I think the most common question/comment we’ve been seeing for classifiers of the simulated Illustris galaxies is along the lines of: “What’s the blue stuff?”
It’s a great question. Let’s talk about it in more detail.
The short answer is that the blue regions are the simulations’ method of reproducing the light emitted by young stars. A star’s lifetime generally scales as a function of its mass – the more massive the star is when it’s first formed, the hotter it is and the faster it burns fuel. Emission from hotter objects will tend to be bluer (ie, produce more photons at shorter wavelengths) compared to less massive stars. These are trends we see in optical images of stars in galaxies, including naked-eye views and composite color images. The exact color depends on the filters being used as well as processing of the images – that’s the difference between images you may have seen of star-forming regions being pink in some images and blue in others, such as those in Illustris.
A couple more specific questions that we’ve received:
What’s causing the blue colors in the galaxies? Are they caused by individual atomic or molecular lines that we can see in the spectra?
Volunteers who worked on the original GZ green peas project might be familiar with the term “nebular emission” – individual, narrow lines caused by ionized or hot gas surrounding stars, or whether they’re the result of the broadband colors of the stars themselves. The GZ-Illustris images use a stellar population model that only computes the broadband colors, due to some issues with unrealistic green images caused by the interaction of the codes that deal with both the emission lines and effects of dust. The model we’re using – based on work by Bruzual & Charlot (2003) – omits the emission lines for that reason. However, we’ve made extensive comparisons of the two sets of images and find that they agree very well for our scientific goals, including the morphology classifications.
How should visual morphology classifiers deal with the star-forming regions? Ignore them and look at the underlying stellar populations? Treat them as part of the galaxy? Something else?
This is a tough one. Many galaxies have the “blobby” star-forming regions but others have nicer looking disk or spiral distributions. Our analysis suggests is that this is a pretty tight function of the total star formation rate (higher SFR = more realistic looking features). We suggest that users treat them as part of the galaxy; it might lead to some odd results in lower mass galaxies, but we expect they should trace each other very well for the more massive galaxies. If you see geometry that’s distinctly different from a well-formed spiral disk or elliptical, don’t be hesitant to click the “Anything Odd” or “Other” buttons – that’s one of the simplest ways in which we can measure the unusual effects of the blue regions, given the constraints of our classification scheme.
The distribution of the blue blobs is often disconnected and/or in unusual shapes compared to Sloan. What determines the spatial distribution of the star forming regions?
This results from the extremely discrete sampling of the density of stars in the images. Stars can only form in “chunks” of about 1 million solar masses, instead of the more typical small clusters and regions that we know exist in the real Universe. Moreover, these chunks have their light spread over a significant fraction of ~1 kpc (which is pretty big, compared to a typical galaxy radius of ~20 kpc), and so they often won’t look much like real star-forming regions. This, coupled with the lack of dust, leads to what you see in the GZ images.
Thanks as always to everyone for your help. Please post here or on Talk if you have more questions!
This post was written with the help of researchers Gregory Snyder (Space Telescope Science Institute) and Paul Torrey (MIT/Caltech), who worked extensively on the development of Illustris and the generation of the mock images for Galaxy Zoo.
This post was written with the help of Sugata Kaviraj, senior lecturer at the University of Hertfordshire in the UK. Sugata has been a member of the GZ science team for several years and is leading our analysis of tidal debris in the DECaLS images.
One of the biggest changes to the questions we’re asking for the new DECaLS images asks users to help us classify galaxies that are either merging and/or exhibiting “tidal debris”. While mergers have been part of Galaxy Zoo since our very first classifications, tidal debris is looking for something more specific, which the new DECaLS data is particularly suited for.
In astronomy, “tides” are a type of force exerted on an object by the effect of gravity. Specifically, it refers to the gravitational force exerted by one body on another – since the force exerted by gravity depends on the distance to the object (specifically, it’s proportional to the inverse square of the distance), the nearer side of the object will feel a stronger force than the farther side of the object. On Earth, the differential force caused (mostly) by the gravity of our Moon acts on the liquid in the oceans, causing the rise and fall in sea levels each day.
