Sensors for the world’s largest digital camera have snapped their first 3,200-megapixel images at SLAC. Crews at the SLAC National Accelerator Laboratory took the photo with an extraordinary array of imaging sensors that will become the heart and soul of the future camera of Vera C. Rubin Observatory.
When the Large Synoptic Survey Telescope high in the Chilean Andes becomes fully operational in 2022, its 3.2-gigapixel camera will collect the same amount of data — every night. And it will do so over and over again for ten years. The sky survey will collect so much data that data scientists needed to figure out new ways for astronomers to access it.
Scientists at SLAC National Accelerator Laboratory are building the world’s largest digital camera for astronomy and astrophysics — a minivan-sized 3200-megapixel “eye” of the future Large Synoptic Survey Telescope that will see light in 2022. In the meantime, the lab has completed its work on a miniature version that will soon be used for testing the telescope and taking LSST’s first images of the night sky. ComCam will help test the observatory once it is installed in Chile later this year.
In a brightly lit clean room at SLAC National Accelerator Laboratory, engineers are building a car-sized digital camera for the Large Synoptic Survey Telescope. When it’s ready, LSST will image almost all of the sky visible from its vantage point on a Chilean mountain, Cerro Pachón, every few nights for a decade to make an astronomical movie of unprecedented proportions. Building the LSST means solving extraordinary technological challenges.
The Large Synoptic Survey Telescope will manage unprecedented volumes of data produced each night. Scheduled to come online in the early 2020s, the LSST will use a 3.2-gigapixel camera to photograph a giant swath of the heavens. It’ll keep it up for 10 years, every night with a clear sky, creating the world’s largest astronomical stop-motion movie.
A new telescope will take a sequence of snapshots with the world’s largest digital camera, covering the entire visible night sky every few days — and repeating the process for an entire decade. What’s the best way to rapidly and automatically identify and categorize all of the stars, galaxies and other objects captured in these images? Data scientists trained have computers to pick out useful information from these hi-res snapshots of the universe.