How Do We Measure Galaxy Morphology?

We've discussed in a previous post how much of what we know about galaxies comes from studying their morphology (in other words, what they look like). This gives us a sense of what a galaxy's internal structure is and, at least in the local universe, galaxy morphology correlates with various other galaxy properties, such as color, star formation rate, and environment. Data from the Hubble Space Telescope is ideal for galaxy morphology studies, especially at high redshift, due to its exquisite high resolution and HST's location above the Earth's blurring atmosphere. With HST data, we are able to see detailed structure in distant galaxies that would be very difficult or impossible from the ground. So how do we actually go about measuring a galaxy's morphology?

A sampling of galaxies with various morphological types and colors.
Credit: Zsolt Frei, Institute of Physics, Eötvös University, Budapest

One of the typically used methods for studying galaxy morphology is to visually look at individual galaxies and classify them into a previously established system. This is what Edwin Hubble did when he first put forth the Hubble sequence. Hubble's classification scheme is what most modern schemes are based on (dividing galaxies roughly into spirals, ellipticals, and irregulars) but there are many other structural features one may wish to include, such as whether or not a bar or tidal features are present. Once a system has been decided upon, the next step is doing the work and looking at a lot of galaxies! Visually classifying galaxies can be very time consuming and can possibly be biased by several different factors (Are you more likely than others to identify certain features? Were you tired when looking at the last set of objects?). However, the human eye is particularly adept at this type of pattern recognition and is unmatched when it comes to identifying faint features in galaxies.

Since classifying galaxies takes a long time, it can be difficult to build up large samples of objects with classifications. It was this problem that lead a group of astronomers to create the Galaxy Zoo project. These astronomers involved the general public in galaxy classifications. These citizen scientists (including hundreds of thousands of volunteers) classified galaxies in the nearby Universe from the Sloan Digital Sky Survey (originally; today Galaxy Zoo includes images from Hubble data as well) via the Galaxy Zoo website. Over time, these classifications have built up to an incredible database of classifications and have lead to public data releases and a number of publications.

Despite the benefits of visual classifications, astronomers have searched for ways to automate galaxy morphology methods so that thousands to millions of objects can be investigated without the need to look at each one individually. Plus, a computer program that can classify galaxies would be able to do the exact same thing for each object, without bias. Several methods have been developed by different groups and they each have their own advantages and disadvantages.

One common method is to use a computer program to quantify how a galaxy's light distribution changes from the center of a galaxy to its edge. Is it very concentrated in the center like an elliptical galaxy or is it extended like a disk galaxy? Perhaps it's somewhere in between? This method is very successful at separating galaxies into spiral and elliptical categories. Another common technique is to quantify how asymmetric a galaxy is. This is done by rotating an image of a galaxy by 180 degrees and subtracting it from the original. Whatever is left tells you how asymmetric it is (if it was perfectly symmetric, like a circle, no signal would remain after subtracting). This method is commonly used to identify galaxy mergers since they are typically messy irregular systems. Another method, which was used in the paper presented in this previous post, combines two different parameters, one called 'Gini' - which is a measure of a galaxy's light distribution, and the other called 'M20' - the second order moment of a galaxy's brightest pixels. By combining these two, galaxies can be split into bulge dominated and disk dominated objects. This method has also been used to identify galaxy mergers.

By combining some of these structural measures with visual classifications, we can calibrate each method (what are the parameters of galaxies with known types?) and study how well each works as a function of a galaxy's brightness and its distance from us. The more distant a galaxy is, the fainter its features are, and the more difficult its morphology can be to measure. In future posts, we will discuss some CANDELS science results using all of these different methods and applying them to galaxies in the distant universe.

Did CANDELS find the first stars in the Universe?

Did that title grab your attention? Spoiler alert: the answer is no (probably), but the journey to that answer was interesting! Read on!

In today's blog post, I'm reporting on a paper I wrote with the help of many other members of the CANDELS team which has just been published in the Astrophysical Journal. The title of the paper is "The Evolution of Galaxy Rest-Frame Ultraviolet Colors from z = 8 to 4" (and you can find it here). There's a lot in the title, so let's break it down: the word "evolution" at the beginning means that we're studying how galaxies change (i.e. evolve) with time. In this particular paper, we're focusing on a time period in the early universe, from around 0.5 to 1.5 billion years after the Big Bang. The universe is now 13.8 billion years old, so this is early on indeed, but as I'll show, things change quickly even in this short time period. The "from z = 8 to 4" denotes this time period; astronomers use a term called "redshift" to denote distance (see these earlier blog posts, #1 and #2, for more details), so a redshift (or "z") of 4 corresponds to 1.5 billion years after the Big Bang, and a redshift of 8 is about 0.5 billion years (or 500 million years) after the Big Bang.

The meat of the title is in the middle: "rest-frame ultraviolet colors"; this means we are looking at the colors in the ultraviolet, which is just bluer than the eye can see. However, due to the expansion of the universe, at these high redshifts this ultraviolet light is shifted to the near-infrared. Thus, we add the qualifier "rest-frame". What this means is that even though the light we observe is in the near-infrared, we have a good idea of the redshift of a given galaxy, so we can figure out what the intrinsic ultraviolet (or UV) color is (you may have seen this referred to as "k-correcting", which is a similar concept).

So, why is this interesting? The UV light tells us a lot about ongoing star-formation. This is because the UV light from galaxies is dominated by massive stars (many times more massive than the Sun). Massive stars are very hot, so they are very bright in the ultraviolet, and they look blue (by comparison, the Sun appears yellowish, and lower mass stars look red). But, massive stars are very short-lived, some exploding as supernovae after only 10 million years. So, if you look at a galaxy and it is bright in the UV and also blue in color, you immediately know that massive stars are still around, so it must be actively forming a lot of stars!  Cool, right?