When the object is a solid body (like a planet or moon), tidal forces can strain and compress the body, resulting in internal heat and sometimes driving geological activity. A galaxy isn’t a solid body, but composed of individual stars/gas clouds/dark matter particles bound within its own gravitational field. When a galaxy is subjected to tidal forces, it pulls the galaxy apart, causing irregularities in shape that can take many forms depending on the magnitude and direction of the forces involved.
One of the main reasons we want to identify tidal features specifically is to make better measurements of the merger history of galaxies. A complication is that the event of merging with a galaxy isn’t an instantaneous event – depending on the relative masses, velocities, and orientations of the merging galaxies, tidal forces strip out long tails of stars and gas from the galactic centers.
The Mice (NGC 4676): colliding galaxies with tails of stars and gas distorted by tidal forces. Source: Hubblesite.org
Ultimately, the nuclei of the two galaxies will fully merge; if that happened sufficiently far in the past for the orbits of stars to relax, then it’s difficult for observers to determine if an elliptical galaxy today was the result of a merger.
Tidal debris features, however, are longer-lived signals of a merger sometime in a galaxy’s past. If we only asked about mergers, we’d be restricting the sample to galaxies that we’re lucky enough to observe “right in the act” of merging. By identifying the tidal debris as well, we can make a more complete census of galaxies that had a merger at some point in their past. One project that this is critical for is looking at the history of galaxy populations, and trying to figure out whether star formation and/or active black holes might be powered by merger events.
Since tidal debris features can be very faint (ie, having low surface brightnesses), the deeper DECaLS images that we’re currently classifying are much better at picking out these features than SDSS. That’s the main reason we’re focusing on trying to detect them in the current set of images.
Tidal debris can come in many different forms, including extended light, faint shells, dust lanes, or satellites in the process of being assimilated to clearly distorted galaxies which have presumably have had a recent interaction. The features can definitely be faint, but we’d like to ask that when you reach this question, please take a careful second look at the area around the main galaxy and see if you can spot anything. Examples are also available in the help text, and we hope that you’ll discuss features you’re not certain about with the moderators, scientists, and other volunteers in Talk.
Please let us know, here or on Talk, what questions you have. Thanks for your help in tackling a new and interesting scientific problem.
Final day of the conference. Still pro-pasta, but may have hit my personal limit on gelato and/or red wine.
We had only a half day for the final day of the Bologna workshop on extragalactic radio surveys. After a tasty conference dinner at the historic Palazzo Re Enzo, we devoted the morning to AGN physics. This is the counterpart to the sessions we had on star formation in galaxies on Monday; almost all continuum radio emission that we detect in individual galaxies is either due to a thermal component from star formation or synchrotron and free-free emission that’s produced in some way by the central supermassive black hole, known as an active galactic nucleus (AGN).
Leith Godfrey (ASTRON) gave a really neat talk on “remnant” radio galaxies, which refers to galaxies that still have active radio emission from the heated plasma in distant lobes, but for which we don’t see the jet because the black has shut down its active phase some time ago (in our observed frame). We can identify these remnants both via morphology (big radio lobes with no jet or core) and through their radio spectra – energy losses from the particles cause a characteristic curved shape which you see if you plot frequency vs. radio flux density. Leith has been doing statistical studies of remnants, finding that less than 1% of bright radio sources are in a dying phase. This is interesting since the number of sources we observe constrains the timescales on which radio galaxies die. It also points toward certain physical properties – there are strong adiabatic losses after the jet switches off, but the lobes seem to remain very high-pressured compared to their environments right up until the end of their lives.
