Tag Archive | stellar variability

Hot Friends of Hot Jupiters: The WASP-47 system

Ever since a mechanical failure caused the end of the original Kepler mission in 2013, the Kepler spacecraft has been conducting a survey of new stars, searching for planets across the ecliptic plane in its new K2 mission (https://blog.planethunters.org/2014/12/12/more-about-the-k2-campaign-0/). The K2 dataset is a goldmine of fascinating science results. One such result is the recent discovery of two new planets in the WASP-47 system.

Until a few months ago, everyone knew that hot Jupiter planets don’t have “friends”, or nearby small planets in close orbits to the host star. These other planets had been searched for extensively, through radial velocity measurements, analysis of the transit times of the hot Jupiters, and even through transits by Kepler during its original mission. All of these searches turned up nothing.

This all changed one day last July, when Hans Martin Schwengeler, a Planet Hunter who enjoys poring over Kepler and K2 data searching for new transiting planets by eye, came across the telltale signatures of two extra transiting planets in the hot Jupiter system WASP-47. WASP 47b was, by all indications, a perfectly normal hot Jupiter — in the discovery paper, Coel Hellier wrote “With an orbital period of 4.16 days, a mass of 1.14 Jupiter masses, and a radius of 1.15 Jupiter radii, WASP-47b is an entirely typical hot Jupiter”. The discovery of additional transiting planets dramatically changed the narrative.

When Hans came across the planets, he posted them to the Planet Hunters forum, where he and other citizen scientists discuss their findings. Andrew Vanderburg came across the post suggesting that a known hot Jupiter had planetary companions. Using his K2 data reduction pipeline (https://blog.planethunters.org/2015/01/08/a-recipe-for-making-a-k2-light-curve/), he analyzed the light curve and confirmed Hans’s discovery – there were additional planets in the system, a super-Earth at a 0.8 day period and a Neptune at a 9 day period!

Andrew emailed me, and at first I hardly believed that the lightcurve was real. How could a hot Jupiter have close-in planetary companions? I knew people had been looking for this type of companion for years via both photometry and transit timing variations, but the lack of discoveries indicated that they might not exist. I performed some numerical stability simulations (because it seemed at first like this system could not be dynamically stable!) and sure enough, the N-body simulations showed that the system was likely stable on timescales of 10 million years.

At that point, we formed a team with Hans, Andrew, MIT Professor Saul Rappaport, University of Michigan Professor Fred Adams (my advisor!), and me. Once this team was formed, we devoted ourselves to understanding as much about the systems as we could. Some work by Saul and Andrew confirmed that the planets were all orbiting the same star, Andrew fit the lightcurve to get the planet properties, and I ran more stability simulations. Soon enough, Fred suggested that I look at what transit timing variations (or TTVs, which happen when transits come late or early because of the gravity of other planets in the system) we would theoretically expect to see from the system – and I found that for the outer two planets, the TTVs should be observable.

I then measured the TTVs from the lightcurve, and sure enough – there was something there. After some discussion, we realized we could measure the masses of the planets from those TTVs! Though I had never done dynamical fits before, I wrote the code to utilize Kat Deck’s TTVFAST code in a Markov Chain Monte Carlo fit. With some advice from Kat and help from Fred, I eventually got the fits working and we were able to measure or put limits on the masses of each planet.

In a little less than two weeks, we had put together a paper deriving planet properties from the lightcurve, mass limits from the TTVs, and showing that you CAN detect companions to hot Jupiters using TTVs!

This result is exciting because it is the very first time a hot Jupiter has been found to have such close-in other planets. Before this discovery, it was unclear if hot Jupiter could have nearby friends, as they might destabilize the friends’ orbits during migration. This discovery opens up new questions about how these systems form – it is possible that there is more than one migration mechanism for hot Jupiters.

The paper on WASP-47 and its new companions, which was published earlier this week in ApJ Letters and is available at http://arxiv.org/abs/1508.02411, was a collaboration between myself (Juliette Becker, a graduate student at the University of Michigan), graduate student Andrew Vanderburg (Harvard CfA), Professor Fred Adams (the University of Michigan), Professor Saul Rappaport (MIT), and Hans Schwengeler (a citizen scientist).



Variable stars (examples)

The reasons for changes in the brightness of a star can be divided into two categories: (1) orbiting companions or (2) stellar astrophysics.

(1) In principle, the variability from orbiting companions (this includes eclipsing binaries or transiting planets) should be as regular as clockwork.  In practice, the variability can deviate from clockwork regularity if stellar binaries get too close together, if there are multiple transiting planets, if there is additional background electronic noise or astrophysical noise.