The story doesn't end here. A number of studies predict that when we look at galaxies very early on, they should appear even bluer than galaxies observed at later times. This is because in the Big Bang the only elements to form were hydrogen and helium (with trace amounts of lithium). If you make a star with just those elements, it will be very hot; this is because gas needs to cool to very low temperatures to condense and form "normal" stars like those we see in today's universe. However, to cool down, gas typically relies on atoms heavier than helium (which we astronomers call "metals") to radiate away energy. If you don't have those elements, then stars do form, but we think that they end up being much more massive (maybe even more than 100 times the mass of the Sun); these massive stars are extremely hot, so they are very blue, much bluer than any star with a normal allotment of metals.

Figure 1: The ultraviolet colors of galaxies at different redshifts (the top vertical axis shows the amount of time in billions of years since a redshift of 20; add 0.2 to change it to since the Big Bang). The red circles show the average of all galaxies, while the blue circle shows the average colors of faint galaxies at a redshift of 7.

So, we were motivated to look through the CANDELS data for distant galaxies, and measure their colors to see how blue they looked. Sounds simple, right?  I'll skip over a lot of the details (though you can learn how we found the galaxies here), but our main results are shown in Figure 1. This plot shows the colors of galaxies at each redshift we study.  The red points show the average colors of all galaxies, but we'll focus on the blue point first, since it represents the average color of faint galaxies only (which tend to be bluer). The gray line and arrow shows the color we would expect if these galaxies had stars with very little metals; if our galaxies had very little metals, we would expect them to be below this line. What we see is that even when we look at the faintest galaxies, while they do look very blue, they are not so blue that we think they host stars with very low metallicities. In fact, taking into account the error bar on this point, these galaxies have colors consistent with the local galaxy NGC 1705 (shown as the cyan bar); while NGC 1705 is blue, it has been studied very intensely, and it doesn't have any metal-free stars.

What this tells us is that even though we're looking less than one billion years after the Big Bang, galaxies have already been enriched by metals a significant amount. This means that star-formation must have already been occurring for a while, so that when we have the capability to look to yet higher redshifts (which we will later this decade with the James Webb Space Telescope), there should be plenty of galaxies burning bright for us to see!

There is one last point to make, this time looking at the red points, which are the average colors of all galaxies at a given redshift.  We see that they start out fairly blue at z=7, and get progressively redder. We think that this is due to the increased presence of cosmic dust grains (composite particles made up primarily of carbon and silicon) in these galaxies. Dust has the funny effect of making the colors of a galaxy look redder, since they absorb and scatter blue light more efficiently than red light, hence the phrase "dust reddening". What we're witnessing here is the build-up of vast reservoirs of dust in these galaxies, in only one billion years of cosmic time! Although dust may sound boring, it has a dramatic effect on the colors of galaxies, as you can see. Also, all of this UV light absorbed by the dust has to go somewhere, and its energy actually gets re-emitted in the far-infrared (much redder than your eye can see). In fact, when we look at galaxies closer to home, many of them are brighter in the far-infrared than in the UV, implying that much of their UV light has been absorbed by dust. What our results here tell us is that while this is likely not an issue at a redshift of 7, it becomes progressively stronger as you move to lower redshift. So, if you want to study galaxies at high redshift, much like the Alamo you must "remember the dust!"

How I Ended up Studying Distant Galaxies

As Janine Pforr mentioned, we've decided that from time to time we will be using blog posts to introduce ourselves and say something about how we got into astronomy. I'm writing this post on a long flight back from Arizona to Baltimore, so apologies in advance if I ramble a bit.

I am Henry C. Ferguson, known to my colleagues as Harry. I am co-Principal investigator of CANDELS along with Sandy Faber. I am an astronomer at the Space Telescope Science Institute (STScI), in Baltimore Maryland. STScI is the science operations center for the Hubble telescope, and will be operating the James Webb Space Telescope (JWST) when it launches in 2018. All the scientists at the institute divide their time between their own research and providing support for the observatories. My research interests broadly center around galaxies and cosmology, and I've been spending most of my time over the past couple decades on surveys of the distant universe.  For my support work, I have most recently been running the Webb Instrument Team as we try to work out the details of how to operate and calibrate the cameras and spectrographs on the new telescope. I've done similar work in the past for Hubble. In my spare time, I enjoy playing Irish traditional music on hammered dulcimer and accordion, most recently as a member of the Tanzania Ceili band.

I've been interested in astronomy since my early teens. I went to high school at St. Paul's, a boarding school in Concord, New Hampshire. The school had a small observatory, and a remarkable science teacher, Walter Hawley. There were no formal astronomy classes, but there was an astronomy club. Skies were reasonably dark, and a friend and I spent many nights observing and sketching the Messier objects. Walter Hawley arranged trips for the astronomy club to the Harvard College observatory, where we got to do some astrophotography with a much larger telescope (a 16-inch reflecting telescope). He had also made the connection with some folks that my parents knew, who had a ten-inch refracting telescope that was equipped with a camera and spectrograph. The telescope had been purchased in a previous generation by a vice-president of General Electric, who was also an amateur astronomer. When it was built, I suspect it was probably the most advanced telescope in the country not owned by a university. The telescope together with the mount probably weighed a couple of tons, and it was inside a big copper-clad observatory with a rotating dome. The camera was a professional device that used glass plates, mounted on a moving stage so that you could track a nearby guide star to keep the images sharp during a long time exposure. I basically had the telescope to myself for a couple of summers, and taught myself by trial and error how to take deep sky images, process them in the dark room, and make nice prints. Back in high-school, the astronomy club would have open nights for elementary school students, scout troops, and the like, and club members would give a little astronomy lecture or slide show before the telescope viewing. So I learned something about galaxies, stars and planets in putting together those shows.