Marisa Brienza (ASTRON) gave the talk immediately following on a new remnant, named BLOB1, that she and her team just detected with LOFAR. LOFAR, a low-frequency array located in the Netherlands and other European countries, is just ramping up full operations, but will be a hugely powerful instrument for increasing the size of these samples over the next decade.
After several more talks, Mike Garrett (ASTRON/Leiden) gave some closing remarks on the conference, including some summaries of what had been discussed and where he thought the future of extragalactic radio sources was going. I was really stoked that RGZ was one of the first results that he specifically cited as being important; Mike mentioned both citizen science and new distributed software routines as being crucial for dealing with the potentially billions of new celestial sources that telescopes will detect in the next decade. The role of citizen scientists in radio astronomy may change – I’ve talked to scientists at this conference about someday doing tasks other than morphology identification, for example – and we’ll definitely have to increase the interplay between the citizen science datasets and machine learning algorithms to maximize our survey results. But, as Mike said on his final slide, the present state of radio surveys is very bright indeed, and we have every reason to think that the best is yet to come.
It’s been a fantastic workshop, and I’m grateful to the conference organizers for accepting my talk and offering financial assistance, the American Astronomical Society for covering my travel costs, and the NSF for partially supporting my work on RGZ at the University of Minnesota. Looking forward to a day or so of sightseeing this weekend, but I’m inspired to get back to work next week and continue being part of such a vibrant scientific community.
75% done with the conference. Still not sick of pasta yet.
Day 3 of the Bologna workshop on extragalactic radio surveys started with a session on the most massive structures in the Universe: galaxy clusters. These collections of galaxies within massive dark matter haloes show up in radio surveys in several different ways: these include radio haloes, which are diffuse large-scale emission regions not associated with a particular galaxy; radio relics, which are similar features but found at the edge of clusters and likely driven by shock waves, and individual radio galaxies found within and nearby these clusters. Reinout van Weeren (Harvard/CfA) gave a really interesting talk on measuring the spectral index in radio relics; this means measurements of the ratio of the radio luminosity at different frequencies, similar to the way color is defined at optical wavelengths. Changes in the radio spectral index trace variations in turbulence in the intracluster medium, or possibly changes in magnetic fields; the fact that radio relics in many clusters have very different spectral index maps is a puzzle that makes it difficult to explain them with a single model.
We also had the second poster session of the conference, including another Radio Galaxy Zoo result! The poster was led by RGZ science team member Minnie Mao (Joint Institute for VLBI in Europe), titled “Here Be Spiral DRAGNs”. Jean Tate, Minnie Mao, and several RGZ volunteers and science team members have been using RGZ to search for radio-loud AGN whose host galaxy is a spiral.* The acronym “DRAGN” stands for “double-lobed radio source associated with galactic nuclei”. These are extremely rare objects – the number of confirmed spiral DRAGNs discovered so far can be counted on your fingers – but really interesting. The standard physical model for how double-lobed, powerful radio sources are generated are triggered by mergers between galaxies and ultimately their black holes. In the process, a major merger disrupts and destroys the disk of the galaxy, resulting in an elliptical – this theory would predict that we see double radio AGN exclusively in massive ellipticals. That’s mostly true, but the existence of exceptions are fascinating and force astronomers to consider alternatives or extensions to the merger driven hypothesis. Minnie and Jean are going through a sample preliminarily assembled in RGZ to try and identify more candidates like these.
One more day to go!
*Changed wording on 24 October 2015 to emphasize the roles played by both volunteers and the science team.
Yesterday was the second day of the workshop in Bologna on extragalactic radio surveys, where I’m attending and gave a talk on Radio Galaxy Zoo. We had three major blocks of talks yesterday: one on galaxy evolution, one on cosmology, and the final one on exploiting synergies between radio telescopes.
