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12-05-2020, 02:22 PM
Best map of Milky Way reveals a billion stars in motion
Davide Castelvicchi | Nature News, 3 December 2020
Data haul from Gaia space observatory offers a glimpse of what Earth’s night sky will look like for 1.6 million years to come.
https://www.youtube.com/watch?v=hNGC8qDEntM&feature=emb_logo
The best available map of the Milky Way just got better. The latest update from the Gaia space observatory — which is tracking more than 1 billion stars in the Galaxy — provides not just a static image but a picture of how stars will move over time. The data will underpin studies that range from the origins and evolution of the Galaxy to locating its dark matter.
“I am yet to see another project in astronomy — or any science — that has had such an impact on such a short timescale,” says Amina Helmi, an astronomer at the University of Groningen in the Netherlands. “My group is ready to go and very excited to find out what is there to discover and learn about the Milky Way.” Using data that Gaia released in 2018, Helmi and her collaborators have studied the motions of large numbers of stars to reveal evidence of galactic mergers that happened billions of years in the past.
Gaia lifted off in late 2013, and began observing stars in July 2014 from a perch 1.5 million kilometres from Earth. The European Space Agency (ESA) probe continuously scans the sky as it slowly spins on itself, and it has now measured the positions of the same stars multiple times. This enables scientists to track stars’ nearly imperceptible motions across the Galaxy year after year. As Gaia orbits the Sun, its changing perspective also makes the stars’ apparent position change by tiny amounts — typically by an angle of millionths of a degree. These offsets can be used to calculate their distance from our Solar System using a technique called parallax.
The type of information Gaia provides is the bread and butter of the field. Without a reliable distance measurement, in particular, it can be difficult to guess a star’s size, age and brightness, and therefore to model its structure and evolution.
Davide Castelvicchi | Nature News, 3 December 2020
Data haul from Gaia space observatory offers a glimpse of what Earth’s night sky will look like for 1.6 million years to come.
https://www.youtube.com/watch?v=hNGC8qDEntM&feature=emb_logo
The best available map of the Milky Way just got better. The latest update from the Gaia space observatory — which is tracking more than 1 billion stars in the Galaxy — provides not just a static image but a picture of how stars will move over time. The data will underpin studies that range from the origins and evolution of the Galaxy to locating its dark matter.
“I am yet to see another project in astronomy — or any science — that has had such an impact on such a short timescale,” says Amina Helmi, an astronomer at the University of Groningen in the Netherlands. “My group is ready to go and very excited to find out what is there to discover and learn about the Milky Way.” Using data that Gaia released in 2018, Helmi and her collaborators have studied the motions of large numbers of stars to reveal evidence of galactic mergers that happened billions of years in the past.
Gaia lifted off in late 2013, and began observing stars in July 2014 from a perch 1.5 million kilometres from Earth. The European Space Agency (ESA) probe continuously scans the sky as it slowly spins on itself, and it has now measured the positions of the same stars multiple times. This enables scientists to track stars’ nearly imperceptible motions across the Galaxy year after year. As Gaia orbits the Sun, its changing perspective also makes the stars’ apparent position change by tiny amounts — typically by an angle of millionths of a degree. These offsets can be used to calculate their distance from our Solar System using a technique called parallax.
The type of information Gaia provides is the bread and butter of the field. Without a reliable distance measurement, in particular, it can be difficult to guess a star’s size, age and brightness, and therefore to model its structure and evolution.
