Tag Archives: stars

Dr. Rawls

My PhD defense took place in Las Cruces on April 8, and was successful! If you’re interested, you can watch my presentation and/or view my slides. However, please be aware the intended audience for this talk is fellow astronomers, not the general public.


I’ve spent the last week or so revising my dissertation, and I’m happy to report it passed the graduate school’s format review today. Once the final copies are printed (yes, multiple copies; yes, printed) and accepted, I will add it to the Astronomy Thesis Collection online and write a post summarizing the main results. I’ll be back in New Mexico in May to celebrate graduation with my family, and I intend to consume even more burritos before embarking on a road trip north.


On Writing a Thesis

If you spend any time around graduate students, you know the culmination of years of work toward a degree ultimately comes down to pouring the essence of that work into a giant written document very few will ever read: a thesis. Also known as a dissertation. (Due to my US-centric perspective, I treat the two as synonyms in this post.)

As it happens, I finished a full draft of my thesis yesterday. It has been a stressful, exhausting, anxiety-riddled few… weeks? months? Yeah. The “fun” isn’t over yet because there are certainly revisions in my future, not to mention the actual thesis defense, which will consist of a public talk followed by an indefinite period of conversation/questions/snake fights with my committee behind closed doors.

So that’ll be great.

But my goal today is to give future-thesis-writers a window into what my process looks like, and share the tools I used to make it slightly less painful than it could have been.

My thesis contains five chapters and three appendices in about 200 pages and roughly 25,000 words. (The word count is imprecise and rounded down because a thesis has lots of words that aren’t exactly part of the main text.) As I understand it, this is a reasonably typical length for astronomy, but I honestly don’t care, because I think I said everything I needed to say.

I have three pieces of unsolicited advice, which boil down to: know how you work, get tools you’ll use, and what I’ll call “think globally, write locally.” Let’s go.

Know how you work

Maybe you’re one of those people who likes to wake up early, gets important work done before the rest of the world is awake, has completed all your thesis research well in advance of when you’d like to defend, and has published four papers along the way. In that case, I say congratu-effing-lations, you have this in the bag.

For the rest of us, it’s time to take stock of how you work. Think about the last time you were really “in the zone” and got a lot of work done solo. Where were you? What was the environment like? What time of day was it? Did you have a certain beverage, view, or music at hand? Figure out what works best for you and structure your life around it. Maybe that means you need to unplug the internet, build a playlist, budget for daily coffeeshop purchases, work in pomodoros, disable email notifications, or embrace the popcorn workstation. Maybe it means you need to block out writing hours on your calendar, get a transit pass, find a standing desk, set weekly deadlines, or pull all-nighters every Tuesday. It doesn’t have to make logical sense and it doesn’t have to be a lifelong commitment; it just has to work for you for now.

If you’re having a hard time remembering the last time you felt highly productive working alone, or the specific circumstances, don’t despair. It’s never too late to try new productivity techniques. We’re all making this up as we go!

Get tools you’ll use

Writing a thesis is more than just opening a blank document and dumping your brain into it. There’s formatting and references and figures and tables and… so many pieces that somehow have to come together. Thankfully you are not the first person in the history of humanity to tackle these problems, and lots of tools exist to help. Good tools are easy to use and lighten your cognitive load so you can focus on the content of your thesis rather than the mechanics of writing it. But not every tool works for everyone, and sometimes you have to be patient with yourself and your computer while you try and discard one after another. After much trial and error, here are some of my favorites.

OmniFocus: The powerful to-do list app that basically changed my life. This is a place to write down action items for everything in your life, from errands to work to any random task or idea you need to get out of your brain. The degree to which I use OmniFocus to its full potential varies, but whenever I need to get something done I take the time to break it up into small, manageable pieces here. You can use it to set deadlines, start-later deferral dates, color categorizations, location- or person-based contexts, and so much more. OmniFocus is not free, it is only for Mac/iOS, and it syncs seamlessly between them. If you are thinking of trying just one of the tools listed here, it is the one I recommend most highly.

TeXShop, ShareLaTeX, and a LaTeX class file: If you want to write a thesis, you’re probably going to need some LaTeX. My editor of choice is TeXShop, which is free and lets you place writing (editor) and viewing (PDF) windows side by side. If installing LaTeX gives you trouble, I recommend ShareLaTeX, which is also free, works in any browser, and syncs with Dropbox (see below). You’ll also need a class file with various packages to tell LaTeX how you want your thesis formatted. Many departments and universities have official or unofficial class files that adhere to formatting guidelines. Ask around to see what older students or recent graduates from your department have used. In my case, NMSU graduate Jeff Coughlin created aastex-thesis (based on AASTeX v5) and a set of well-documented sample files that compile into a pretend thesis—about exowhales, no less!