Galaxy evolution is a big topic, and one that drives a lot of the science behind both Galaxy Zoo and Radio Galaxy Zoo. Several of the talks really highlighted the importance of having multiwavelength data, in addition to what we learn from the radio (this is one of our main goals identifying the optical counterpart in our project). A couple of the most famous deep fields which have been studied in radio were discussed, including the VLA-COSMOS study, GOODS-North, and the Hubble Deep Field.
Data from new telescopes, like the low-frequency LOFAR, are yielding some exciting results. One interesting result was the fact that lower-mass galaxies more commonly hosted active galactic nuclei (AGN) seen in the radio in the early Universe, at redshifts of 1 < z < 2. Galaxies with higher masses, however, had about the same fraction of radio-loud AGN at this time. It’s interpreted as being the result of more galaxies accreting matter in what’s known as “cold” or “radiative mode”, thanks to the increase in the supply of cold gas available to galaxies at earlier times (Wendy Williams, U. Hertfordshire).
Cosmology is probably being a bit underrepresented at this conference, since we only had three talks in this session. A lot of the focus was on how detecting very large samples of galaxies (both in radio continuum, like the FIRST and ATLAS surveys in RGZ data, as well as looking at spectral lines like the 21-cm hydrogen line) constrain our cosmological models. Different parameters for both dark energy and dark matter make specific predictions for how populations of galaxies evolve, including their numbers, distributions of sizes and masses, and geometrical arrangement. You can also test cosmology through gravitational lensing at radio wavelengths. It’s promising, but very challenging compared to how it’s done in optical wavelengths due to difficulties in fitting shapes in the raw visibility data (Prina Patel, U. Western Cape).
One of the talks I found really interesting (and new to me) was by Emma Storm, from GRAPPA/U. Amsterdam. She gave a great presentation on how radio observations explore the nature of dark matter. While we don’t know a huge amount about the nature of the dark matter particle, one prominent theory predicts that when they collide, the particles annihilate and produce other particles in the Standard Model that we can directly observe (like pions and gamma rays). If that’s so, then these annihilations would also produce charged particles like electrons and positrons; when those particles are accelerated in magnetic fields, they emit synchrotron radiation, which we detect in the radio. So by looking for radio emission in objects that we expect to be dominated by dark matter (like galaxy clusters), scientists can constrain the parameters of their dark matter models, particularly things like the cross-section. The signal this would produce is expected to be diffuse and weak, though; Emma’s work doesn’t detect radio emission in many clusters, but places important upper limits on the amount that could be there within the detection limits.
The last session of the day dealt with synergy and commensality. I normally hate things that sound like business-speak buzzwords, but in this case it is really important – we have a number of new radio telescopes coming online now or in the next several years, such as ALMA in Chile, LOFAR in Europe, and the Square Kilometer Array in Australia and South Africa. It’s quite important to plan the capabilities and designs of each so that we don’t repeat work unnecessarily, maximize the scientific output, and try to make the data and results available to as many people as possible.
Halfway over already! You can also follow what some of the other people have been discussing at the conference at the hashtag #radsurveys15.
One of the best things about being a scientist is the opportunity to attend conferences – you get to visit a new place, meet your colleagues in person, learn about what they’ve been doing, and get a chance to share your exciting research with them. I’m lucky (through the assistance of the American Astronomical Society, the Italian National Institute for Astrophysics, and the University of Minnesota) to participate in a conference this week on the future of extragalactic radio surveys in Bologna, Italy. I’m getting my first chance to share results from Radio Galaxy Zoo and to learn about other, new results in the area of extragalactic radio science!
The conference is four days, from Tuesday – Friday; I’m going to try to make a blog post each day. I’m going to try give a quick overview of all talks/posters on the day, as well as more details on talks which I thought were particularly interesting. I know I won’t do justice to many of the interesting research topics being presented, but I won’t have time to give every topic the breadth they deserve.
