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One Million for Zooniverse – and One for Galaxy Zoo!

one million in galaxies

Galaxy Zoo started in 2007 because astronomers had 1,000,000 galaxies that needed to be sorted, classified, and examined. After the incredible response from the public, the zookeepers realized that this kind of problem wasn’t limited to galaxies, nor even just to astronomy, and the Zooniverse was born.

Now, seven actual years, close to 30 projectsmore than 60 publications, and hundreds of years’ worth of human effort later, the Zooniverse has just registered its 1,000,000th volunteer. Given that Galaxy Zoo was the project that led to the creation of the Zooniverse, it seems fitting that its millionth citizen scientist joined to classify galaxies! That volunteer (whose identity we won’t divulge unless s/he gives us permission) joins over 400,000 others who have classified galaxies near and far. That number is 40% of the Zooniverse’s overall total — meaning that, while Galaxy Zoo has a large and vibrant community of volunteers and scientists, most people who join Zooniverse start off contributing to a different project. Many of them try other projects after their first: over on the Zooniverse blog Rob described the additions we’ve made to the Zooniverse Home area so that everyone who brought us to a million can see their own contribution “fingerprint” on the Zooniverse. Here’s what mine currently looks like:

The blue at the left is Galaxy Zoo; the orange is Snapshot Serengeti. #addict

The blue at the left is Galaxy Zoo; the dark orange is Snapshot Serengeti. #addict

Our millionth volunteer gets a cheesy prize (but hopefully useful: a Zooniverse tote bag and mug), and while we’d like to give that same prize to the 999,999 who came before him/her and to everyone who contributes to Galaxy Zoo and all Zooniverse projects, perhaps it’s more fitting that we say to everyone what’s really on our mind right now:

Galactic-Scale Gratitude. You all are awesome.

Galactic-Scale Gratitude. You all are awesome.

The Green Valley is a Red Herring

Great news everybody! The latest Galaxy Zoo 1 paper has been accepted by MNRAS and has appeared on astro-ph:

In this paper, we take a look at the most crucial event in the life of a galaxy: the end of star formation. We often call this process “quenching” and many astrophysicists have slightly different definitions of quenching. Galaxies are the place where cosmic gas condenses and, if it gets cold and dense enough, turns into stars. The resulting stars are what we really see as traditional optical astronomers.

Not all stars shine the same way though: stars much more massive than our sun are very bright and shine in a blue light as they are very hot. They’re also very short-lived. Lower mass stars take a more leisurely pace and don’t shine as bright (they’re not as hot). This is why star-forming galaxies are blue, and quiescent galaxies (or “quenched” galaxies) are red: once star formation stops, the bluest stars die first and aren’t replaced with new ones, so they leave behind only the longer-lived red stars for us to observe as the galaxy passively evolves.

Example images of galaxies classified by you. There are blue, green and red spirals, and blue, green and red ellipticals.

Example images of galaxies classified by you. There are blue, green and red spirals, and blue, green and red ellipticals.

As @penguin galaxy (aka Alice) put it....

As @penguin galaxy (aka Alice) put it….

Blue Ellipticals & Red Spirals
The received wisdom in galaxy evolution had been that spirals are blue, and ellipticals are red, meaning that spirals form new stars (or rather: convert gas into stars) and ellipticals do not form new stars (they have no gas to convert to stars). Since you’re taking part in Galaxy Zoo, you know that this isn’t entirely true: there are blue (star-forming) ellipticals and red (passive) spirals. It’s those unusual objects that we started Galaxy Zoo for, and in this paper they help us piece together how, why and when galaxies shut down their star formation. You can already conclude from the fact that blue ellipticals and red spirals exist that there is no one-to-one correlation between a galaxy’s morphology and whether or not it’s forming stars.

The colour-mass diagram of galaxies, split by shape. On the right: all galaxies. On the left: just the ellipticals (or early-types) on top and just the spirals (or late-types) on the bottom. On the x-axis is the galaxy mass. On the y-axis is galaxy colour. Bottom is blue (young stars) and top is red (no young stars).

The colour-mass diagram of galaxies, split by shape. On the right: all galaxies. On the left: just the ellipticals (or early-types) on top and just the spirals (or late-types) on the bottom. On the x-axis is the galaxy mass. On the y-axis is galaxy colour. Bottom is blue (young stars) and top is red (no young stars).