Dropbox: You probably don’t back up your work as often as you should, and even if you do, it’s probably not every time you hit “save.” I initially uploaded my thesis files to ShareLaTeX, linked that to Dropbox, and then did most of my writing in TexShop. So long as I was online, the latest versions of all my thesis files were automatically synced with the cloud. This offered peace of mind, because if my computer spontaneously self-destructed, I could have continued working with ShareLaTeX on any computer with internet access.

TextWrangler: My go-to text editor. You can use alt/option-click to select a rectangular block of text (a column), it has brilliant find-and-replace, and it lets you remotely edit files over ssh. I use this for everything, including python programming, formatting LaTeX tables, and keeping a BibTeX bibliography file up to date. TextWrangler is free and for Mac only.

Papers: The absolute last thing I want to actively think about is how to cite a paper or format my bibliography. BibTeX handles some of this, but it can’t help me find the paper I’m looking for or open several in tabs for me to continually reference. Papers lets you save PDFs in a special folder, automatically organizes that folder and imports information about that paper, and makes it easy to copy a BibTeX record into your bibliography file. From there, you can customize a natbib keyword, run a series of LaTeX-BibTeX-LaTeX-LaTeX commands in TeXShop, and carry on writing. Papers also syncs between devices (Mac/Windows/iOS) so you can read papers on the go. It’s not free, but they offer student pricing and it is well worth the investment.

SnagIt: This is just a fancy screenshot program. I use it to grab a figure from a paper, save it in the “figures” subdirectory of my main thesis directory, and add it to my thesis. It’s not free, but there are many other perfectly good screenshot options out there.

Evernote: My research notebook. My workflow is essentially paperless, so anything I need to jot down goes here. I write a brief summary of what I did each day for my own personal reference. Quick calculations, the location of important files, and notes taken during meetings all land in Evernote. It’s free and syncs between all my devices which makes it a handy reference during meetings and conferences.

RescueTime: A neat little free app that runs in the background on my computer and tracks how much time I spend using different applications. It keeps you honest and lets you compare hours spent on different tasks from week to week.

focus@will: Various types of music and ambient sounds that help get you in the flow of working. I use this when I just can’t concentrate and/or when I want music but don’t want to spend time deciding what to listen to. It’s a subscription service with a free trial period. [post edited to add this one]

Slack: Did I mention I’ve been finishing my PhD remotely over the last year? This means my collaborators are never “just down the hall,” and Slack bridges that gap for free. I’ve become at least as good of a communicator from afar than I ever was when I could theoretically walk to a colleague’s office. For example, during a virtual meeting, everyone can easily share plots and other files in real time.

“Think globally, write locally”

One of the most challenging parts of a thesis is figuring out just how to pitch your epic, unprecedented contribution to the field. There’s no getting around it: this is important, and part of the game is convincing others your results matter. But if you don’t have it figured out yet, there’s no reason you can’t start writing your thesis anyway. I essentially arrived at my conclusions as I was writing, for two reasons: the final numbers pertaining to my stars weren’t ready until days before my draft was due, and the process of writing about those numbers helped me clarify the story they could tell.

I can’t work if things aren’t organized, so the first thing I did after I had a set of mostly-empty LaTeX files in place was come up with chapter and section titles. I decided, quite arbitrarily, that I was going to have four chapters: Introduction, That Paper I Just Published, and Applying Stuff I Did In That Paper To Similar Situations (split into two logical halves), and three appendices. Then I created sections, and subsections, and even a few sub-subsections. Once all this was written down, I had a clearer idea of what my thesis looked like globally. Then I could pick a smaller “local” section I was ready to work on and get a finite piece of thesis done in one writing session.

That’s not to say the chapters and sections couldn’t change! They most certainly could, and did; for instance, at the eleventh hour, it was decided I would write a fifth chapter entitled Larger Context And Summary Of This Entire Damn Thing. More or less. But by that point, it was clear I had some things left to say which did not fit in the other four chapters, and adjusting course made sense.

With tools in place to handle formatting, citations, figures and tables, colleague communication, a to-do list with bite-sized pieces, and an outline as a jumping-off point, all that was left was the writing. I know enough about how I work to block off large chunks of time in the afternoon and evening during the last few weeks, which culminated in one final writing push from 10pm-5am on Sunday night. It sucked, but it worked. At least, I think it did. My committee will have the final say on that in the next couple of weeks.

Not my favorite way to spend Easter weekend, but I think the bunny had it worse.

The Double Red Giant With Odd Oscillations

My latest paper was accepted for publication on December 31, announced on the astro-ph preprint arXiv on January 5, and will appear soon in The Astrophysical Journal [UPDATE Feb 11! Rawls et al. 2016, ApJ, 818, 108]. It was written online using Authorea. I also wrote several programs in python to analyze data for this paper.

