Dark Energy Survey Catalogs 226 million Galaxies – Sky & Telescope


Dark Energy Survey
Ten areas in the sky were selected as “deep fields” that the Dark Energy Camera imaged several times during the survey, providing a glimpse of distant galaxies and helping determine their 3D distribution in the cosmos. The image is teeming with galaxies — in fact, nearly every single object in this image is a galaxy. Some exceptions include a couple of dozen asteroids as well as a few handfuls of foreground stars in our own Milky Way.
Dark Energy Survey / DOE / FNAL / DECam / CTIO / NOIRLab / NSF / AURA; Acknowledgments: T.A. Rector / M. Zamani / D. de Martin

In one of the biggest sky surveys ever, astronomers have captured 226 million galaxies up to 7 billion light-years away in an area covering about one-eighth of the entire sky. This treasure trove of data provides scientists with the best-ever probe of cosmic evolution and illuminates the role of dark matter and dark energy in shaping the large-scale structure of the universe.

The Dark Energy Survey (DES) started back in August 2013. On May 27th, the international collaboration published its second data release, covering the first three years of observations. The results are described in 30 scientific papers, available on the DES website. “It’s a beautiful dataset,” says René Laureijs, project scientist of the European Space Agency’s Euclid mission.

The new results support the popular ΛCDM model, in which the universe is governed by 68.5% dark energy (or lambda, Λ) and 26.6% cold dark matter – mysterious ingredients that vastly overshadow the remaining 4.9% of “normal” matter in galaxies, stars, planets, and people. There’s one nagging discrepancy, though: just like other surveys, DES found that the current universe is a few percent less “clumpy” than the ΛCDM model would predict. Nobody knows why.

The real star of the survey is the massive 570-megapixel Dark Energy Camera, built by the Department of Energy at Fermilab in Chicago, and mounted at the prime focus of the 4-meter Blanco Telescope at the Cerro Tololo Inter-American Observatory in Chile. Night after night, it has captured hundreds of 90-second exposures, each as wide as four full Moons. Over the years, the whole 5,000-square-degree survey area was imaged at least 10 times down to a limiting magnitude of 23.3, while ten deep fields were studied repeatedly in even more detail.

Dark Energy Camera
The Dark Energy Survey camera in the cleanroom.
DOE / FNAL / DECam / R. Hahn / CTIO / NOIRLab / NSF / AURA

Based on a galaxy’s brightness in five wavelength bands in visible and near-infrared light, the DES team can determine its “photometric redshift,” which yields a rough but reliable distance estimate. Thus, astronomers are able to discern the evolution of galaxy clustering across the history of the universe, which sheds light on the actions of dark matter and dark energy. Estimates of so-called cosmic shear — minute shape distortions due to weak gravitational lensing — provide additional information on the distribution of dark matter. The elaborate data analysis was carried out at the National Center for Supercomputer Applications at the University of Illinois.

Although the Dark Energy Survey was completed in early 2019, the last three years of data are still being processed; results may not be published until a few years from now. Meanwhile, an equally impressive spectroscopic galaxy survey officially took off a few weeks ago at the 4-meter Mayall telescope at Kitt Peak National Observatory in Arizona. The similarly named Dark Energy Spectroscopic Instrument aims to capture real spectra of tens of millions of galaxies and quasars over the next five years.

Slated for launch in late 2022, the Euclid space mission will carry out an even larger and deeper survey with similar cosmological goals. According to project scientist Laureijs, Euclid will study about 15 times more galaxies than the Dark Energy Survey has done, out to distances of 10 billion light-years, both by measuring their brightness (focusing on the infrared) and by taking their spectrum. “We really need a higher precision to definitely validate the ΛCDM model,” he says.



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