Blue, Red and…. Green?
A few years back, astronomers noticed that not all galaxies are either blue and star forming or red and dead. There was a smaller population of galaxies in between those two, which they termed the “green valley” (the origin of the term is rather interesting and we talk about it in this Google+ hangout). So how do these “green” galaxies fit in? The natural conclusion was that these “in between” galaxies are the ones who are in the process of shutting down their star formation. They’re the galaxies which are in the process of quenching. Their star formation rate is dropping, which is why they have fewer and fewer young blue stars. With time, star formation should cease entirely and galaxies would become red and dead.

The Green Valley is a Red Herring
Ok, why is this green valley a red herring you ask? Simple: the green valley galaxies aren’t a single population of similar galaxies, but rather two completely different populations doing completely different things! And what’s the biggest evidence that this is the case? Some of them are “green spirals” and others are “green ellipticals”! (Ok, you probably saw that coming from a mile away).

So, we have both green spirals and green ellipticals. First: how do we know they must be doing very different things? If you look at the colour-mass diagram of only spirals and only ellipticals, we start to get some hints. Most ellipticals are red. A small number are blue, and a small number are green. If the blue ellipticals turn green and then red, they must do so quickly, or there would be far more green ellipticals. There would be a traffic jam in the green valley. So we suspect that quenching – the end of star formation – in ellipticals happens quickly.

In the case of spirals, we see lots of blue ones, quite a few green one and then red ones (Karen Masters has written several important Galaxy Zoo papers about these red spirals). If spirals slowly turn red, you’d expect them to start bunching up in the middle: the green “valley” which is revealed to be no such thing amongst spirals.

We can time how fast a galaxy quenches. On the x-axis is the optical colour, dominated by young-ish stars, while on the y-axis is a UV colour, dominated by the youngest, most short-lived stars.

We can time how fast a galaxy quenches. On the x-axis is the optical colour, dominated by young-ish stars, while on the y-axis is a UV colour, dominated by the youngest, most short-lived stars.

Galaxy Quenching time scales
We can confirm this difference in quenching time scales by looking at the ultraviolet and optical colours of spirals and ellipticals in the green valley. What we see is that spirals start becoming redder in optical colours as their star formation rate goes down, but they are still blue in the ultraviolet. Why? Because they are still forming at least some baby stars and they are extremely bright and so blue that they emit a LOT of ultraviolet light. So even as the overall population of young stars declines, the galaxy is still blue in the UV.

Ellipticals, on the other hand, are much redder in the UV. This is because their star formation rate isn’t dropping slowly over time like the spirals, but rather goes to zero in a very short time. So, as the stellar populations age and become redder, NO new baby stars are added and the UV colour goes red.

It’s all about gas
Galaxies form stars because they have gas. This gas comes in from their cosmological surroundings, cools down into a disk and then turns into stars. Galaxies thus have a cosmological supply and a reservoir of gas (the disk). We also know observationally that gas turns into stars according to a specific recipe, the Schmidt-Kennicutt law. Basically that law says that in any dynamical time (the characteristic time scale of the gas disk), a small fraction (around 2%) of that gas turns into stars. Star formation is a rather inefficient process. With this in mind, we can explain the behaviour of ellipticals and spirals in terms of what happens to their gas.

A cartoon version of our picture of how spiral galaxies shut down their star formation.

A cartoon version of our picture of how spiral galaxies shut down their star formation.

Spirals are like Zombies
Spirals quench their star formation slowly over maybe a billion years or more. This can be explained by simply shutting off the cosmological supply of gas. The spiral is still left with its gas reservoir in the disk to form stars with. As time goes on, more and more of the gas is used up, and the star formation rate drops. Eventually, almost no gas is left and the originally blue spiral bursting with blue young stars has fewer and fewer young stars and so turns green and eventually red. That means spirals are a bit like zombies. Something shuts off their supply of gas. They’re already dead. But they have their gas reservoir, so they keep moving, moving not knowing that they’re already doomed.

A cartoon version of how we think ellipticals shut down their star formation.

A cartoon version of how we think ellipticals shut down their star formation.

