Calling all space cadets: Today, a group of researchers led by the Carnegie Institute of Science released an impressive database containing 61,000 so-called Doppler velocity measurements of 1,600 nearby stars. The team is graciously inviting you to use their data to find the next exoplanet. Go forth and become drunk with power.
The data behind the new catalog was collected from 1994 to 2008 by the High Resolution Echelle Spectrometer (HIRES), located at the W.M. Keck Observatory in Hawaii. HIRES takes a star’s incoming light and splits it into a rainbow of color channels, which allows scientists to learn more about its composition and radial velocity, or the speed at which the star is moving toward or away from an object (in this case, human observers on Earth).
Although the dataset wasn’t initially designed to look for exoplanets, MIT Torres postdoctoral research and team member Jennifer Burt said HIRES has proven itself to be an astute planet-hunter, through its furnishing of radial velocity data.
“HIRES was designed back in the late ‘80s and early ‘90s to go and look at these faint, fuzzy galaxies,” Burt told Gizmodo. “The professor who designed it—Steven Vogt, who’s on the planet hunting team—was one of my advisors in grad school. Steve went through when designing HIRES and included the machinery that you would need to turn it into an exoplanet machine.”
HIRES contains a gaseous iodine absorption cell, which the team uses to observe periodic shifts in the parent star’s light spectrum, called Doppler shifts. Such shifts are caused by slight changes in the star’s velocity, which scientists can use to deduce the gravitational tug of an exoplanet.
The team has found 100 exoplanets using the HIRES data, including one orbiting the fourth-closest star to our solar system, GJ 411. The researchers’ findings have been accepted for publication in The Astronomical Journal.
By giving the public access to the HIRES data, Burt and her team hope to bring in lots of fresh ideas—and eyeballs. Users simply install the team’s console, select a star they’d like to study, and manipulate a slider tool to increase or decrease the time window of stellar observations. If a user finds that their analysis is similar enough to the previously-recorded model measurements of “stellar jitter,” they’ve probably found a planet, and can report it here.
“The big thing is that at this point, we’ve got so much data on so many stars, it turns out that just getting the data isn’t quite enough,” Burt explained. “There’s a lot of follow up that needs to be done to rule out false positives. And the team in many ways just isn’t big enough—there aren’t enough of us to give the data the amount of attention it deserves.”
Even if a person never finds an exoplanet, they’ll learn about the process by which planets are found just by looking at the HIRES data and learning how to interpret it. For those interested, Yale professor Greg Laughlin has written a tutorial on how to do this, which is available on his website.
“It opens up a great chance to teach the public about searching for planets,” Burt said. “It also provides information to other exoplanet teams working at other large observatories, because to find planets that are either very small or [in] very long periods you need hundreds of data points.”
Basically, it’s the people’s data now and we’re all better for it, even if that ruffles a few academic elitists’ feathers.
“We’re trying to move toward a more community-focused aspect, where different teams can combine their resources and really take this science to the next level, instead of carefully hoarding and protecting their data,” Burt said.
So, just to make the snobs extra mad one more time, this data set means anyone can be an exoplanet hunter?
“Exactly,” Burt said. “That’s the idea.”