Picture two nearly-identical stars orbiting each other. Something like this:

An approximation of the double red giant binary KIC 9246715, created using an eclipsing binary simulator. In reality, the two stars are separated by more than 200 times our Sun’s radius, but this simulator maxes out at 60. One orbit takes 170 days rather than the 26 illustrated here. The brightness, or flux, dips when one star passes in front of the other. The eclipses are not evenly spaced in time because the orbit is eccentric.

Even though they usually appear as a single dot of light, binary stars are one of the best tools astronomers have to measure stellar properties. Thanks to the math behind gravity, we can weigh pairs of stars using the relationship between how long an orbit takes and how far apart the things are doing the orbiting. Weighing stars accurately is important because a star’s mass seals its fate. So if every star in the night sky had a secret companion star (or exoplanet!), we could wrap this up pretty neatly and move on to deeper questions about stars’ lives.

Unfortunately, only about half of stars have orbiting companions, and many of those aren’t observable because they don’t happen to be edge-on like the case shown above. This is where starquakes come in.

Weighing stars from the inside out

Some stars, including our own Sun, ring like bells. Pressure waves are excited by convection inside stars, and the waves bounce around at resonant frequencies just enough to make them pulse, or oscillate. Because an oscillating star is changing brightness ever-so-slightly, we can use regular observations of brightness versus time (from Kepler, in my case) to pull out the frequencies of oscillation. Heavy stars oscillate differently from lighter ones, and big stars oscillate differently from smaller ones. Voila—a new technique for weighing stars that doesn’t require anything in orbit!

Of course, the story doesn’t end there. While the study of starquakes (more formally known as asteroseismology) is a powerful way to characterize many stars quickly, it remains relatively untested. We don’t know how accurate of a scale we’re using when we whip out asteroseismology to weigh stars. To address this, my colleagues and I identified about twenty binary systems containing red giants. That’s the kind of star our Sun will become when it runs out of fuel in billions of years. Red giants are convenient targets for asteroseismology because they are bright and oscillate slowly. Both properties make them easier to observe than Sun-like stars. And since our red giant stars all live in binaries, we should be able to weigh them in two independent ways and compare the results.

Solar-like oscillations make a comb-shaped pattern at different resonant frequencies. The central location of the spikes and their spacing in frequency tell us about a star’s average surface gravity and density, respectively. Red is oscillations from the double red giant binary in my paper. Gray is oscillations of a single red giant star with similar properties, plotted upside-down for reference. Figure 7 from Rawls et al.

The case of the missing oscillations

In my paper, I present a case study of two red giant stars in an eclipsing binary. From binary modeling, I show that the stars are both a little more than two times as massive as the Sun, and over eight times as large. However, I am surprised to only find a single signature of starquakes in the observations. Two similar but not-quite-identical stars should, in principle, both oscillate. The oscillation modes, pictured above, are broader and weaker than expected, too. The same physical process could be fully stopping oscillations in one star and only partially suppressing them in the other.

By harnessing many observations (both images and spectra) and modeling techniques, I thoroughly characterize both stars and investigate why only one of them appears to oscillate. I measure each star’s mass, size, temperature, chemical composition, level of magnetic activity, and tidal force strength, among other things. Then I bring in asteroseismology to see if I can tell which star is oscillating and if its story checks out.

By simultaneously modeling different observations of this double red giant binary, I can map the geometry of its orbit in space and measure each star’s mass and size. I do this by fitting a model (black) to observations (red and yellow). The top panel shows radial velocities, or how fast each star is moving toward/away from us, and the other panels show a light curve, or brightness versus time, with two eclipses (the bottom is a zoomed view of each eclipse). The x-axis is in units of how long one orbit takes, which is about 170 days for this binary. Figure 6 from Rawls et al.
Stars emit different amounts of light (flux) at different colors (wavelengths), but the light from a binary contains overlapping information about both stars. As the stars orbit, characteristic dips in flux shift to higher or lower wavelengths depending on how fast they are moving. To create one representative spectrum for each star as shown here (red and yellow), I used a physical model of the stars’ orbit to remove the velocity offset from each observation and then combined them. This process is called disentangling. An example of a single observation containing light from both stars (before disentangling) is plotted in black. Figure 5 from Rawls et al.

As it turns out, the two stars in this binary are similar enough that it’s impossible to say for sure which one the oscillations belong to. Recent work has shown that magnetic fields may suppress oscillations in stars, however, so I strongly suspect the oscillating star is the less magnetically active of the pair. There may be a weak second set of oscillations, but the signal is very noisy and doesn’t appear quite where it should. Either way, the single mass and radius derived from asteroseismology is consistent with that of both stars from binary modeling.