Ellipticals life fast, die young
The ellipticals on the other hand quench their star formation really fast. That means it’s not enough to just shut off the gas supply, you also have to remove the gas reservoir in the galaxy. How do you do that? We’re not really sure, but it’s suspicious that most blue ellipticals look like they recently experienced a major galaxy merger. There are also hints that their black holes are feeding, so it’s possible an energetic outburst from their central black holes heated and ejected their gas reservoir in a short episode. But we don’t know for sure…

So that’s the general summary for the paper. Got questions? Ping me on twitter at @kevinschawinski

Happy Valentine’s Day from Galaxy Zoo

Here are our ideas for #sciencevalentines from GalaxyZoo to help you out today. 

First a heart shaped galaxy, as found on Talk



In fact there’s a whole category of galaxy #hearts to check out. 

Or how about saying “I love you” in galaxies with help from






A Galaxy Zoo update for 2014

Exciting news for everyone who has been helping to classify (and discuss) the new images added to Galaxy Zoo just a couple of months ago. Back in October, we added two new sets of images to Galaxy Zoo: infrared images of galaxies from the UKIDSS survey, and optical images of galaxies that were processed to make them artificially redshifted (appear as if they were much further away). The second set is critically important for the data from GZ: Hubble and the CANDELS project; we need this to properly calibrate the classifications for effects like changing resolution and surface brightness as a function of distance.

An example of an artificially-redshifted galaxy from Galaxy Zoo.

An example of an artificially-redshifted galaxy from Galaxy Zoo.

As of last week, we’re excited to announce that the classifications of the artificially redshifted galaxies have been finished! They’ll now be retired from active classification, and we’re excited to start working on the analysis right away to enable the science we want to do on high-redshift galaxies. In the meantime, please keep your classifications coming for both the SDSS and UKIDSS images on Galaxy Zoo. There’s plenty left to do, although we’re getting closer with your help!

Radio Galaxy Zoo: New tools in Talk

For Zooniverse projects, the science teams have always been really impressed by the users who actively participate in Talk and engage in close inspections and discussions. This is especially true for our newest project, Radio Galaxy Zoo, and the number of excellent questions about larger structure for the powerful radio jets has spurred us to add some new tools to the Talk interface.

The new tools we’ve set up (with the invaluable help of Zooniverse developer Ed) show images of the galaxies and their associated radio jets from other surveys. New images include radio observations from the NRAO VLA Sky Survey (NVSS) and optical images from the Sloan Digital Sky Survey (SDSS). We’ve also included direct links to the FIRST (radio) and WISE (infrared) datasets that we use to make the classification images in the first place.

The new tools in RGZ now link to four catalogs (FIRST, NVSS, SDSS, and WISE) for each galaxy. FIRST and NVSS are radio image, SDSS is optical, and WISE is infrared.

The new tools in RGZ now link to four catalogs (FIRST, NVSS, SDSS, and WISE) for each galaxy along the bottom of each image. FIRST and NVSS are radio surveys, SDSS is optical, and WISE is infrared.

Radio images with wider fields of view, such as NVSS, help to identify structures that may extend beyond the boundaries of the standard RGZ image. These include many of the images being labeled as #overedge in Talk. The NVSS images were taken using the same telescope (the Very Large Array in New Mexico) and at the same wavelength at the FIRST radio images. The main difference is the spacing of the telescopes used to take the observation. NVSS images have a much larger beam size, and are better at resolving large and extended structures. FIRST has a smaller beam size and are more sensitive to compact structures with very accurate positions. FIRST is also about 2.5 times more sensitive than NVSS.

By looking at the NVSS images, both RGZ volunteers and scientists have been able to work together and find potentially new examples of giant radio galaxies in these surveys. Larry Rudnick (@DocR) has started a great discussion on Talk, and we’re still identifying more as the project continues.

RGZ image ARG0002gt4, as seen in three of the surveys accessible in the new tools. The wide-field radio NVSS image of the jets is on the left; in the middle is the radio FIRST image, showing the better-resolved galaxy core, and on the right is the infrared WISE image showing the host galaxy.

RGZ image ARG0002gt4, as seen in three of the surveys accessible in the new tools. The wide-field radio NVSS image of the jets is on the left; in the middle is the radio FIRST image, showing the better-resolved galaxy core, and on the right is the infrared WISE image showing the host galaxy. Image from Larry Rudnick (UMN).

