aspects of jet – environment interaction. Further afield, the ongoing GAMA Legacy ATCA Southern Survey (GLASS) project on the Australia Telescope Compact Array, as well as the Australian Square Kilometre Array Pathfinder EMU survey, will use this method to study the physics of black hole jets and the impact they have on their surroundings in a younger Universe.
On the 31 October 2018, Radio Galaxy Zoo published its first end-to-end machine learning system for “Classifying Radio sources Automatically using Neural networks” (ClaRAN). This paper is led by ClaRAN’s developer, Chen Wu, a data scientist at the International Centre for Radio Astronomy Research at the University of Western Australia (ICRAR/UWA), who repurposed the FAST-rCNN algorithm (used by Microsoft and Facebook) to classify radio galaxies. ClaRAN was trained on radio galaxies classified by Radio Galaxy Zoo and so recognises some of the most common radio morphologies that have been classified.
The purpose of ClaRAN is to reduce the number of radio sources that require human visual classification so that future Radio Galaxy Zoo projects will have fewer “boring” sources, thereby increasing the chances of real discoveries by citizen scientists. ClaRAN (and its future cousins) are crucial for future surveys such as the EMU survey which is expected to detect ~70 million radio sources (using the Australian Square Kilometre Array Pathfinder telescope). While Radio Galaxy Zoo has made visual source classifications much more efficient, we will still need to reduce the total survey sample size to a sample for visual inspection that is less than 1% of the 70 million sources.
How does ClaRAN work? ClaRAN inspects both the radio and coordinate-matched infrared overlay in the same fashion as RGZ Zooites, and then determines the radio source component associations in a similar fashion to the RGZ Data Release 1 (DR1) catalogue. As ClaRAN is still in its prototype stage (–analogous to the capabilities of a toddler), it only understands 3 main classes of radio morphologies — sources which have 1-, 2- or 3- separate radio components. ClaRAN was trained to understand these three different radio morphologies through seeing examples of all three classes from the RGZ DR1 catalogue. The animated gif (from the ICRAR press release) describes how ClaRAN “sees” the example radio galaxy. Please do not click on the link to the animated gif if you suffer from epilepsy or have any issues with flashing images.
As we look towards the future, we look forward to teaching ClaRAN some of
the more complex and exotic radio galaxy structures. For that to happen, we need to assemble much larger samples of more complex radio morphology classifications. With your support of Radio Galaxy Zoo, I am sure that we will get there.
Fun fact: did you know that some of the more obscure bugs in the RGZ DR1 catalogue processing was actually found through training ClaRAN? This is because ClaRAN is a good learner and will learn all the small details that we didn’t initially notice. We only discovered these bugs through some of the funny answers that we got out of some of the early testing of ClaRAN.
Thank you very much again to all our Radio Galaxy Zooites for your support. More information on the ICRAR press release for ClaRAN can be found via this link: https://www.icrar.org/claran/
Just a quick post to say thank you for your contributions to Galaxy Zoo: 3D in the last couple of weeks. I’m delighted to say that the bar drawing task is now completed. We still have a lot of spirals to draw though, so if you are ready for a challenge come join us in drawing these beautiful structures. Remember we collect 15 answers per galaxy, and use clever algorithms to combine them into a really reliable answer – so do your best, but don’t get too worried if your hand slips slightly! 🙂
I’m posting this on behalf of Amelia Frasier-McKelvie, a postdoc at the University of Nottingham, UK.
Hi – I’m Amelia, and I’m a postdoctoral researcher at the University of Nottingham. I work on galaxy evolution using the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (and yes, I know it’s a contrived acronym!) MaNGA aims to observe 10,000 galaxies using integral field spectroscopy, which means instead of just obtaining one spectrum of a galaxy, we take several hundred at all different points across a galaxy. From this, we can infer interesting spatial information on galaxy properties. For example, we can see the regions in which star formation is occurring, or compare the ages of the stars in the bulge regions of a galaxy to the outer disk. By breaking down a galaxy into its components (such as bulge, disk, spiral arms, and bar) we can discover more about how the galaxy formed, and how it has led its life so far.
I’m really interested in how bars affect their host galaxies. In particular, I’m looking for observational evidence that bars are involved in the quenching of star formation within a galaxy. This phenomenon is known as secular evolution/quenching. The one thing a galaxy needs to form stars is a reservoir of cool hydrogen gas. It’s been postulated that a bar can transfer matter (such as gas) radially inwards through a galaxy’s disk and into its central regions. If this is the case, then maybe it takes this gas required for star formation and funnels it towards the galactic centre, starving the disk, and ceasing star formation. Simultaneously, this gas that is funnelled into the central regions could either induce a final starburst, using up all gas, or feed an active galactic nucleus (AGN), which can heat the gas to a point where it cannot collapse to form stars.
If we wanted to catch a bar in the act of quenching a galaxy, we could look for tell-tale signs of this funnelling action, namely a difference in the age and chemical composition of the stellar populations in the bar region of a galaxy when compared to the disk.
