Rubin starts decade-long survey with 3,200-megapixel camera

In Chile, a camera roughly the size of a small car has started taking a new picture of the night sky every 40 seconds. The Vera C. Rubin Observatory officially began its Legacy Survey of Space and Time on June 30, 2026, moving from system optimization into full, sustained observing after already sending scientific alerts to researchers since February.

The instrument is the LSST Camera, built at SLAC National Accelerator Laboratory in California. Its 3,200 megapixels are spread across 189 charge-coupled devices, and the camera weighs roughly 3,000 kg (6,600 lb). It is cooled to nearly minus 148°F (minus 100°C) to reduce false readings. Mounted on the Simonyi Survey Telescope, the camera works with an 8.4-meter telescope to capture, process and reposition for another exposure at high speed, producing about a thousand images on a typical night.

Rubin’s flood of data will not arrive as a ready-made list of discoveries. The observatory can issue up to seven million alerts a night, each marking a statistically significant difference between a new image and an earlier view of the same patch of sky. That difference could be a brightening star, a shifting asteroid, a flickering galaxy or an imaging artifact. Automated alert brokers will sort the stream so researchers can concentrate on likely supernovae and fast-moving objects.

The power of the survey is repetition. Rubin plans to revisit each point in its survey footprint about 800 times over the coming decade, using six color filters. That turns separate photographs into a time series capable of revealing slow stellar dimming, distant orbits and other subtle changes. During roughly six weeks of pre-launch optimization observations, the observatory logged more than 11,000 previously unknown asteroids, including 33 near-Earth objects.

So what changes concretely? Researchers receive a persistent record of how the sky changes, rather than isolated snapshots, and can follow candidates as the system flags them. The scale also changes the bottleneck: Rubin can find statistical changes quickly, but alerts are not discoveries, and automated sorting remains essential before scientists can determine what each signal means.