Fraternal twins: born together, but not identical

Because oscillations bounce around inside stars, they carry information about how stellar interiors are structured. Stars of different ages have very different things happening inside: younger red giants are still fueled by hydrogen, while older ones are fueled by helium. The oscillating star in this binary appears to be in an advanced helium-burning stage of its life called the horizontal branch or secondary red clump. I verify this with stellar evolution modeling, and confirm that the two stars most likely were born, grew up, and evolved together. They are about 940 million years old.

The next step is to do a similar analysis for the other red giant binaries my team identified. We are working on two fronts: comparing masses and radii from binary modeling and asteroseismology, and using those results to investigate why about a third of red giants don’t show any oscillation behavior. Our work has important implications for understanding the composition of our Milky Way galaxy, because bright red giants are often surveyed to better understand our galaxy’s history and structure. It’s important to get their stories right.

Simulating the Universe

Collecting light from distant stars and galaxies is pretty straightforward. You just need a really big light bucket (also known as a telescope). But turning that light into a story about how the Universe was born, grew up, and will die is much harder.

At the huge distances between galaxies, gravity reigns*. To see how structures in the Universe change over time, researchers use computer simulations: they throw a bunch of virtual particles in a box, turn on gravity, and see what happens.

Of course, the devil is in the details. Starlight, supernova explosions, piles of gas and dust flying between galaxies… all of this is a complex interaction of much more than just gravity. The fun really begins when scientists start adding more detailed physics to their simulations. There are two main approaches: smoothed-particle hydrodynamics and adaptive mesh refinement.

From this paper http://arxiv.org/abs/arXiv:0801.3092
Simulated star formation. This figure compares adaptive mesh refinement (left) with smoothed-particle hydrodynamics (right) for a much smaller simulation than the whole Universe. The results are similar but not identical. Figure from Commercon et al. 2008.

The first case, smoothed-particle hydrodynamics, does pretty much what it sounds like: individual particles, each representing thousands of stars or large chunks of empty space, are free to flow through a virtual Universe over time. The particles’ motions are governed by whatever laws of physics the box is told to use. The other case, adaptive mesh refinement, is sneakier: instead of tracking every virtual particle, the Universe-box is divided into chunks of different sizes depending on how much is happening in that area. A relatively empty region can be large and have low-resolution, because it doesn’t need much computing power, while a relatively full region that is busy forming galaxies and stars is small and has high-resolution.

But why all the caveats? Why not simulate every portion of a Universe-in-a-box down to the size scale of, say, a star or solar system? Wouldn’t that be more accurate than “smoothing” elements of the Universe into unwieldy virtual particles or “adapting” your box to different resolutions in different regions?

The problem is dynamic range. Important physical processes govern the Universe over an immense range of size scales, and even the most powerful supercomputers can’t handle that level of detail in a simulation. For instance, hydrogen fusion is our Sun’s source of power. Fusion takes place on size scales of about 10-10 meters. On the other extreme, galaxies tug on one another to shape the Universe on size scales around 1022 meters. That spans more than 30 orders of magnitude!

You can experience a miniature version of this problem for yourself. Recently, NASA organized a “Global Selfie” for Earth Day. The idea was for people all around the world to take a picture of themselves and post it using social media. The result is a massive 3.2 gigapixel mosaic that you can explore in a web browser.

Notice how your computer has to work really hard to load that mosaic, and zoom around it. It’s hard work to go from fully zoomed-out to a clear view of over 35,000 individual images. And this is a mere 5 orders of magnitude.

Despite this hurdle, astronomers have made great leaps in simulating our Universe. For instance, the Illustris project uses a technique similar to adaptive mesh refinement to simulate an impressively realistic chunk of the Universe. Even so, the fact remains that the real Universe is far more intricate than our most powerful computers can imagine.

*At the largest scales, the mysterious force known as dark energy actually reigns.

A Thesis, Proposed

Graduate school is a bit of an odd beast. It’s not really college, it’s not quite a job, and it’s certainly not easy. In the US, getting a PhD in the sciences typically involves a couple years of classes, several exams, some work as a teaching assistant, and eventually a self-directed research project called a thesis. The whole shebang takes some 4-8 years on average. AstronoMerrdiff’s graduate school journey began in San Diego with a somewhat atypical MS-only program, and then wound its way to Las Cruces for a PhD. (The “normal” path is to earn a Master’s degree en route to the PhD at a single institution.) Finally, back in February, after years of related and not-so-related research, successfully completing a host of departmental prerequisites, and a hectic few days of last-minute changes, I stood in front of my department and outlined the project I will undertake for my thesis dissertation:

Red Giants in Eclipsing Binaries
as a Benchmark for Asteroseismology.

Any questions? …Well, since this is my primary purpose in life for the next while, I figure the least I can do is spend a few paragraphs explaining my own little corner of astronomy.