The first day of the workshop started with several talks covering current and upcoming surveys in radio astronomy. These include radio telescopes in the Northern Hemisphere. The two main telescopes discussed were the Very Large Array (VLA) in New Mexico, USA, which will run surveys like VLITE (a low frequency survey which will run constantly on the telescope in parallel with other observations), and VLASS, a new all-sky survey with many similarities to the current FIRST data in Radio Galaxy Zoo. LOFAR is a low-wavelength radio telescope with stations centered around Europe; it will open up similar resources, but at significantly lower frequencies than the VLA and thus probing different physical phenomena. In the Southern Hemisphere, the EMU survey in Australia and the MIGHTEE survey in South Africa will carry out similar responsibilities.
I gave a talk at the end of this session on Radio Galaxy Zoo, covering our first accepted paper and some of our early science results. If you’re interested, I’ve put my talk online here.
The afternoon had two sessions on science: one on radio continuum and star formation, and one on radio observations of the transient universe.
I think after the first day that I’m filled with a great sense of optimism about radio astronomy. We’ve got a fantastic new telescope being built in the next several years: the Square Kilometer Array. It’ll be the largest telescope ever built, addressing a huge number of scientific questions. We’re currently in the stage of building prototype telescopes, but those telescopes are already producing useful science – some of which I learned of today. We have a reasonable understanding about how things like magnetic fields affect both the formation and evolution of galaxies. Radio observations have a unique way of detecting and leveraging these detections; through polarization of the radio signal, we can measure the magnetic field and directly probe (through its signal) the interactions with matter between its source and our telescopes. New phenomena like fast radio bursts are, I think, a really neat way of measuring both the amount and distribution of matter in the Universe – this has implications for everything from star formation to cosmology.
Really excited for the rest of the week (including more Radio Galaxy Zoo results) – will post again tomorrow!
This is a guest post by Freya Pentz, who has spent much of this summer doing research with Galaxy Zoo.
Hi Galaxy Zoo volunteers!
I’m a summer student at the Zooniverse. I’m at university studying natural sciences about to go into my second year and for the past 5 weeks I’ve been working at the Zooniverse office here in Oxford. I wanted to let you know what I’ve been doing during that time.
I’ve been using data from the Galaxy Zoo: Bar Lengths project, writing code to process the information and making sure it looks sensible. Before I started working at the Zooniverse, I had done very little computing so I had to learn a lot! For those of you who are interested, I’ve been using python to extract the measurements you did on the galaxies and plotting graphs with all the data. Learning how to use python was like learning another language but it was definitely worth it.
The first thing I did was to find out how many of the galaxies that you’ve classified have bars. That meant looking at the answers to the first question about the galaxy in the Bar Lengths project ‘Does this galaxy have a bar’ and seeing for each galaxy if most people answered ‘Yes’ or if most people answered ‘No’.
Luckily, the code could do that for me; otherwise I would have had to look at over 66000 answers! So far, 4960 galaxies have been classified out of a total of 8612 in the project. Your classifications show that 700 of these have a bar, meaning that the fraction of classified galaxies with a bar is around 14%. This is similar to the 10% bar fraction referred to in the study recently done by the Galaxy Zoo and CANDELS teams on bar fractions out to z=2 (blog post & paper). This number will probably change a little bit as more galaxies get classified, but it’s good that it is similar to known values so far.
The next thing was of course to find the lengths and widths of the bars. When you draw lines on the galaxy to mark the length and width, the database records this as coordinates. Each line has four coordinates, 2 x coordinates and 2 y coordinates. Once you have the coordinates, it’s fairly simple to turn them into lengths. All you need is some Pythagoras. When plotting a histogram of the lengths, the shape was a Gaussian distribution, or a bell curve. This shows that most of the galaxies have lengths between certain limits (5-15 kpc) and then as you go beyond these limits, the number of galaxies decreases.