Walter N. Hawley, science teacher
at St. Paul's School. In 1998 he was
awarded the Thomas Brennan award
for excellence in astronomy teaching
by the Astronomical Society of the
Pacific. He also has a main-belt asteroid
named after him. 

Before going on, I'd like to add a few more notes about Walter Hawley. In addition to having a real passion for astronomy, he has to be one of the most intrepid, energetic, and organized people I ever met. When I was a student at the school, we had two telescopes - the 5-inch Alvan Clarke refractor in the observatory, and portable Questar telescope that we could take out into a field. By the time he retired, the school had an Astronomy Center with four domes, a chart house, and a 27-inch robotically-operated reflecting telescope equipped with a CCD camera. About a quarter of the school now takes one of the astronomy courses sometime before they graduate. Walter Hawley's vision and persistence didn't stop at the edge of the school grounds. He was instrumental in building the Christa McAuliffe planetarium in Concord, in honor of the local science teacher who was to have been the first teacher in space when she perished in the space-shuttle Challenger explosion in 1986. His other passion was sailing. He was not a sailor for sport, but I think approached it as a combination of art and engineering. He supervised the building of a wooden yawl at a shipyard run by two 80-year-old boat builders in New Bedford Mass. It was launched while I was still in high school. When I was in college, he sailed it back and forth across the Atlantic, and spent several months in the Carribean on his boat, with his dog, sailing by day and observing variable stars by night. I count myself extremely fortunate to have encountered such a remarkable person during my formative years.

I majored in astronomy at Harvard. The Center for Astrophysics there has one of the largest concentrations of astronomers in the world. At the time, in the late 70's and early 80's, it was the operations center for the Einstein X-ray observatory. I worked with Rick Harnden as a research assistant. Astronomers working on Einstein at the time were not only making great advances in our knowledge of the X-ray sky, but were also inventing new ways to calibrate, analyze and interpret data. Working with Rick, I learned that solving the mystery of why an instrument behaves the way it does is often a subtle and interesting challenge in and of itself. That's part of what makes working as a support astronomer at an observatory appealing, at least to me.

After college I taught science for a year at Maret School in Washington DC, and then went to the Johns Hopkins University for graduate school. When I entered graduate school, the launch of Hubble was imminent. It was still imminent when I finished grad school eight years later. I worked for a few years on the Hopkins Ultraviolet Telescope with Arthur Davidsen and a close-knit team astronomers, students and postdocs. The telescope was scheduled to be launched in the space shuttle in 1986, coinciding with the passage of Halley's comet. On January 28 1986, we watched in horror as the Challenger exploded. Our mission had been next in line. The telescope finally flew four years later as part of the Astro-1 mission, and again in 1995 as part of the Astro-2 mission. But in the meantime, I was left searching for a new PhD thesis topic.

Allan Sandage in front of the 100-inch Hooker telescope
on mount Wilson (Image from Carnegie Observatories/
Carnegie Institution of Washington)

Fortunately for me, another remarkable person arrived as at Johns Hopkins as a visiting professor at just about the same time. Allan Sandage had been Edwin Hubble's assistant when he was right out of graduate school, and was probably one of the most famous astronomers alive. As a graduate student, he had been instrumental in figuring out how to connect the observations of the colors and brightnesses of stars in globular clusters to the emerging knowledge of stellar structure and nuclear fusion, and was able to use that knowledge to estimate the ages of the oldest stars in our galaxy. As Hubble's assistant and for a good portion of his career thereafter, he built much of the foundation of modern observational cosmology. He is well-known for his measurements of the Hubble constant, the expansion rate of the universe, and for his battles with other astronomers over the various systematic uncertainties in these measurements. But he also laid the foundations for studies of very distant galaxies, in a classic paper in 1961 outlining what the great Mount Palomar Telescope could do, and later in a review article on observational tests of world models that grew out of a course he gave while I was at Hopkins. I believe he has told some people that I was the only student able to do the problem sets. That's not true. I was a senior graduate student and mostly was auditing the course. I don't recall even doing the problem sets. I do recall several amazing 3-4 hour sessions in his office, talking about my thesis, but then free-associating on many questions about galaxies and cosmology and how to use galaxies as measuring rods or chronometers to help explore the evolution of the universe. I also recall that when I handed him a draft of a chapter of my thesis, it would come back to me practically the next day with voluminous comments on all aspects of the work from organization to writing style to the technical minutiae of the analysis. I have never met anyone before or since who paid so much attention to the words on a page.

Sandage had arrived at Hopkins with a stack of enormous glass photographic plates with deep images of the Fornax Cluster of galaxies and a few other nearby groups of galaxies. I spent a couple years inspecting, measuring and classifying galaxies on these plates, and then trying to make sense of the correlations that we found in these measurements. Most of the galaxies in nearby clusters are dwarf-elliptical galaxies. I became very good at identifying these amidst thousands of more distant galaxies. It turns out that these galaxies follow a pretty tight correlation between size and brightness. I helped quantify that with my thesis measurements, but to this day we don't really understand what causes this correlation.

Deep-sky image obtained by Tom Shanks
with the William Herschel Telescope.
The color-stretch on this image shows the faint-blue
quite prominently. If you look closely you will notice that
most of the space between the bright reddish and greenish
galaxies is filled with very faint blue galaxies.