In a nutshell, I’m studying red giant stars that are in eclipsing binary systems. Many of the giant stars have sound wave oscillations going on inside that we observe as small changes in brightness (this is called asteroseismology, and tells us about a star’s interior which is otherwise impossible to see). But not all of the giant stars oscillate. I want to figure out why. The fact that these stars are in eclipsing binaries makes them relatively easy to physically model and characterize. We think the oscillations might be weaker or non-existent when there are lots of starspots or tidal forces, but we’re not sure.

Want more? Here is the talk I gave for the “Three Minute Thesis” Competition held recently at my university. While I didn’t win, I thought I did pretty well. My classmate Kyle Uckert took home first place for his outstanding talk about searching for microbial life on other worlds. I had a lot of fun, though, and I learned how challenging it is for me to give a talk without visual cues (like multiple slides) and a strict time limit.

My slide for the Three Minute Thesis Competition. Image credits: G Perez, IAC, SMM (left), NASA (right), J Orosz (right)

Have you heard about how we’ve found over 1000 planets orbiting distant stars?

The Kepler space telescope finds planets by staring at stars. When a planet passes in front of a star, we see less light. This technique lets us not only DETECT planets, but also characterize them. For instance, a big planet will block more light than a small one.

OK, so, planets are great, but that’s not what my thesis is about. I study stars! It turns out that Kepler is also incredibly useful when the situation is a little different: instead of a planet orbiting a star, you have two stars orbiting each other.

Just by observing how the brightness changes with time, we can learn a lot of things about these binary stars, such as how long it takes for them to go around once and how much hotter one is than the other.

But Kepler alone doesn’t give us the full picture. For that, I use a telescope right here in New Mexico, at Apache Point Observatory, which spreads out all the different colors of light into a rainbow. I watch characteristic dark areas move from red to blue and back again, which tells me the velocities of the stars as they orbit. I then use that information together with the data from Kepler to get sizes, masses, and other properties for both stars.

Now, let me step back for a moment and ask: why do we care? Well, stars are astronomers’ main tool. Unlike other sciences, we can’t interact with what we study. What we CAN do is carefully measure light. And virtually all of the light we see bouncing around the Universe started out deep inside a star. So wouldn’t it be nice if we could look deeper and study the interiors of stars?

As it turns out, many stars, including our Sun, have sound wave oscillations going on inside that we can observe as small changes in brightness. And just like earthquakes help us study the interior structure of the Earth, these STARquakes let us study the insides of stars. This is called asteroseismology.

Conveniently enough, some of the biggest stars oscillate slowly enough that our friend Kepler can see it. This includes Red Giants, the kind of star our Sun will become when it runs out of hydrogen fuel in a few billion years.

In fact, based on what we know about their insides, we think ALL Red Giant stars should have these starquakes. So, we were surprised when we found several Red Giants that DON’T.

The good news is, because these stars are in binaries, that makes them relatively easy to study. I’m looking at binary stars with Red Giants that DO oscillate, and comparing them to binary stars with Red Giants that DON’T. Along the way, I’m using the systems that DO oscillate as a way to check quantities like mass and size that we can get from both techniques.

My research uses observations of binary stars together with asteroseismology to learn how all stars live and evolve.

When Stars Explode

There’s a new supernova in the skies! Last week, students at the University of London Observatory discovered a strange bright spot in nearby galaxy Messier 82 (M82) during a routine observing training session. As undergraduate student Tom Wright put it, “One minute we’re eating pizza then five minutes later we’ve helped to discover a supernova. I couldn’t believe it.”

Words. Image credit UCL/University of London Observatory.
Two images of galaxy M82. The bottom one shows the location of the new supernova, dubbed SN 2014J. The overall galaxy appears dimmer in the bottom picture because the exposure time was shorter, so less light had time to reach the camera. Image from UCL/University of London Observatory.

What’s the big deal about a supernova? Well, to start with, all the elements in the Universe were formed deep inside stars, and spewed out into space through supernova explosions like this one. Take a moment to let that sink in.

This supernova is a special variety called “Type Ia” (type one-A). This means it is caused by a very dense white dwarf star collecting more mass than it can support and eventually going BOOM! We know this because we see signatures of telltale elements like Silicon in the spectrum of the explosion.

Type Ia supernovae are particularly useful because they are all physically very similar—white dwarf stars can only handle so much mass before they explode—so they are all roughly the same brightness. Astronomers love things that are all the same brightness, because they let us determine distances. How? Let’s pretend you’re staring into a huge, dark, empty room containing nothing but a handful of 100-Watt light bulbs. (Not a bad analogy for an astronomer’s life, really…) You’d like to know how far away the light bulbs are, but you don’t have a measuring tape, plus the room is really big. However, you know how much light each bulb is putting out (100 Watts), so you can figure out the ones that look dimmer are actually farther away. We call the 100-Watt light bulbs of the Universe, such as Type Ia supernovae, “standard candles” because they let us determine distance like this.

