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The U.S. National Science Foundation (NSF) and the U.S. Department of Energy (DOE) Office of Science will support Rubin Observatory in its operations phase to carry out the Legacy Survey of Space and Time. They will also provide support for scientific research with the data. During operations, NSF funding is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with NSF, and DOE funding is managed by SLAC National Accelerator Laboratory (SLAC), under contract by DOE. Rubin Observatory is operated by NSF NOIRLab and SLAC.

NSF is an independent federal agency created by Congress in 1950 to promote the progress of science. NSF supports basic research and people to create knowledge that transforms the future.

The DOE Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.

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    1. Explore
    2. Rubin Basics
    3. Alert Brokers


    Media

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    "Postage stamp" images of different types of Rubin alerts, classified by the alert brokers
    "Postage stamp" images of different types of Rubin alerts, classified by the alert brokers

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    Alert Brokers

    Rubin’s alert stream is massive, but Rubin’s alert brokers make it manageable for scientists.

    Rubin Observatory is starting to flood astronomers with new activity in the sky. Ultimately Rubin will detect up to about seven million changes in the sky every night: exploding stars, moving asteroids, flickering black holes, and countless other cosmic happenings. With that many alerts pouring in, how do scientists find the discoveries they actually care about?

    Behind the scenes, Rubin’s alert brokers work like cosmic news editors, turning the flood of alerts into something scientists can practically use.

    First, brokers compare each alert against catalogs of already known objects, like stars, galaxies, and asteroids. Then machine learning systems analyze the source of the alert itself: How bright is it? Is it getting brighter or fading? Is it near a galaxy? Is it moving? Using patterns learned from millions of past observations, brokers can predict whether the alert is likely a supernova, an asteroid, a variable star, or something more unusual.

    "Postage stamp" images of different types of Rubin alerts, classified by the alert brokers

    Finally, brokers pass the alerts through filters so scientists can choose which ones to view on a broker’s web portal or receive in a customized stream. A scientist searching for exploding stars can filter for alerts likely associated with supernovae, while another studying black holes might look only at unusual galactic flares. Instead of trying to sift through millions of alerts themselves (an impossible task!), researchers get a curated view of the events most relevant to their work.

    Speed also matters. Some cosmic events fade within hours or days, which is why machine learning and automation are essential to the brokers’ work. These automated software systems can identify interesting alerts and trigger follow-up observations by other telescopes much faster than a human could notice and respond (in this video, a sample Rubin alert triggers follow-up observations in just 12 minutes). In some cases, machine learning systems can even flag strange objects that don’t fit any known category — the kinds of odd discoveries that could end up revealing something entirely new.

    Further exploration:

    • Visit our alerts and brokers web page for a list of Rubin’s brokers with links to their websites — where you can explore alerts too!

    • Learn more about the alert stream in this Rubin Basics entry

    • See samples of real alerts in our Gallery

    • Watch a video that shows how quickly Rubin alert follow-up observations can happen