After grad school, I spent three years as a postdoc at the Institute of Astronomy in Cambridge. One of the most talked-about topics in astronomy at the time was the problem of "faint blue galaxies:" there were too many of them. A factor of ten more than expected from the favored cosmological model. Most cosmologists were unwilling to accept that the problem might be in the geometry of the universe itself, rather than in our understanding of galaxies. I spent several years working on the problem from the galaxy perspective, thinking that whatever these faint, blue galaxies were, they might be related to the dwarf galaxies I had been studying in nearby clusters. Together with another postdoc, Arif Babul, I explored a somewhat radical model, which postulated that gas in dwarf galaxies collected there early in the universe, but didn't didn't become cool enought to form stars for billions of years. When the gas finally cooled, it formed stars in a rapid burst, making the galaxies briefly shine brightly enough to be seen at great distance. The theory was at least plausible, and matched a lot of the observations.

A small portion of the Hubble Deep Field.

This was just one of several competing models that were being published when I arrived back in Baltimore as a Hubble Fellow at STScI. One of the ways to try to figure out what was going on would be to take a really long time exposure with Hubble, counting up the number of galaxies to even fainter limits. Ideas like this were floating around when the first images from the refurbished Hubble telescope came back to earth in mid 1993, and showed that it would now be capable of obtaining the sharp images that had been promised. Bob Williams, the STScI director at the time, decided to pour most of his "director's discretionary time" into a very long time exposure -- the Hubble Deep Field (HDF). I became deeply involved in planning and executing these observations, calibrating the data, and trying to interpret the results. The observations immediately ruled out our theory, and many of the others. In fact, within a couple years, observations of distant supernovae, along with other lines of evidence, made it clear that the cosmologists had been wrong: the faint-blue-galaxy problem was due primarily to an incorrect assumption about the geometry of the universe.

The Hubble Deep Field became one of the most studied patches of sky and demonstrated the value of bringing combining observations not just from Hubble but from many different observatories. It also demonstrated the value of making the data immediately public to the astronomical community, without the usual proprietary period to a small group of investigators.  It paved the way for the CANDELS survey and many others.

It has been a long couple of flights, with a delay on the connecting flight. So I fear I have gone on too long. I'm returning to Baltimore from a planning meeting for the Large Synoptic Survey Telescope (LSST), a telescope to be built in Chile to survey the entire southern sky, roughly once every four nights. Albeit without quite the clarity of the Hubble images, this telescope will reach the depths of the original Hubble Deep Field over an area 25 million times larger. As a project, it has much of the attraction of the HDF and CANDELS -- it is aimed at gathering a representative sample of the universe (in this case a very large representative sample!), to enable a huge variety of scientific investigations. And all the data will be public. With that and JWST operating at the same time, there is a lot to look forward to.

The Trials and Tribulations of Finding the Most Distant Galaxy Clusters

OK, now for something a little different. In this post I'm not going to talk about stuff we already know or get right, but the stuff we think we may be getting wrong. That may seem a little negative, but is in fact what astronomers spend much of their time doing. We constantly check, question, argue, ponder … it's only when we've run out of ways to challenge an idea or result that we then tend to think we may have just learnt something.

We've heard before about galaxy environment, and more specifically, the relative importance of galactic nature vs. nurture. Measuring environment (or nurture) has become increasingly popular in recent years, mainly because it's become increasingly possible to do.

In particular, large space-bound telescopes, like Hubble, and the galaxy surveys they produce, like CANDELS, have been especially important in the search for, and classification of, rare yet impressive cosmic structures called galaxy clusters. This has sparked a kind of friendly competition within the community to find increasingly distant clusters in the early Universe. For astronomers, it's a bit like searching for the earliest fossilised pre-humans: a trophy when you can beat the previous record, and (more importantly) juicy new clues to early galaxy life within the cosmos.

An early forming galaxy cluster, but is this a real over-density or
artificial? Credit: Papovich et al. 2010

A perfect example is the 2008 discovery of a early forming cluster at redshift 1.6 (about 9 billion light years distant) by CANDELS team member Casey Papovich and collaborators. This cluster was first identified using the Spitzer Space Telescope in the infrared, and the galaxies within were recently studied using CANDELS data to measure their structural properties, types, masses and colours. However, to date, only 13 galaxies in the cluster have been confirmed to be at the distance of the cluster centre to any precision.

This highlights a problem: when clusters become distant and hard to find, how do we know if we've actually found one? Let me propose that you have to answer three challenges before you get to pop the champagne cork on a new cluster distance record:

1. Demonstrate that the galaxies making up the cluster aren't just a chance alignment of unassociated galaxies along the line-of-sight. When you only have very rough distances, which is often the case (called photometric redshifts in astronomy-speak), such alignments can be a very common occurrence, and tricky to recognise.
2. Show that the "reality" of the cluster doesn't depend on the method used to find it. There are many environment "metrics" employed by astronomers, typically based on counting galaxies projected on the sky within a fixed radius, or by an association of nearest neighbours. But the measurement techniques are varied, the uncertainties large, and the agreement between them approximate at best.
3. Even when you've found a genuine cluster, how do you actually know what it will evolve in to? Simulations have shown that some structures grow fast and some slow, and there's no way to know in advance. It may be that the future for this particular object is rather boring and not the "Australopithecus" you were expecting.

At Swinburne, my graduate student Genevieve Shattow and I have been looking into these issues using CANDELS-based simulations of galaxy and cluster formation. These simulations are useful because we have "perfect" information for every modelled galaxy, unlike the real observations. By perfect I mean that every property of each dark matter halo and galaxy are precisely described (because we made them!), and the history of each is fully identified. We can use this information to our advantage.