We’ve also added links to the infrared and optical catalogs that show the galaxies themselves. The infrared images that we show in RGZ come from the WISE spacecraft, an orbiting infrared telescope that carried out an all-sky survey. The new link shows you infrared images of the galaxy in four different infrared bands (3.4, 4.6, 12, and 22 microns), as opposed to the single 3.4 micron image we normally show. Detecting the galaxy at longer wavelengths might mean that it contains more dust than expected, or show whether a feature in one band might be an artifact (not showing up in any of the other bands). We’ve also linked to the optical image from the SDSS; these dusty and distant galaxies are often too faint to show up there, but an optical detection there makes it much more likely that we already have a spectrum for the object.

WISE infrared images of the galaxy ARG0002h6v. Note how the central galaxy shows up strongly in the two bands on the left (3.4 and 4.6 microns), but is not detected in either of the bands on the right (12 and 20 microns).

WISE infrared images of the galaxy ARG0002h6v. Note how the central galaxy shows up strongly in the two bands on the left (3.4 and 4.6 microns), but is not detected in either of the bands on the right (12 and 20 microns).

Let us know if you have suggestions or questions about the new tools; we hope that they’ll continue to lead to many future discoveries with Radio Galaxy Zoo!

Announcing Galaxy Zoo’s machine-learning competition (with prize money!)

Since Galaxy Zoo began in 2007, our scientific results have relied on the classifications of our volunteers. These have always been checked (in small numbers) against expert classifications, and several papers have explored how the Galaxy Zoo data compares to results from computers. Galaxy Zoo has compared well with both expert and automated classifications, and that’s helped underscore the science that your observations have made possible.

While doing real science with the Zooniverse has always been our primary goal, we’re also looking to the future; upcoming telescopes like the SKA, LSST, and just-launched Gaia will have billions of new images and detected objects. This will simply be too large for citizen scientists to handle the full scope of data – even if literally everyone on the planet is involved.

This is where Galaxy Zoo will come in yet again. Our goal, which is shared by many groups of astronomers, is to improve the accuracy of the galaxy classifications that can be performed by computers. We’ve done some of this already (Banerji et al. 2010, Huertas-Company et al. 2011), but it’s still not good enough for much of the science we want to do. If we can make these algorithms better, future datasets for citizen science can be selected in advance; we can automatically process the bulk of the images, but still have citizen scientists play a key role in classifying at the more unusual objects. Citizen scientist results will also provide important calibration for the algorithms, and will continue to look for weird and wonderful discoveries like the Voorwerp.

With that goal in mind, we’re pleased to announce the launch of a data science competition for Galaxy Zoo. We’ve partnered with Kaggle, an online platform for predictive modeling that has a massive amount of experience in similar projects. Also working with us is Winton Capital: they’ve generously agreed to provide prize money for the winners of this competition. The first prize is $10,000 USD — we hope this will help incentivize some really great solutions!

Here’s how the competition works. On the Kaggle website, competitors will be given a large set of JPG galaxy images (taken from Galaxy Zoo 2), as well as a big text file with a few dozen variables for each image. These data are a modified version of the classifications that citizen scientists generated in GZ2 (and published in Willett et al. 2013). The goal for competitors is to come up with an algorithm that will predict what those classifications should be based only on the picture. These algorithms are submitted to Kaggle and tested against a second, private set of GZ2 images and classifications. The highest scores on the new set will win the prize money.

Galaxy Zoo's machine learning challenge. Hosted by Kaggle and sponsored by Winton Capital.

Galaxy Zoo’s machine learning challenge. Hosted by Kaggle and sponsored by Winton Capital.

We’re really excited about this competition. For Winton, this will help them identify promising candidates who are skilled at predictive analysis that they might be interested in hiring. For Galaxy Zoo, we’ll use the results for two major things: efficient selection of sources for upcoming citizen science projects, AND analyzing the results to see how the algorithms relate to physical properties of galaxies.

The competition is open to anyone in the world, and will run for three months, ending on March 21, 2014. Participants will need significant programming experience, and a math/astronomy background would probably help since the project relies on image analysis and machine learning. If you’re interested, check out the project at

See if you can beat deep space net!

Galaxy Zoo Challenge Leaderboard, as of 22 Dec 2013.

Radio Galaxy Zoo: How were the images made?


Today’s post is from Enno Middelberg, RGZ science team member and astronomer at Ruhr-University Bochum, Germany and expert in interferometry. Enno has kindly agreed to share some details of this complex and highly useful technique for improving the resolution of images.