If you live in the Northern hemisphere and have access to good binoculars or a telescope, you can try seeing SN 2014J for yourself! It is close to peak brightness, and should be visible for another couple of weeks—the blink of an eye from an astronomical perspective.

Look for galaxy M82 with binoculars or a telescope near the dipper portion of the Big Dipper in Northern hemisphere skies. Image from Universe Today.

Even if you can’t spot the supernova in M82, the galaxy itself and neighboring galaxy M81 are a lovely sight. They’re also a great example of how light can be deceiving. The image below shows two images of these galaxies: one taken with visible light (inverted so the galaxies appear dark on a light background), and one taken with radio light. There is all kinds of gas and material connecting the galaxies together that you can’t see with your eye!

Two views of galaxies M81 (the larger one) and M82 (the smaller one above it). These pictures show the same region of space in two different flavors of light. The galaxies appear as two isolated collections of stars in visible light (left), while the multicolor radio image (right) shows gas connecting the galaxies. Observations like these are used to figure out how galaxies have interacted gravitationally in the past. Image from the SEDS Messier Catalog.

What I find particularly mind-boggling is how a galaxy some 12 million light years distant is “nearby” on a cosmic scale. Because light doesn’t travel instantaneously, we are seeing this supernova as it happened 12 million years ago. In contrast, every star in the night sky is located in our own Milky Way galaxy, which is about 100,000 light years across, so the light from these stars (and the planets orbiting them!) is “only” delayed by hundreds or thousands of years, not millions. If the planets in our Solar System are our next-door neighbors, and stars in our galaxy with their own planets are other cities, then M82 is an entirely different country.

I can’t help but wonder… is some alien civilization in our galaxy witnessing this distant explosion just as we are, at this very moment? Are intelligent creatures on a planet we have recently discovered also turning their telescopes to the heavens to study this supernova and learn more about the Universe we share?

Repurposing Kepler

One of my favorite telescopes has to be Kepler. Kepler has been orbiting the Sun, much like Earth does, since its launch in 2009. Its primary mission was to discover Earth-like planets orbiting other stars, called exoplanets. And since its launch in 2009, Kepler spent some four years staring at one region of the sky, unblinking, carefully monitoring how thousands of stars’ brightnesses change with time, with insane precision.

Kepler finds planets orbiting other stars using a technique called the transit method. That’s really just a fancy way of saying, “if a dark thing passes in front of a bright thing, we see less light.” Consider planet = “dark thing” and star = “bright thing”… and that’s it! Kepler isn’t fancy; rather, it takes a simple idea and milks it for all it’s worth. Bigger planet? More starlight blocked. Slow-moving planet? Starlight blocked for longer.

Artist's impression of the Kepler Space Telescope. An example of the transit method Kepler uses to detect planets is in the upper left corner. Note, however, that Kepler can't actually take a picture like this - it just records how a star's brightness seems to change over time. Image from http://www.stsci.edu.
Artist’s impression of the Kepler Space Telescope. An example of the transit method Kepler uses to detect planets is in the upper left corner. Note, however, that Kepler can’t actually take a picture like this – it just records how a star’s brightness seems to change over time. Image from http://www.stsci.edu.

While exoplanets are Kepler’s specialty (and it has found hundreds!), Kepler has somewhat unintentionally revolutionized stellar astrophysics, too. Planets getting in the way isn’t the only thing that can make a star’s brightness change. Scientists studying exoplanets have to deal with many other brightness-changing effects to properly characterize the planets they discover. As we say, though, one astronomer’s noise is another’s data: the “annoyance” of seeing so many rotating stars, pulsating stars, spotted stars, and even stars orbiting other stars, is my personal favorite of Kepler’s many successes.

Unfortunately, a critical part of Kepler broke recently, and there is no way to fix it. One of Kepler’s specialties is pointing ever-so-carefully at one part of the sky. To accomplish this, it needs a good sense of balance in three dimensions. This was provided by a set of “reaction wheels,” which are basically gyroscopes that spin to keep Kepler oriented in the right direction. Three dimensions of space means you need three wheels. Kepler actually has four, so one is redundant – we intentionally built Kepler with an extra reaction wheel in case one broke. As luck would have it, one stopped working shortly after launch. “No problem!” said scientists back on Earth. “We still have three wheels!” Or rather, we did. Until last spring, when a second one bit the dust.

And that is the sad story of how NASA wound up with a crippled telescope that can no longer search for Earth-like planets.

Thankfully, though, Kepler’s story doesn’t end there.

After a series of thorough tests to be sure two wheels really were broken, the folks at NASA put out a call to astronomers everywhere. They provided technical details about Kepler’s capabilities and limitations, and asked, “What should we do with Kepler now?”