With this simulation we looked at the most massive cluster at redshift 2 (i.e. when the Universe was 1/3 its present age, and where the current distance record is) and asked:

• How accurately can we identify the cluster if we degrade our information to be comparable to that of real observations?
• When we apply different environment measurement techniques, do they paint a consistent picture? Or do they return different answers?
• What will this object evolve into? Is it actually interesting? Is there a way to separate the interesting objects in the distant Universe from the more mundane ones without knowing in advance?

We're still working on these problems, but let me show you a few early, yet slightly disturbing results.

The above figure shows how galaxies in the larger environment around this simulated cluster appear on the sky if observed at four different times, ranging from the present day (far left) to redshift 2 (far right). We've coloured the galaxies: purple shows the actual gravitationally bound cluster members, while black are the non-cluster galaxies. The circle represents the typical radius astronomers would count within to look for over-densities, signalling the presence of a cluster.

As you can see, finding a cluster in the present-day Universe is fairly easy as there are many galaxies around to characterise it. In the early Universe though it's not so clear. Even worse, the ratio of cluster to non-cluster galaxies tips in an uncomfortable direction, making it hard to distinguish the actual cluster members from the background of field galaxies.

Different viewing angles of the same
cluster return different cluster
membership due to projection effects

We can play an even more illuminating game with the simulation. Let's again look at this single cluster and its surroundings at redshift 2, again projected onto the sky, but now from many different angles. Since galaxies in three dimensions will project differently on to the two dimensional sky depending on the viewing angle, the measured environmental over-density within the circle will vary. But by how much?

The distribution of counted galaxies based solely on changing the viewing angle is shown in the figure on the right. As can be seen, the environment measure may find 60 cluster members, or it may find 80 cluster members. That's a big difference for what is in essence exactly the same object! Given that we can't correct for such projection effects in real observations, this highlights a substantial uncertainty in any such measurement.

This is just the beginning of our work, but important to quantify if we're to have an honest accounting of the issues around measuring galaxy environment in real data. In doing this we'll be looking for ways to correct such biases, hopefully making the job of cluster identification easier and more accurate. This will enhance the value of data from galaxy surveys such as CANDELS and the science that follows from them.

How Far Away is this Galaxy?

In previous posts you have read a lot about redshift and the distance of galaxies from us. You have read how to find and select very distant galaxies and how to distinguish between different types of galaxies from their spectral energy distributions. What you haven’t read in more detail is how astronomers determine a galaxy’s distance or redshift. I’ll tell you a bit more about this now.

The electromagnetic spectrum: wavelengths get smaller from the radio to gamma rays.
A wavelength is here the distance between two peaks of the red wave. Credit: NASA

First of all, let’s recap again what redshift means. I guess all of you have heard an ambulance with its siren switched on passing by. You might have noticed that the pitch of the siren changes as the ambulance moves. In particular it sounds higher when it approaches you and deeper when it drives away from you. (The same is true for the sound of passing by race cars which make the popular "brrrmmmmm" sound kids love so much.) This effect is called the Doppler Effect. While the ambulance moves, the sound waves coming from the siren are squeezed when it drives in our direction and stretched when it moves away from us, resulting in a different sound.

The same happens to the light of distant galaxies. The Universe is expanding and so distant galaxies are moving away from us. The light emitted by these galaxies is stretched out on its way to us. If the galaxies were moving towards us, their light would be squished. Because light can be described as a wave just like sound, this stretch/squish means that its wavelength is changing. Blue light has a shorter wavelength than red light, so light that is blue when it is emitted turns redder on its way to us when the galaxy is moving away, hence we say it is redshifted. The light from distant galaxies takes a long time to reach us. The further away the galaxy is the longer it takes, because light travels with a particular speed and nothing is quicker than light. So if we know the redshift of a galaxy, we know its distance to us and with this we know how long it took the light we see today to get to us. Hence, we see distant galaxies not as they are right now (this light is just emitted and hasn't reached us yet), but as they were a long time ago. With a particular redshift astronomers can assign a so-called look-back time which is the time the light of a galaxy at this redshift took to reach us. For example, the light of the sun takes 8 minutes to reach Earth, but it takes about 5 hours to reach Pluto. The light of distant galaxies needs billions of years to reach us which means they existed when the Universe was very young.

   redshift                  look-back time                   age of the Universe

   0                                         0                                      13.7 billion years

   0.0043                      59 million years                         13.6 billion years

   0.01                        140 million years                         13.5 billion years

   0.1                           1.3 billion years                          12.4 billion years

   0.5                              5 billion years                            8.6 billion years

   1.0                           7.7 billion years                            5.9 billion years

   2.0                         10.3 billion years                            3.3 billion years

   3.0                          11.5 billion years                           2.2 billion years

   4.0                          12.1 billion years                           1.6 billion years

   5.0                          12.5 billion years                           1.2 billion years

   7.0                          12.9 billion years                          800 million years

   10                           13.2 billion years                          480 million years

I've listed the look-back times and ages of the Universe for some redshifts above (for the very cosmologically interested: using a Hubble constant of 71 km/s/Mpc and Omega Matter, describing the density of matter in the Universe, of 0.27 assuming a flat Universe, but you can play yourself with these values over here). Redshift 0.0043 is the redshift of the closest large galaxy cluster to us. Up until redshift 0.5 the galaxy population is pretty well mapped out and studied by surveys such as SDSS. The range between redshift 1 and 3 is interesting to researchers to study how galaxies assemble their mass as we told you in this previous post. Redshift 7 is close to the redshift of the most distant galaxy known to date. With CANDELS we hope to detect many galaxies at this redshift and even further away. We hope to discover galaxies at redshift 10 someday, which were perhaps the first galaxies to form in the early Universe.