Radio waves from cosmic objects have been observed since the 1930s, starting with Karl Jansky and Grote Reber. In the beginning, astronomers used single telescopes, some of which looked more or less like TV antennas (and some looked just weird, for example Karl Jansky’s self-made telescope). Whatever the telescope looked like, astronomers understood very well that the resolution of their instruments would never be quite as good as at optical wavelengths. The fundamental reason for this has to do with diffraction theory and Fourier transforms, but the outcome is rather simple: the smallest separation on the sky a telescope can “resolve”, which means, that it can actually tell that there are two things and not one slightly extended thing, is given by the fraction λ/D. Here, λ represents the length of the waves observed (some centimetres in radio astronomy), and D represents the diameter of the telescope (some tens of metres). One can easily calculate that this fraction is of order 0.001-0.004 for a radio telescope, but for an optical telescope the number is much smaller, of order 0.00000005 or so. This means that optical telescopes could separate things on the sky which were much smaller together than the first radio telescopes.

Astronomers had tried to improve on this early on, using something called interferometry. The wavelengths could not be changed (otherwise they wouldn’t be radio telescopes any more, right?), and telescopes could only be made as big as 100m (otherwise they would be too heavy and too expensive). So astronomers took two of the telescopes they had and combined their signals into one. Such a contraption with two telescopes is called an interferometer, and its resolving power is no longer given by the diameter of the dishes, but by their separation. So simply moving the two telescopes further away from one another would increase the resolution – what a fantastic idea! In the 1960s, this technique was much advanced by British astronomer Sir Martin Ryle in Cambridge, and he was awarded the Nobel Prize in Physics for his work in 1974.

In the following decades, Martin Ryle’s innovation was improved upon by astronomers all over the world, creating radio interferometers of various sizes and forms. Radio telescopes sprouted like mushrooms. Ever more powerful telescopes were build: the Very Large Array, theAustralia Telescope Compact Array, the Effelsberg and Greenbank giant single dishes, and many more. Most recently, technical advances have made it possible to build completely digital radio telescopes, such as Lofar. Even though these instruments consist of many more than two radio telescopes, the measurements are always made between any two of them: the Very Large Array, for example, has 27 telescopes, which yields 351 two-telescope inteferometers. Using many more such interferometers improves the image quality and, of course, the sensitivity of the final images.


Radio image with faint emission visible, at the cost of losing details in the bright spots.


Infrared image with radio contours overlayed

Radio images are most commonly reproduced as contour images. This makes them easier to analyse and interpret when printed, and contours are better when very bright and very faint portions of an image have to be shown at the same time. If such information was represented in a grey-scale image, the differences in brightness would not be decipherable. Radio astronomers love contour plots. My wife calls them “fried eggs” and always asks me if the kids can colour them in…

The radio images you’re seeing here are the results of the Australia Telescope Compact Array Large Area Survey (astronomers love acronyms!), or ATLAS for short. Between 2006 and 2009 we have collected data on two small regions in the southern sky to create the basis for an investigation of the way that galaxies evolve. We have used these data to create the radio images you’re seeing when you classify sources. The infrared images were made with the Spitzer telescope, to compare the radio to infrared emission. Radio and infrared waves are not necessarily emitted by the same material and can therefore be displaced from one another in a galaxy. That’s why we need your help to determine what radio blobs belong to which infrared blob!

Radio Galaxy Zoo: a close-up look at one example galaxy

We hope everyone’s been excited about the first few days of Radio Galaxy Zoo; the science and development teams certainly have been. As part of involving you, the volunteers, with the project, I wanted to take the opportunity to examine and discuss just one of the RGZ images in detail. It’s a good way to highlight what we already know about these objects, and the science that your classifications help make possible.

For an example, I’ve chosen the trusty tutorial image, which almost everyone will have seen on their first time using RGZ. We’ll be focusing on the largest components in the center (and skipping over the little one in the bottom left for now).

The tutorial image for Radio Galaxy Zoo

The tutorial image for Radio Galaxy Zoo

The data in this image comes from two separate telescopes. Let’s look at them individually.

The red and white emission in the background is the infrared image; this comes from Spitzer, an orbiting space telescope from NASA launched in 2003 (and still operating today). The data here used its IRAC camera at its shortest wavelength, which is 3.6 micrometers. As you can see, the image is filled with sources; the round, smallest objects are either stars or galaxies not big enough to be resolved by the telescope. Larger sources, where you can see an extended shape, are usually either big galaxies or star/galaxy overlaps that lie very close together in the sky. 

