Three weeks before Christmas, astronomers are opening one of their presents early. Inside is a most welcome gift—a vast catalog of more than a billion stars in and around our galaxy, the most advanced of its kind ever made. Already this new trove is being put to use, with eager astronomers poring through its data, hoping to unlock some of our galaxy’s most intriguing secrets in a way never before possible.
This gift comes from the European Space Agency’s (ESA) $1 billion Gaia telescope, launched in 2013 on a decade-long mission to measure the motions, positions and other key properties of billions of stars in and around our galaxy. On Thursday, December 3, ESA released a new batch of survey data—known as the Gaia Early Data Release 3 (EDR3)—which contained updated information about a billion stars, including more refined calculations of their locations and velocities, vital tools for astronomers. “Distances to stars are about 30 percent more precise, and proper motions have increased by a factor of two,” says Anthony Brown from the University of Leiden in the Netherlands, the lead on the Gaia data processing team. “That’s because we collected observations over 34 months, instead of 22 months for the previous release.”
Putting these refined calculations immediately to use were dozens of astronomers who gathered in a virtual “hackathon,” known as the Gaia Sprint, on Thursday. With Gaia’s previous data release, in 2018, these astronomers met in person in New York; this year, owing to COVID-19, a more remote meeting was required. Using the instant messaging platform Slack, combined with a digital conference room in the video-calling service Wonder, astronomers from around the world were able to mingle and discuss the data in real time as soon as it was publicly released. “We’re all [working] on the same data set on the same day, but we’re doing very different things,” says Jackie Faherty from the American Museum of Natural History, one of the event’s organizers. “It’s like a party of science.”
Among the participants was Łukasz Wyrzykowski from Warsaw University in Poland, who planned to use the data to look for signs of black holes as their gravitational pulls bent the light of more distant stars. In particular, he was looking for small, so-called “stellar mass” black holes roughly five to 10 times the weight of our sun. “We only know of a few dozens of such black holes,” he says. “So, we try to detect lensing effects. If the light is disturbed by the gravitational potential of the black hole, then you see the effect of the black hole itself.” Gaia provides a novel way to look for such effects on a huge scale. “Only Gaia can give us such precise measurements so that we can see the displacement of the background star” from such lensing effects, Wyrzykowski says. Chances are slim though, he notes; only one or two such events are expected from the two billion stars in the Gaia data, if any at all.
Elsewhere, Ana Bonaca from Yale University and Adrian Price-Whelan from the Flatiron Institute were using EDR3 to hunt for clumps of dark matter in our galaxy. Throughout the Milky Way can be found groups of stars appearing to move in an orderly queue, known as stellar streams. Using Gaia’s precise data, it should be possible to map out the motion of these streams and look for any regions that appear to be unusually dense or bereft. “We noted these stars should all be traveling together,” says Bonaca. “However, [in] a galaxy with a lot of dark matter clumps, the distribution [should] look kind of different.” This should result in over- and under-densities in the stream, hinting at the gravitational influence of clumps of dark matter hidden from our view. Already EDR3 was giving “much cleaner views of the streams,” says Price-Whelan, allowing possible clumps to be flagged more easily.
Kareem El-Badry from the University of California, Berkeley, meanwhile, was on the hunt for wide binaries—stars orbiting one another but separated by 10 to 100,000 times the Earth-sun distance. Earlier releases of Gaia data contained numerous data processing errors that made more distant stars appear closer, El-Badry says, which made identifying wide binaries difficult. But in EDR3, “so far it seems they’ve done a much better job of filtering out those bad sources,” he says. This should allow many more to be found, which could be useful for further calibrating Gaia’s data itself. The telescope has a small amount of uncertainty in the stellar distances it calculates, up to 20 percent for the most distant stars, which can cause problems for data analysis. But El-Badry says seeing wide binaries could help resolve that issue if the distances to two stars known to be orbiting each other can be independently measured and compared.
Much has also been made of Gaia’s potential ability to spot exoplanets orbiting around some of these stars using a technique called astrometry, which can tease out the presence of planets by the way they can make their host stars wobble back and forth in the plane of the sky. And while most discoveries of new exoplanets are not expected until the telescope’s fourth release of data four or five years from now, the full Data Release 3 in early 2022 could contain information on previously discovered exoplanets. “In 2022 hopefully some of the known exoplanets will have astrometric measurements, which gives us some real information on the masses of these exoplanets,” says Ronald Drimmel from the Turin Astrophysical Observatory and a Gaia team member. “We’re talking about the big exoplanets, the Jupiters going around other stars and seeing their influence on their host star, not small terrestrial exoplanets.”
Other research has also already been possible with EDR3. Drimmel has seen evidence for a previously hypothesized black hole in a stellar system, for example, thanks to the refinement of the Gaia data. And astronomers were able to measure the acceleration of our solar system towards the galactic center by measuring the distances to quasars, bright objects billions of light-years away, arriving at a figure of seven kilometers per second per million years. “It’s a ridiculously small number, but we were able to measure it with Gaia,” Brown says. And over the coming weeks, months and years, much more exciting science awaits. “Gaia data is like a tsunami rolling through astrophysics,” said Martin Barstow from the University of Leicester in the U.K., part of the Gaia team, in a virtual press conference on Thursday announcing the data. “It’s just transformational. Astronomy before and after Gaia will be unrecognizable.”