This is where Galaxy Zoo 3D comes in — I need to know where the bars actually lie in their host galaxies! Galaxy Zoo 3D citizen scientists mark out the bar (and spiral arm) regions of the MaNGA galaxy sample, which I can apply to our data cubes and extract spectra belonging to the galactic bar and disk regions. I can then analyse the bar and disk spectra separately and compare their properties. I’m interested in the global properties of a large sample of galaxies, so I need as many bar and disk region classifications as possible!
If I can find observational evidence that bars are helping to quench galaxies this will confirm the idea that internal secular evolutionary processes are important in galaxy evolution.
This will prove that along with external factors, internal structures such as bars are extremely important in determining a galaxy’s fate!
We hope you enjoyed hearing about how the masks made in Galaxy Zoo: 3D are being used. There’s still plenty of bars and lots and lots of spirals to mark in the project, so please join in if you’d like to help us complete our sample and help Amelia and others (including me!) with their research.
Some of you may remember a while back we posted a blog announcing that we would be testing a new messaging system on Galaxy Zoo. Some of you may even have seen these messages while classifying on the site! This test was also part of a study of how we could use messaging to increase engagement on the project. Working with researchers from Ben Gurion University and Microsoft Research we delivered messages to volunteers at key times during their participation on Galaxy Zoo and observed how these messages affected their engagement. This research was based on previous work we had done that demonstrated that sending similar messages in emails could increase the likelihood of volunteers returning and engaging more with the project.
The volunteers were split into three main cohorts; One group who were delivered the messages at random intervals, one group who were delivered the messages at what were predicted to be optimal times, and a final control group who received no messages. This study has led to two peer-reviewed publications and the results show that optimal timing of an intervention message can significantly increase the engagement of volunteers on Galaxy Zoo.
These early results are intriguing, and we’d like to do more tests to see if it’s something we can use more broadly across Zooniverse projects. The same machinery might also be used by Zooniverse teams to send messages to volunteers – either in a group or individually – as they participate in their projects. We’ll keep you informed on the blog.
To read about the study and its finding in more detail please see the following papers:
For a discussion regarding the ethics of this study, please read this Zooniverse Talk thread https://www.zooniverse.org/talk/14/675633.
For the past few years, a new Galaxy Zoo project has been under development. This project allows the creation of models of galaxies inside the Zooniverse website (although in a slightly experimental fashion). Many of you helped trial this project in December of 2017, and some have classified since it was quietly launched in late April. I’d like to take this opportunity to share with you some of the early results we have obtained from your classifications!
From the beta
260 of you helped beta test and debug the project in our beta, providing invaluable feedback (most of which we hope we addressed!) and submitting over one thousand test classifications of our small test sample. One of the images in this sample was the SDSS r-band image of the galaxy below, catchily known as SDSS J104238.12+235706.8.
In this post we’ll look specifically at the spiral arms drawn on this galaxy, and how we can recover information about the shape of the spirals from your drawn arms. If we plot every spiral arm drawn on the galaxy, two distinct spiral appear:
There are a number of classifications which have either crossed the center of the galaxy, linking the two arms with one line, or which attempt to enclose the spiral (as in the GZ:3D project) rather than tracing along the center line. This confusion arose from the short tutorial and confusing help text present in the beta, which was flagged by our testers (thank you!).
We can make use of unsupervised machine learning techniques to cluster together these drawn arms, and extract points corresponding to each arm (while throwing away some lines which didn’t fit into our groups).
Taking one arm as an example, we identify points which could be considered outliers, and remove them to improve our later fit (using another unsupervised machine learning technique called Local Outlier Factor). In the image below, red dots correspond to points identified as outliers, and the blue contours can be seen as a probability map, with points in regions of darker blue being more likely to be an outlier.
Fitting a spiral
Brilliant – we now have a load of (unordered) points which roughly resemble the spiral arm of our galaxy! We’ll fit a smooth line to obtain a “best guess” of the galaxy’s spiral properties, the result of which can be seen below:
What we’ve discovered from the beta trial is that we need at least 20 attempts at drawing spirals on a galaxy to get reliable answers, so we’re keen to get more people trying to build galaxies on Galaxy Builder.
If you’d like to help please join us at https://www.zooniverse.org/projects/tingard/galaxy-builder. If that’s not your thing we still need classifications on Galaxy Zoo: 3D, and the classic Galaxy Zoo is still live with all new images from the DECaLS survey.
There are various kind of rings we see in galaxies – nuclear, inner, outer, pseudo rings, collisional, accretion, maybe even disk instability at high redshift. We discussed how all of these are thought to form, and enjoyed a parade of beautiful images of ring galaxies.
Spiral arms and how they form were a big discussion at the conference. Bill Keel (who you may now better for his work on overlapping galaxies found in the forum), presented work by the most recent Galaxy Zoo PhD – Dr. Ross Hart (who unfortunately could not make the meeting) on Galaxy Zoo constraints on spirals. This included results from a small side project Spiral Spotter. What is clear from this result (and many others presented at the meeting) on spirals – we really don’t understand which spiral arm formation mechanisms are the most important in galaxies, or how to tell in an individual galaxy which mechanism makes its spirals. There’s a dizzying array of possibilities – so lots of results to test with morphology. Overlapping systems did still get a mention – presented by Benne Holwerda.