(2) Brightness variations caused by physical processes internal to the star (stellar astrophysics) can arise from pulsations of the star, starspots or flares. Flares are random spikes in the light curve brightness.  Pulsations from stars (like RR Lyraes) are quasi-periodic: they can appear to be regular for a while and the cycles are relatively short (generally hours to a day or so). The Figure below shows two variable stars with short periods that might be best classified as “variable” and “pulsating.” These could be short period binary systems – this could quickly be verified with follow-up observations.

puls1 puls2

Starspots produce complex variations. As the star spins, the spots rotate in and out of view with a   periodicity of a day or two (for the most rapidly spinning stars) to several days for slowly rotating stars (the Sun has a rotation period of 25 days).  Starspots can form at different latitudes on the star.  Since some latitudes rotate faster, spots can show multi-cyclical variations. The light curves below might be best classified as variable and irregular.  However, a case could be made for classifying the light curve in the figure below (and left) as variable and regular. Even though the amplitude of the curves changes, the time from one peak to the next is about the same.



Quiet Stars (examples)

Thanks very much for your help with this project. At last count, roughly 50,000 light curves had been sorted at planethunters.org. Many of you have requested more examples about how to classify stellar variability, so we’ll start with the easiest case.  All of the light curves below are examples of quiet stars.  Random variations in brightness occur because of photon noise (similar to shot noise in electronics). The number of photons that are collected are small enough that there random fluctuations that have nothing to do with the actual brightness of the star. Photon noise (or Poisson noise) produces scatter, but the data remain in a nearly featureless band of points.



If you look closely at the light curve data for these quiet stars, you will see light gray error bars associated with each data point.  In any physical measurement, the error bar simply captures our ignorance about the true value of the measurement. In the Kepler light curves, the brightness is represented as a discrete dot, however, any and all points along an error bar are equally correct values for that particular brightness measurement.

In the quiet light curves above, should any of those low points be flagged as possible transits?  Probably not.  A deviant point or two can still just be noise. A true transit event should have a series of low brightness points that last for the time it takes the planet to cross in front of its stars (i.e., a few to several hours, represented by a few to several data points).  Low dips that repeat are also good indicators of a transit, however some of the most exciting transits (from planets in wider, more habitable orbits) will only occur once per month (for example, a true analog of our Earth would just transit once per year).

The quiet light curves above may seem like duds, but they are an extremely important aspect of research for this project. Stars that do not vary in brightness are particularly important objects for exoplanet searches with other techniques.  The work that you’re doing will feed into our understanding for the next generation instruments and space missions that could be built to detect planets.

Happy Holidays to All!  Debra Fischer

Stellar Variability

Greetings from Kevin Schawinski and Meg Schwamb, postdoctoral fellows at Yale and members of the Science Team.

Wow, we’ve been blown away by how enthusiastic everyone has been about the project. In this post, we wanted to talk more about another goal of Planet Hunters, which is to study and better understand stellar variability.  The public release Kepler data set is unprecedented, both in observing cadence and in the photometric precision. The lightcurves reveal subtle variability that has never before been documented.

The Kepler lightcurves are complex  many exhibiting significant structure including multiple oscillations imposed on top of each other as well as short-lived variations. Most of this variability is due by starspots or stellar pulsations.With Planet Hunters we will not only be looking for stars harboring planets outside of our solar system, but we will be able to study and classify stellar variability in ways that automated routines cannot. Unlike a machine learning approach, human classifiers recognize the unusual and have a remarkable ability to recognize archetypes and assemble groups of similar objects.

Users have the ability to identify strange or unusual lightcurves as well as tag similar curves and come up with their own classes or  ”collections”  of variability with  Planet Hunters Talk. You can add a comment and  use the #hashtag like in Twitter to mark an interesting lightcurve and alert others including the science team. Every light curve, or collection of curves has a short-message thread (140 characters) associated with it for general comments. You also can start discussions if you want to chat in a more in-depth fashion.

Mining the Kepler data set will inevitably lead to unexpected discoveries, showcased by the successes of Galaxy Zoo. The prime examples are the discoveries of  ”Hanny’s Voorwerp” and the ”green peas” by Galaxy Zoo users. Hanny’s Voorwerp is a cloud of ionized gas in the Sloan Digital Sky Survey image of the nearby galaxy IC 2497. Unlike an automatic classification routine, citizen scientist Hanny van Arkel spotted a blue smudge next to IC 2497, recognized it as unusual, and alerted the Galaxy Zoo team and the other users. Since then, Hanny’s Voorwerp has been identified as a light echo from a recent quasar phase in IC 2497, making it the Rosetta Stone of quasars. The Galaxy Zoo participants started noticing a very rare class of objects of point sources showed as green in the SDSS color scheme. Dubbing them the ”green peas,” the citizen scientists scoured the SDSS database, and assembled a list of these ”pea galaxies.”  The ”peas” were revealed to be ultra-compact, powerful starburst galaxies whose properties are highly unusual in the present day universe, but resemble those of primordial galaxies in the early universe. The citizen scientists found veritable fossils living in the present-day universe.

With so many eyes looking at the lightcurves, we are bound to find new variability types! We’re hoping that Planet Hunters, like Galaxy Zoo, will yield exciting new results that we can’t even attempt to speculate or imagine! We can’t wait to see what turns up.