Redshift Determination

Example of emission lines in a galaxy spectrum. Credit: Jeyhan Kartaltepe

There are two ways to determine the redshift or distance of a galaxy, either from the spectrum of that galaxy or from its spectral energy distribution (SED) and colours. If astronomers have spectra available, they look for particular features in each spectrum, such as emission lines (those spikes in the figure to the right) or absorption lines. Emission and absorption lines are caused by elements in the galaxy that emit or absorb the light of that galaxy’s stars at particular wavelengths. From lab experiments we know at which wavelength the lines of various elements should be when not moving, we call this the rest-frame wavelength. We also know what their separation in a spectrum is. In order to determine the redshift of a distant galaxy one can look for the spectral lines caused by elements in that galaxy. Since the elements are located within that distant galaxy, the wavelengths of the spectral lines are redshifted by the same amount as all other light coming from the galaxy. We say these observed spectral lines are in observed-frame. The difference between the rest-frame and observed-frame wavelength of a particular spectral line lets you calculate the redshift of the galaxy. The difficulty with getting redshifts from spectra lies in the identification of the spectral lines, you need to be sure that the line you are seeing comes from the element that you think it is. It is easier if spectra have several lines that can be used to determine the redshift because then you can identify the pattern of lines, and know without a doubt what the observed lines are. A redshift determined from a spectrum is called 'spectroscopic redshift'.

SEDs of typical galaxies at different redshifts. The solid curves show the SED in
the rest-frame or at z=0, meaning how it looks when the galaxy is very close to us. The
dotted and dashed lines show the same SED at redshifts z=1 and z=2, meaning the
light from such galaxies traveled about 8 billion and about 10 billion years to reach us!!
The bottom panel shows various filter bands from U (blue curve, visibly blue light) to
infrared bands (black curves), the filter bands are the same ones we showed you in
the SED post. Galaxy templates are taken from Polletta et al.

Taking spectra of many galaxies is very time-consuming and requires a lot of telescope time, which can be difficult to get. Instead, with imaging, you can observe thousands of galaxies at once and construct an SED by using multiple filters. In this case you can still determine the redshift of a galaxy by using SED-fitting. Astronomers take advantage of the fact that the SEDs of galaxies have particular shapes and features at specific wavelengths. For example the Lyman-break that is used to find distant galaxies and about which Russell told you in his post is always located at the same rest-frame wavelength and shifts to redder wavelengths the further away the galaxy is. Another important feature is the so-called 4000 Angstrom break. The 4000 Angstrom break (at 0.4 micron in the figure to the left) occurs because many heavy elements in the atmospheres of old stars in the galaxy absorb some of the starlight around this particular wavelength. The brightness of a galaxy changes noticeably from the left to the right of this break, so in one filter band the galaxy will be brighter and in the other one it will be fainter. A comparison with model galaxies and the location of these jumps in brightness allows us to estimate the redshift of the galaxy. The better the shape of the SED and features such as the mentioned spectral breaks are sampled with the images, the better we can determine the redshift. A redshift determined from galaxy images where no spectrum is available is called a 'photometric redshift'.

For large galaxy surveys, the latter method is used to measure redshifts for many objects at the same time. Although the uncertainties for photometric redshifts are larger than those for spectroscopic redshifts and photometric redshifts can be wrong for single objects, researchers gain better statistics with large sample sizes. Furthermore, the redshift distribution of that sample will be correct on average. While CANDELS itself is focused on imaging data, many spectroscopic surveys have been undertaken in these deep fields and new surveys are always ongoing to obtain more spectra. A lot of CANDELS science you will read about here will make use of photometric redshifts.

Astronomer of the Month: Duilia de Mello

Each month we will highlight a member of the CANDELS team by presenting an interview introducing them and what it's like to be an astronomer. This month's Astronomer is Duilia de Mello.

Tell us a little about yourself!

My name is Duilia de Mello. I am an Associate Professor at The Catholic University of America in Washington DC. I teach Physics and Astronomy at CUA and do my research at NASA's Goddard Space Flight Center. I am from Brazil and I have a PhD in Astronomy from the University of Sao Paulo. I was a post-doctoral fellow at the Hubble Space Telescope Science Institute.

What is your specific area of research? What is your role within the CANDELS team? 

My area of research is galaxy evolution. I study how galaxies interact with each other and how they evolve to become galaxies like our own Milky Way. I am one of the leaders of the ultraviolet team of CANDELS. We will be searching for galaxies having bursts of star formation and analyzing their shapes around 7 billion years ago when the Sun was not even born yet.

What made you want to become an astronomer? At what age did you know you were interested in astronomy? 

I was one of those curious kids who always wanted to know more and more. NASA's spacecrafts Pioneer 11 and Voyager 2 were sending images of the planets for the first time and the universe was a big puzzle to me. I had to become an astronomer to know more about it. At age 16 I was ready to do that but my family wasn't. Nobody knew what an astronomer did and my mom decided to take me to the university to visit the small Observatory in downtown Rio de Janeiro where I am from. When I entered the building and met some of the students I knew that I wanted to be one of them. But at that point I promised my mom that I was going to be able to make a living as an astronomer. We lived in a poor neighborhood in Rio and had very little money. But fortunately college is free in Brazil, if you are a good student. So I went to the best university and did my best.

What obstacles have you encountered on your path to becoming an astronomer and how did you overcome them? 