During my time here, I found some interesting galaxies. When I first looked at the redshifts, there was a galaxy with a redshift of 4.25. I mentioned this to a couple of people on the Zooniverse team and they all said there wouldn’t be a galaxy with such a high redshift in the sample. I checked it out and this is the galaxy in question:
You can see that there is a bright blue smudge in the top left of the galaxy. When I first saw this, I thought it was a lens. It looks like one, and you can just see a small bit of blue on the other side of the galaxy’s core, suggesting a lens even more. According to the experts in the Zooniverse however, this is probably not a lens, as the galaxy does not look massive enough to lens light. Also, the blue curve is well inside the galaxy, instead of being around the outside. Usually, all the mass of the galaxy is needed to lens an object so the light would appear around the edge. The blue curve is most likely an unusual feature of the galaxy itself, which can explain why the reported redshift is so high. The redshift for this galaxy was measured photometrically. This is where astronomers use galaxy colours across a wide range of wavelengths to predict the likely redshift. This method of measuring redshift is much more prone to error than spectrometry (where the absorption lines for certain elements in a galaxy are observed and the shift of these lines is measured) so the blue smudge could have easily made the telescope think the redshift was higher than it is. This redshift is therefore almost definitely a mistake. We also know this from the high resolution of the image. You normally wouldn’t be able to see a galaxy with even a redshift of 1 this well!
The reason telescopes have to use photometric redshifts sometimes even though they are often wrong is that there is not enough time to take a spectrum of every galaxy when you are conducting a large survey of the sky. Telescope time is expensive and photometric measurements allow you to get a bit of information about lots of galaxies which can sometimes be more useful that getting a lot of information about a few.
When running into problems like this it was really useful to be able to look at a picture of the galaxy on the Galaxy Zoo: Bar Lengths website. Looking at the galaxies and seeing in real life what the data on the graphs was telling me was probably my favourite part of my time at the Zooniverse. It’s so amazing that thanks to the Sloan Digital Sky Survey, the Hubble Space Telescope projects and other mass surveys of the universe, we can actually look at pictures of thousands of galaxies easily.
The Zooniverse is such a cool organisation and I’m lucky to have worked for them this summer. The great thing about them is that you can get involved too! I know from my work with Bar Lengths that even if a few people log on and classify in any of the projects, it can be really helpful. None of the science can be done without you providing the data.
Measure some galaxies here:
Or have a look at some of the other projects here:
We’re extremely excited to announce the launch of two new image sets today on Galaxy Zoo. Working with some new scientific collaborators over the past few months, we’ve been able to access data from two new sources. This blogpost will go into more details on where the images come from, what you might expect to see, and what scientific questions your classifications will help us answer. (See Part 1 of this post to learn about the other new images from the DECaLS survey).
The second set of new data comes from the Illustris Project. Illustris is a state-of-the-art simulation of the Universe, led by a large team of researchers in the US, UK, and Germany. Large-scale cosmological simulations are a critical tool in astronomy; since we don’t have laboratories where we can replicate the conditions of processes like galaxy formation, we use computer simulations to investigate them instead. Such simulations start with what we believe conditions in the very early Universe were like (which we infer from the cosmic microwave background), and can include both dark matter and baryons (particles like protons and neutrons that eventually form the stars, dust and gas in galaxies). The simulation then tracks what happens to the matter and energy over billions of years as the Universe expands, evolving according to the laws of physics that are programmed into the simulation. This includes relations like the law of gravity, which dominates how dark matter moves, and hydrodynamics, which describe the motions of the gas. It’s truly amazing – scientists can watch galaxies form and evolve over huge scales of distance and time, and compare the results to real observations to test if the physics of the simulations are correct. Illustris is one of the largest and most detailed simulations ever run, taking more than 19 million CPU hours to run on powerful supercomputers.
This comparison to real data is the key feature that sparked the collaboration between Illustris and Galaxy Zoo. Once the simulation is run, astronomers analyze the results to see if their galaxies match the properties of those seen in the real Universe. This includes measurements like the total number of stars formed, the ratio of stars to dark matter, and the distribution of galaxies of different masses and luminosities. Another critical parameter we want to compare is galaxy morphology; measuring the ratio of ellipticals to spirals, for example, is an important test of whether the galaxy merger rate is correct, and if the simulation codes for star formation and gravitational interaction are correct.