More than 40 proposals flooded in to answer that question. See them here.

Most of these are full-fledged papers, representing hours of work for each author (and most of them have many, many authors!). Teams of astronomers from all over the world collaborated to come up with countless ideas for putting Kepler back to work. From those ideas, they fleshed out the most promising ones, and did extensive research to present science goals that are both realistic given Kepler’s current state and important to advance astronomy.

Just to put this in perspective: hundreds of astronomers spent countless hours to come up with creative, robust ideas for a telescope that doesn’t work properly anymore. Nobody paid them to write these proposals. Realistically, only one from a multitude of ideas will be able to happen, because we only have one Kepler. And it is broken!

I can’t help but imagine the science astronomers could accomplish if we had access to multiple, UN-broken space telescopes like Kepler. Even so, it is heartening to know that Kepler will have some scientific purpose, going forward. Long live Kepler!

Buckets of Starlight

Have you ever watched rain fall on the pavement? It makes a beautiful, seemingly random pattern. No drop is more or less likely to fall in a spot where another drop has fallen.

Let’s say you wanted to collect as much water as possible during a 30-minute rainfall. What kind of bucket would you make? Tall, short… wide, narrow… orange, green… hot, cold… raised above the ground, in a hole… what would you do?

This is the exact situation astronomers face when designing telescopes. Only instead of rain, we are trying to collect drops of light – called photons. And instead of setting a bucket in a rainstorm, we put a mirror in a dark location and hope for clear skies.

If you took a minute to think about it, you probably settled on using as big of a bucket as possible to collect the most rain. The width of the bucket, or its area on the ground, is more important than its depth, so long as it isn’t going to overflow. And the color, temperature, and height above the ground don’t really matter. This is exactly why astronomers are partial to huge telescopes! The most important part of a telescope is its primary mirror, which is like a bucket for light. Giant mirrors don’t really give us a more “zoomed in” view of the cosmos, but they do let us collect more light – just like a big bucket will collect more rain. Photons of light are always raining down from the cosmos. Bigger mirrors mean more photons, and more photons means fainter stars and galaxies are visible.

Four telescopes, each with an 8.2 m diameter mirror, that together compose the aptly-named Very Large Telescope (VLT). Image credit: Wikipedia via ESO.
The aptly-named Very Large Telescope (VLT) comprises four telescopes, each with an 8.2 m diameter mirror. Image credit: Wikipedia via ESO.

There is another way to get even more rain, or photons, too, of course: leave your bucket out for more than 30 minutes. Maybe even leave it out for hours on end, and carefully set aside all the water – or light – you collect until you can add it all up later. The faintest, most distant galaxies are only visible to those with a big light-bucket and a lot of patience.

The Hubble eXtreme Deep Field. Nearly every object here is a galaxy, containing billions of stars. Hubble spent over 20 days total staring at a tiny patch of sky with its relatively modest 2.4 m diameter mirror to create this image.
The Hubble eXtreme Deep Field. Nearly every object here is a galaxy, and each galaxy contains billions of stars. Hubble spent a total of over 20 days staring at a tiny patch of sky with its relatively modest 2.4 m diameter mirror to create this image.
Image credit: NASA, ESA, et al.

As it turns out, falling rain and incoming photons can both be described by a special set of mathematical rules called Poisson statistics. Each drop hits the ground in a random spot. But the sum total of all of these random events is predictable. So, If you make a graph of raindrops hitting a bucket, or photons hitting a telescope mirror, you get a special shape: a Poisson distribution.

Astronomers use this to know how long we need to stare at a distant star or galaxy, or how big a telescope we need to use. Poisson statistics tells us that the quality of telescope data for a star emitting N photons will be 1/√N. (We like to say the uncertainty, or “standard deviation,” is √N.) This is great news! If you spend some time looking at a star and collect 100 photons, your uncertainty will be 10 photons, which is 10% of 100. That’s not very precise. But if you stare at it longer – or trade up to a bigger telescope – and collect 1000 photons, the uncertainty will be about 32 photons, which is only 3%. Much better.

Image credit: wellhappypeaceful.com
Image credit: wellhappypeaceful.com

The next time you look up at the night sky, remember that your eyes are miniature telescopes. Or perhaps fun-sized light-buckets. How much starlight can you collect?

Giants of Eclipse Wrapup

Interferometry, asteroseismology, heartbeats, tomography… oh my!