The career path is really long and it is natural to get discouraged during those long years of study. And after getting a PhD one still needs to wait several years and look for post-doctoral positions anywhere in the world. It is really hard to plan ahead. So at some point one tends to forget why they actually entered the career and start questioning if it is really worth the long hours of dedication and the little money one gets. It is also very hard to get peace of mind knowing that there are so few jobs and one tends to get pessimistic after a few years trying. But I am a dreamer and I could not think of myself doing anything different. There are so many advantages in following your dreams and during those crisis in the career I looked at friends and family who were doing other things, who had standard jobs, and saw how lucky I was.

Who has been your biggest scientific role model and why? 

When I was a graduate student I met a French female astronomer in my field of research, Francoise Combes, and decided that I wanted to be like her when I grew up My male supervisor used to call her Superwoman. She was everywhere we looked at. She was invited to give talks, she was observing in many observatories, she was chairing meetings, she was publishing dozens of articles, she had a family and she was a world traveler. Her work was phenomenal and she was extremely active. I consider her a friend and a colleague now and I still admire her energy and her accomplishments.

What is it like to be an astronomer? What is your favorite aspect? 

To be an astronomer is to be a scientist. We live to ask questions and to search for answers. It is intriguing and rewarding. One of my favorite aspects is the freedom we have at work. We don't have to work for a certain number of hours or to be at a desk for those hours. We can be in an airplane and be working. I like that. I also like the international aspect of astronomy. I have friends everywhere in the world and I have lived on three continents.

What motivates you in your research? 

The fact that we still do not know how our own galaxy formed and evolved keeps me going. I feel I need to contribute somehow to that puzzle. 

CREDIT: STS-82 Crew/STScI/NASA

What is your favorite astronomical facility? (This could include telescopes or super computers, for example) 

I am a Hubble hugger. There is no other telescope like Hubble.

Where do you see yourself in the future? What are your career aspirations? 

As a professor I hope to inspire many students to learn more about the universe. I hope to become a role model to my own graduate students and to help them succeed.

If you could have any astronomy related wish, what would it be? 

I wish there was more funding for astronomy. I wish foundations would start looking into funding astronomy projects. There are so many open questions that need to be answered and so little funding to make that possible.

What is your favorite, most mind-boggling astronomy fact? 

I have been staring at the deep fields taken with Hubble for decades, but I still find it amazing that when we look at deep images we are seeing the past, billions and billions of years ago.

Is there anything else you would like for the public to know about you or astronomy in general? 

In 1997 I discovered a supernova in Chile when I was observing other galaxies. I was not searching for supernovae but my curiosity drove me to the discovery. It was an amazing feeling to know that I was the first one to see a star exploding and to know that I was able to make the right choice when I was observing. This discovery made the headline news in the newspapers in Brazil and until today people still remember that I did that. There is even a fan club created by young students dedicated to the Woman of the Stars (or Mulher das Estrelas in Portuguese). I have been told that there are very few scientists with fan clubs so I am proud of being one of those

How to Find Distant Galaxies

The study of the most distant galaxies is a very active and quickly evolving field, led primarily by the Hubble Space Telescope. But before discussing the exciting results, we should first address the question of "How do we find distant galaxies?''

The spectrum of a distant galaxy and the typical
appearance in the HST deep fields.

Over the years several schemes to identify galaxies at high redshift have been developed, but the most common technique is known as the "Lyman-break method.'' In every galaxy there are not only plenty of stars, but also a lot of hydrogen gas clouds. These clouds will absorb most of the bluest light emitted by young stars, which causes the blue portions of the galaxy's spectrum to be completely missing. We call the missing region of the spectrum the "Lyman break*.'' Due to the expansion of the Universe, distant galaxies are receding from us, resulting in a "redshifted'' spectrum. Like the Doppler shift of the siren from a passing ambulance, the expansion stretches the spectrum of a distant galaxy, causing the light to be observed at redder wavelengths. Therefore the Lyman break is observed at progressively redder wavelengths as the distance of a galaxy increases. So to find a distant galaxy, we take many images of a galaxy at varying wavelengths and identify the wavelength where the galaxy is missing or is said to "drop out.'' In the related figure, we show the spectrum of a typical distant galaxy (in dark grey) with a series of filters (in light grey, red, green, and blue), but just focus on the colored filters for the time being. Notice how the spectrum has completely "dropped out'' in the blue-shaded filter; although stars have emitted light at these wavelengths, this light has been absorbed by hydrogen gas. Above each filter you can see a typical distant galaxy in HST images (colored accordingly). It is important to notice the complete lack of observed light in the blue image, despite robust detections in the green and red images. This results in a characteristic three-color image, which is the hallmark of a high-redshift (or distant) galaxy.

In that still image, we have showed how three adjacent red, green, and blue filters can be used to find galaxies at a specific redshift (in that example, it was redshift 3.0 or a distance of 11.5 billion light years). We can select other redshift windows by tuning our filters to sample the Lyman break at other redshifts. In the above video, we demonstrate how as redshift/distance increases the Lyman break moves to progressively redder wavelengths and show representative images of high-redshift galaxies from several HST deep fields. When it falls between two adjacent filters, we have a means to find distant galaxies. If you carefully watch the grey spectrum as it moves through the filter-set, you may notice a depression growing by the strong emission line (known as Lyman alpha). Stay tuned for more details on this depression, its causes, and its uses!

For more great HST images of distant galaxies and to see the progress we've made, check out:

• CANDELS 2011 van der Wel et al.
• HUDF 2010 Illingworth et al.
• ERS 2010 Windhorst et al.
• HUDF 2004 Beckwith et al.
• GOODS 2003 GOODS Team & M. Giavalisco
• HDF 1996 Williams et al.