The Illustris scientists have created images of the galaxies from their simulation that GZ volunteers will classify by their morphology. Our comparison data set for this will be the SDSS results from Galaxy Zoo 2, and the images are designed to match the Sloan images as closely as possible. This includes the same set of filters for the telescope, sizing the images so that the galaxies look like they’re at cosmic distance from the Milky Way, and setting them against backgrounds of stars and other galaxies. The quality of the simulations and images are amazing – these look to me like real galaxies in every way. It’s something that astronomers definitely couldn’t do ten years ago.
Although these images aren’t of “real” galaxies, we want to emphasize again how much your classifications will help scientists to do astronomical research. Simulations like Illustris are the only way that we can probe galaxy formation and evolution as it happens. Your classifications, both from Galaxy Zoo 2 and from the new Illustris data, provide vital tests for the output and will be fed back to the science teams in order to improve future versions of these sims.
If you have questions or want to discuss anything you see in the new images, please join the discussion with scientists and volunteers on Talk. The Illustris Project also has some amazing online tools if you want to learn more, including an interactive explorer of the simulation and videos of the evolving Universe. You also can explore specific galaxies you’ve classified via GZ:Examine. As always, thanks to everyone for your help!
We’re extremely excited to announce the launch of two new image sets today on Galaxy Zoo. Working with some new scientific collaborators over the past few months, we’ve been able to access data from two new sources. This blogpost will go into more details on where the images come from, what you might expect to see, and what scientific questions your classifications will help us answer. Part 2 of this post will discuss the other set of new images from the Illustris simulation.
The Dark Energy Camera Legacy Survey (DECaLS) is a public optical imaging project that follows up on the enormous, groundbreaking work done by the various versions of the SDSS surveys over the past decade. The aim of DECaLS is to use larger telescopes to get deeper images with significantly better data quality than SDSS, although over a somewhat smaller area. The science goals include studies of how both baryons (stars, gas, dust) and dark matter are distributed in galaxies, and particularly in measuring how those ratios change as a galaxy evolves. By adding morphology from Galaxy Zoo, our joint science teams will explore topics including disk structure in lower mass galaxies, better constraints on the rate at which galaxies merge, and gather more data on how the morphology relates to galaxy color and environment.
DECaLS observations use the Blanco telescope, which is located at CTIO in northern Chile at an altitude of 2200m (7200 ft). The telescope has a 4-m aperture mirror, giving it more than three times the collecting area of the SDSS telescope. The camera used for the survey is named DECam, a large-area and extremely sensitive instrument developed for a separate program called the Dark Energy Survey. The camera has 570 megapixels and covers a 2.2 degree field of view – more than 20 times the apparent size of the full moon! The combination of the exquisite dark-sky observing site, a sensitive wide-field camera, and larger telescope all combine to generate the new images, which will eventually include more than 140 million unique sources on the sky when DECaLS is finished.
The DECaLS images in Galaxy Zoo are a smaller group taken from a catalog called the NASA-Sloan Atlas. We’re focusing on somewhat larger and brighter galaxies from the catalog. The reason is that although many of these galaxies have been classified in GZ already via their Sloan images, we’re particularly interested in measuring details like tidal tails from mergers, seeing fainter spiral structures, and separating galaxies that couldn’t be individually resolved in the Sloan data. Here’s a great example of a single galaxy in both SDSS and DECaLS – check out how much clearer the spiral arms are in the new images!
Almost all of the morphology and classification tasks are the same as they were for the Sloan images, so it should be familiar to most of our users. If you have questions or want to discuss anything you see in the new images, please join the discussion with scientists and volunteers on Talk. As always, thanks for your help!
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.