Overlaid on top of that is the data from the radio telescope; this shows up in the faint blue and white colors, as well as the contour lines that encircle the brightest radio components. The telescope used is the Australia Telescope Compact Array (ATCA) in rural New South Wales, Australia. This data was taken as part of the ATLAS survey, which mapped two deep fields of the sky (named ELAIS S1 and CDF-S) in the radio at a wavelength of 20 cm.

So, what do we know about the central sources? From their shape, this looks like what we would call a classic “double lobe” source. There are two radio blobs of similar size, shape, and brightness; almost exactly halfway between them is a bright infrared source. Given its position, it’s a very good candidate as a host galaxy, poised to emit the opposite-facing jets seen in the radio.

This object doesn’t have much of a mention in the published astronomical literature so far. Its formal name in the NASA database is SWIRE4 J003720.35-440735.5 — the name tells us that it was detected as part of the SWIRE survey using Spitzer, and the long string of numbers can be broken up to give us its position on the sky. This is a Southern Hemisphere object, lying in the constellation Phoenix (if anyone’s curious).

The only analysis of this galaxy so far appeared in a paper published by RGZ science team member Enno Middelberg and his collaborators in 2008. They made the first detections of the radio emission from the object, and matched the radio emission to the central infrared source by using an automatic algorithm plus individual verification by the authors. They classified it as a likely AGN based on the shape of the radio lobes, inferring that this meant a jet. It’s also one of the brighter galaxies that they detected in the survey, as you can see below – brighter galaxies are to the right of the arrow. That might mean that it’s a particularly powerful galaxy, but we don’t know that for sure (for reasons I’ll get back to in a bit).

The brightnesses (measured in radio) of galaxies in ATLAS-SWIRE. From Middelberg et al. (2008).

The brightnesses (measured in radio) of galaxies in ATLAS-SWIRE. From Middelberg et al. (2008).

So what we know is somewhat limited – this object has only ever been detected in the radio and near-infrared, and each of those only have two data points. The galaxy is detected at both at 3 and 4 micrometers in the infrared, but the camera didn’t detect it using any of its longer-wavelength channels. This makes it difficult to characterize the emission from the host galaxy; we need more measurements at additional wavelength to determine whether the light we see (in the non radio) is from stars, from dust, or from what we call “non-thermal processes”, driven by black holes and supernovae.

One of the biggest barriers to knowledge, though, is that the galaxy doesn’t currently have a measured distance. Distances are so, so important in astronomy – we spend a massive amount of time trying to accurately figure out how far away things are from the Earth. Knowing the distance tells us what the true brightness of the galaxy is (whether it’s a faint object nearby or a very bright one far away), what the true physical size of the radio jets are, at what age in the Universe it likely formed; a huge amount of science depends critically on this.

Usually distances to galaxies are obtained by taking a spectrum of it with a telescope and then measuring the Doppler shift (redshift) of the lines we detect, caused by the expanding Universe. The obstacle is that spectra are more difficult and more expensive to obtain than images; we can’t do all-sky surveys in the same way we can with just images. This is one reason why these cross-identifications are important; if you can help firmly identify the host galaxy, we can effectively plan future observations on the sources that need it.

Welcome to Radio Galaxy Zoo!

Today’s post is from Ivy Wong, who is delighted to announce our newest Galaxy Zoo project.

Welcome to the extraordinary world of radio astronomy. Observe the Universe through radio goggles and discover the jets that are spewing from the cores of galaxies!

Supermassive black holes lie deep in the cores of many galaxies. And though we cannot directly see these black holes, we do occasionally see the huge jets originating from the cores of some galaxies. However, most of these jets can only be seen in the radio.

Centaurus A in the radio skyThe figure on the left compares the extent of the radio jets from Centaurus A (the nearest radio galaxy to us) to the full moon using the same scale on the sky. Also, the small white dots in this image are not stars but individual background radio sources. The antennas in the foreground are 4 of the 6 antennas that make up the Australia Telescope Compact Array where the radio image was taken.

How do galaxies form these supermassive black holes? And how does having a supermassive black hole affect the evolution of its host galaxy as well as its neighbouring galaxies? Why don’t we see jets in every galaxy with a supermassive black hole? Though much progress has been made in recent years, there are still many open questions such as the above that we can shed light on by amassing a large sample.