The rest of the Giants of Eclipse meeting saw a much wider array of subjects than just Epsilon Aurigae. We heard about interferometry, a special technique often used by radio telescopes to get sharper, higher-resolution pictures. Daniel Huber gave a great overview of asteroseismology, or stellar pulsations, which related to my talk the next day. Andrej Prsa discussed lots of work being done by the Kepler team with eclipsing binaries. The Kepler spacecraft is one of my favorites – it spent over three years collecting extremely precise data to search for planets around other stars. (Unfortunately it recently stopped working, and prospects of getting it up and running again are slim, but there is still tons of data to pore over.) A great benefit of all the high-precision Kepler data isn’t just planet hunting – it’s also extremely useful to study stars. We heard about a special kind of binary star that shows a “heartbeat-like” pattern in its light curve, and we also learned about an innovative technique called tomography, which essentially creates a 3D map from a series of 2D slices.

Brightness versus Time for a so-called "heartbeat star." The black dots are the observations from Kepler, and each line is a different model. The brightness changes because the two stars pass very close to one another as they orbit and their shapes are briefly distorted. Figure from Beck et al. 2013.
Brightness versus Time for a so-called “heartbeat star.” The black dots are the observations from Kepler, and each line is a different model. The brightness changes because the two stars pass very close to one another as they orbit and their shapes are briefly distorted. Figure from Beck et al. 2013.

So much science! By the time I presented my research on Thursday afternoon, everyone was probably tired of listening to talk after talk after talk. But I was pleased that I didn’t go over my time, got a couple of chuckles, and was able to answer questions intelligently. Next time I give a talk at a conference, I hope I don’t have to go last, because I spent a lot of time worrying about my own presentation instead of listening intently to others’.

Overall, I was thrilled to meet so many other people who care about binary stars at least as much as I do. We shared many great meals and fun evenings. I left Monterey with new friends and a better sense of what cool research is happening with binary stars.

Giants of Eclipse, Day 2

What happened to Day 1, you may ask? Unfortunately, a canceled flight happened. To make a long story short, AstronoMerrdiff finally maxed out her travel karma and got to spend an extra day in San Diego. It worked out okay, though – I worked on my talk for Thursday, and had a great impromptu meeting with my old advisor at San Diego State.

By arriving at the conference in Monterey some 24 hours later than intended, I missed a couple of overview talks, a session on VV Cep stars (a special kind of eclipsing binary), and a particularly interesting-sounding theory session. This apparently featured red giant atmosphere modeling, red giants in eclipsing binaries (!), and working out how triple systems (three stars orbiting one another) may have formed.

Let me back up a step…

This conference is all about big stars that orbit other stars so that one routinely passes in front of the other. That’s why it’s called GIANTS of ECLIPSE! It also happens to be precisely what I’m working on right now. In particular, I’m working on a project that involves red giants in eclipsing binaries. A red giant is a huge, bright red star that has run out of hydrogen fuel. Our Sun will become a red giant near the end of its life. An eclipsing binary is a pair of stars orbiting each other that pass in front of one another as viewed from Earth. As it turns out, the talk I missed yesterday about red giant eclipsing binaries was originally scheduled for Wednesday, and got moved at the last minute. Neither the speaker nor I knew this until we each arrived.

A recurring theme at the conference so far has been “this person was going to come and give a talk, but wasn’t able to.” There have been at least four cases of this, and there are fewer than 40 people at the conference to begin with. Sometimes an absent presenter is able to Skype in and/or pre-record a talk to be played back. In other cases, they ask a colleague at the meeting to give their talk for them. And in many situations, the talk is simply withdrawn. These cancellations and substitutions are what led to schedule shuffling. Why this all has to be so last-minute and offline is beyond me.

So, this brings us to today. Today’s theme was Epsilon Aurigae (usually pronounced or-EYE-jee, with “jee” sounding like “jeans”). This funny name belongs to a particularly mysterious eclipsing system. As best we can tell, Epsilon Aurigae is a cooler F-type star and a hotter B-type star orbiting each other, with a critical twist – the hotter star is embedded in a dark, dusty disk. Epsilon Aurigae is a particularly hot topic right now among stellar astronomers because it just completed an eclipse: the dark disk hiding a hot star inside just finished passing in front of the cool star. This only happens every 27 years, so lots of people were excited to observe it and begin to understand it.

Artist's impression of Epsilon Aurigae.
Artist’s impression of Epsilon Aurigae.
Image from http://en.wikipedia.org/wiki/Epsilon_Aurigae.

The best part of a small conference like this, however, is meeting people whose names you know from papers – in person. The under-40 group is rather under-represented at Giants of Eclipse, which is unsurprising given budget woes. (Grad students and postdocs are generally hit hardest when it comes to travel funding. In my case, I’m only here because I could afford to pay out-of-pocket, and that simply isn’t possible for most early-career astronomers.) So: the few of us young folks automatically meet and shake our heads as some of the more senior astronomers use overhead projector sheets (yes, really).

Thankfully, it isn’t all slide rules – there is lots of great science being done. I’m looking forward to the next couple of days, where the talks will venture further afield than just Epsilon Aurigae. Giants and binaries and eclipses, oh my!