*For the quantum mechanically inclined, the Lyman break occurs at the Lyman limit of 0.0912 microns due to the energy spectrum of neutral hydrogen.

The multi-wavelength shapes of galaxies - Spectral Energy Distributions

In this post I’d like to tell you a bit more about the spectral energy distributions of galaxies, what they tell us and how we can decode the properties of galaxies, such as a galaxy’s mass, using a galaxy's spectral energy distribution.

A spectral energy distribution (SED) shows how the energy output of a galaxy is distributed across the electromagnetic spectrum, meaning how bright the galaxy is at each particular wavelength. As was described in previous posts, galaxies consist of many different components, such as stars, gas and dust, and possibly active galactic nuclei (AGN). Each of these leaves a different and specific imprint on a galaxy's SED. For example, young stars are very bright and emit most of their light in the ultraviolet and blue optical (visible) part of the spectrum while old stars emit most of their light in the red optical (visible) and near-infrared. This difference is due to the different temperature of the stars: young stars are very hot, old stars are cooler. You can see this difference by comparing the different shapes of the SEDs for the elliptical (red curve) and spiral (Sd, blue curve) galaxies in the picture below. For a starbursting galaxy that is undergoing a merging event, such as Arp 220 (purple line), the SED shows that the galaxy is very bright in the infrared compared to its optical emission and compared to normal star-forming galaxies like the two spiral galaxies. That is why Arp 220 belongs to the class of ultra-luminous infrared galaxies which were described in a previous post.

Spectral energy distributions for typical galaxies - an old elliptical galaxy (red), two types of spiral galaxies (Sb in green and Sd in blue), an AGN (Markarian 231, solid black), a QSO (dotted black), and a merging and star-bursting galaxy Arp 220. Template spectra are taken from Polletta et al. 2007.

AGN on the other hand show themselves in the ultraviolet, optical, X-ray, and sometimes also at radio wavelengths. The overall shape of an AGN SED (shown here is that of Mrk 231) is similar to that of a power law, meaning in the figure above, the black line is very flat at optical and IR wavelengths. The SED of a QSO, a quasi stellar object, an object for which the AGN outshines the host galaxy in which it resides, is very steep and shows emission lines in the UV and optical.

If dust is present in a galaxy then some of the ultraviolet and blue optical light is absorbed and re-emitted in the infrared which can be seen as bumps in the purple, blue and green curves (around a wavelength of 5 to 110 micron). You might have also noticed the "spikes" of emission in the SEDs around about 5 to 12 micron, these are caused by so-called polycyclic aromatic hydrocarbons (PAHs), which are a class of organic molecules. They give important clues towards the structures of dust in galaxies, star formation, and the merger histories of galaxies.

Thus, from looking at the spectral energy distribution of a galaxy one can establish what kind of stars live in the galaxy (predominantly old ones or young ones), how much dust is present in the galaxy, with what intensity it formed stars over its lifetime, and if the galaxy has an active galactic nucleus or not and how active it might be.

Spectral energy distribution fitting

In order to extract the information encoded in the SED one can fit the SEDs of model galaxies to the data. This is called spectral energy distribution fitting. Let’s first look at the data needed for this. Instead of taking a spectrum - very detailed data showing how the light of the galaxy is distributed over a narrow wavelength range - one takes images of the galaxy in a number of filter bands (which only let the light in a narrow wavelength range through, see figure below). From each filter band image one obtains a number for the brightness of the galaxy at that particular wavelength (green dots with error bars in the last figure of this post). Combined, these numbers trace the overall shape of the SED of the galaxy. Since the different components of a galaxy (stars, dust, AGN) leave their traces at different wavelengths one aims at imaging galaxies over a wide wavelength range. The CANDELS fields with their vast data coverage are an ideal data set for this sort of analysis.

Shown are some commonly used filter bandpasses from the optical and near-IR wavelength ranges (wavelength on the x-axis). For each filter only the light of an object that is within the curve of the filter is detected, everything outside is excluded. Credit: Janine Pforr

On the other hand model galaxies are needed for comparison. So-called model SEDs or templates, can be created purely based on the theory of stellar evolution or by using real observed SEDs of typical galaxies. The model spectra for different types of galaxies are treated in the same way as the observed, to-be-analyzed data. The brightness of the model galaxies in each filter band is obtained and compared to the brightness of the real galaxy in the same filter band. The properties from the model galaxy – such as age, stellar mass, star formation rate and history, amount of dust - that best compares overall to the real galaxy are then assigned to the real galaxy.

Example of an SED-fit: the blue and red curves are two different model SEDs that are fit
to the green data points (brightness in the listed filter bands). The blue model represents
an old galaxy, nearly 4 billion years old, which does not contain any dust. The red model
represents a very young galaxy that is also very dusty. Both models fit the data equally well,
demonstrating the difficulties astronomers face when analyzing SEDs. Credit: Janine Pforr

Although this might sound simple, there are many galaxy properties that make the SEDs of very different galaxies look very similar over some wavelength range. One of the most prominent difficulties one faces is the ambiguity between the age of the galaxy and its dust content. For example, a young but dusty galaxy looks red (red curve in the picture to the left) but an old dust-free galaxy looks red too (see blue curve in the picture to the left).  

Since the only data required for SED-fitting is obtained from taking many images of a galaxy and with modern instruments it is possible to take images of tens of thousands of galaxies at the same time, SED-fitting is a very popular method to analyze large numbers of galaxies efficiently. The results can then be used to try to understand how galaxies formed and evolved with time. Many CANDELS team members use SED-fitting in their research and you will soon hear more about their exciting results.