To probe the co-evolution of galaxies and their central supermassive black holes, help us map the radio sky by matching the radio jets and filaments to the galaxies (via the infrared images) from whence they came.

Example image with radio jets and infrared galaxies

Can you see the infrared galaxy between the radio jets?

This is a matching & recognition problem that humans are still best at, especially in cases where there are radio jets or multiple sources. And it’s an important task, one that will only become more important as the next generation of radio surveys and instruments come online and start producing enormous amounts of data. So if you’re willing to help, please try out the new Radio Galaxy Zoo and help find some growing black holes — and thank you!

We’re Observing at the Very Large Array!

I’m really excited to be able to post that galaxies selected with the help of Galaxy Zoo classifications are being observed at the VLA (Very Large Array) in New Mexico, possibly right now.


It’s the Very Large Array!

The funny thing about observing at the VLA is that you do all of the work for the actual observations in advance.

The VLA runs in queue mode – as an observer you have to submit very (very) detailed information about what you want the telescope to do during your session (called a “scheduling block”) and a set of constraints about when it’s OK to run that (for example you tell them when the galaxy is actually up in the sky above the telescope!). Then the telescope operators pick from the available pool of scheduling blocks at any time to make best use of the array.

This means after you submit the scheduling blocks you just have to sit and wait until you start getting notifications from VLA that your galaxies have been observed. The observing semester for the B-array configuration started on 4th October (had a pause for the US shutdown) and runs until the 13th January 2014. I’m happy to report that we started getting notifications in late November of the first of our 2 hour scheduling blocks  having been observed. At the time of writing four of our galaxies have each been observed at least once (we need six repeat visits to each one to get the depth of data we’d like) for a total of 16 hours of VLA time. I’ve been getting notifications every couple of days – which means that as I write this the VLA could be observing one of our galaxies!

Since making these very detailed observation files is the observing prodecure at the VLA –  it takes the length of time you’d expect given that…..

So, in September  in-between a crazy travel schedule, and with a lot of help from our collaborator Kelley Hess at Cape Town, I spent a lot of time scheduling VLA observations of some very interesting very gas rich and very strongly barred galaxies we identified in the Galaxy Zoo 2 sample (the bit which overlaps with the ALFALFA survey which measures total HI gas in each galaxy).

We have been granted time to observe up to 7 of these fascinating objects (depending on scheduling constraints at the VLA) which I think may reveal some really interesting physics about how bars drive gas around in the discs of galaxies.

You might notice from the picture (and the name) that the VLA is not a “normal telescope”. It’s what astronomers call a radio interferometer. Signals are collected from 27 separate antennas and combined in a computer. This means that as well as observing sources for flux calibration (so we can link how bright our target is through the telescope with physical units) we also have to observe, roughly every 20 minutes or so a “phase calibrator” to be able to know how to correctly add the signals together from each of the antennae (to add them “in phase”).

So a single scheduling block lasting 2 hours for one of our sources comprises:

1. Information to tell the VLA where to slew initially and what instrumentation to use (how to “tune” it to the frequency we know the HI in the galaxy will emit at).

2. A short observation of a known bright source for flux calibration.

Then there’s a loop of

a. Phase calibration

b. Source observation

c. Phase calibration

d. Source observation

and so on – ending with a Phase calibration (on Kelley’s advice we’ll do 5 source observations, and 6 phase calibrations). We have a total of 6 of these blocks for each galaxy, that makes 12 hours of telescope resulting in about 10 hours of collecting 21cm photons per galaxy.

We have to check which times all these sources are visible to the VLA, and set durations for each part which give enough slew time and on source time wherever the sources are on the sky. And this all has to add up exactly to 2 hours to fit the scheduling block.

The benefit of this though is a telescope which acts like it’s much larger than you could ever physically build. We’re trying to detect emission from atomic hydrogen in these galaxies which emits at 21cm. So we need a really large telescope to get a sharp picture.

And just to end, because they’re lovely, here are the four galaxies the VLA has observed so far in the Sloan Digital Sky Survey visible light images.





Thanks again for your help finding these rare and interesting galaxies. They’re rare, because they’re so gas rich and strongly barred – we have previously posted about how we showed strong bars are rare in galaxies with lots of atomic hydrogen. Hopefully we’ll have some exciting results to share once we’ve analysed these data.

(PS. That takes a lot of time too – it’ll be almost 1TB of data to process in total!).


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