Rubin Observatory sends thousands of data alerts with the help of Seattle astronomers
An astronomical warning system developed at the University of Washington got off to a flying start this week, sending out 800,000 alerts about moving asteroids, exploding stars and other celestial changes detected by the Vera C. Rubin Observatory in Chile.
Tuesday night’s outbreak was the first wave of alerts. Ultimately, the Alert Production Pipeline is expected to generate up to 7 million alerts per night. Astronomers around the world will use the system to sift through the data, focusing on events from newly discovered asteroids to supernovas, variable stars and active galactic nuclei.
“Rubin’s alert system was designed to allow anyone to spot interesting astronomical events with enough notice to quickly receive important follow-up observations in a timely manner,” said Eric Bellm, a UW astronomer who leads the Alert Production Pipeline Group for the Rubin Observatory, said today in a news release. “Rubin will explore the sky at an unprecedented scale and allow us to discover rare and unusual objects in the universe.
The $800 million lab, jointly funded by the National Science Foundation and the US Department of Energy’s Office of Science, had its grand opening last June. It is now ascending to begin the 10-year Legacy Survey of space and time. Each night, the center’s Simonyi Survey Telescope — named for the family of Seattle-area software billionaire Charles Simonyi, who provided $20 million in seed funding — will image the Southern Hemisphere sky, generating up to 20 terabytes of data a night.
Processing billions of bytes of raw data is no easy task. For the past decade, the University of Washington’s Institute for Data Intensive Research in Astrophysics and Cosmology, also known as the DIRAC Institute, has been working with other teams across the country to find a way to manage the area’s astronomical wealth.
“Enabling real-time acquisition of such massive data streams requires years of technological innovation in image processing algorithms, databases and data orchestration,” Bellm said. “We are thrilled to continue the UW’s legacy of excellence in data-driven science.”
Rubin’s data processing system is designed to compare pixels in new images with previous images of a patch of sky. Each change in the image – for example, a change in the position of a moving asteroid, or a change in the brightness of a supernova – triggers an alert within two minutes of capturing the image.
“The scale and speed of the notifications is unprecedented,” said Hsin-Fang Chiang, who leads data processing operations at SLAC National Accelerator Laboratory’s US Data Facility. “After generating hundreds of thousands of test notifications over the past few months, we now know, within minutes, with each image, ‘here’s everything’ and ‘go.’ “
Software agents known as vendors use machine learning algorithms to filter alerts for research and industry teams. Official buyers of Rubin data include ALERCE, AMPEL, ANTARES, Babamul, Fink, Lasair, Pitt-Google, SNAPS, and POI Broker. Using these tools, astronomers can set hyper-specific criteria — for example, to display alerts for events brighter than magnitude 21, detected less than six days ago, and associated with two previous detections.
Thanks to the warning system, other observatories will be able to track Rubin’s data and confirm the discovery of stars. And by partnering with citizen science programs like Zooniverse, anyone with access to a computer will be able to join in too.
