Final supernova results from Dark Energy Survey offer unique insights into expansion of universe

In 1998, astrophysicists discovered that the universe is expanding at an accelerating rate, attributed to a mysterious entity called dark energy that makes up about 70% of our universe.

This revolutionary discovery, thanks to observations of specific kinds of exploding stars called type Ia (pronounced “type one-A”) supernovae, was recognized with the Nobel Prize.

Now, 25 years after the initial discovery, the scientists working on the Dark Energy Survey have released the results of an analysis using the same technique to further probe the mysteries of dark energy and the expansion of the universe.

In the culmination of a decade’s worth of effort, the scientists analyzed an unprecedented sample of more than 1,500 supernovae classified using machine learning. They placed the strongest constraints on the expansion of the universe ever obtained.

The results are consistent with the now-standard cosmological model of a universe with an accelerated expansion, the scientists said.

Yet the results do not rule out a more complex theory that the density of dark energy in the universe could have varied over time.

Taking a unique approach to analysis

To understand dark energy and how it affects our universe, astrophysicists trace out the history of cosmic expansion by using large samples of supernovae.

For each supernova, they combine its distance with a measurement of its redshift — how quickly it is moving away from Earth due to the expansion of the universe. They can use that history to determine whether the dark energy density in the universe has remained constant or changed over time.

In this case, the team analyzed supernovae catalogued by the Dark Energy Camera, a 570-megapixel digital camera built by Fermi National Accelerator Laboratory and funded by the U.S. Department of Energy’s Office of Science and the National Science Foundation. Mounted on the National Science Foundation’s four-meter Blanco telescope, part of the Cerro Tololo Inter-American Observatory in Chile, the Dark Energy Camera mapped the sky for six years. The Dark Energy Survey collaboration comprises more than 400 astrophysicists, astronomers and cosmologists from over 25 institutions led by members from Fermilab.

The scientists wanted to use these supernovae to test our existing model of the universe. The standard cosmological model is LCDM, or Lambda Cold Dark Matter, a model based on the dark energy density being constant over cosmic time. It tells us how the universe evolves, using just a few features, such as the density of matter, type of matter and behavior of dark energy.

The supernova method can be used to test Lambda Cold Dark Matter by measuring a quantity called w, which indicates whether the dark energy density is constant or not.

According to the standard cosmological model, the density of dark energy in the universe should be constant, which means it doesn’t dilute as the universe expands. If this is true, the parameter represented by the letter w should equal –1.

The new results found a w of –0.80, plus or minus 0.18, using supernovae alone. Combined with complementary data from the European Space Agency’s Planck telescope, w reaches –1 within the error bars.

w is tantalizingly not exactly on –1, but close enough that it’s consistent with –1,” said Tamara Davis, a professor at the University of Queensland in Australia and co-convener of Dark Energy Survey’s supernova working group. “A more complex model might be needed. Dark energy may indeed vary with time.”

“All of this is really unknown territory,” said Dark Energy Survey director and spokesperson Rich Kron, who is a Fermilab and University of Chicago scientist. “We do not have a theory that puts dark energy into a framework that relates to other physics that we do understand. For the time being, we in the Dark Energy Survey are working to constrain how dark energy works in practice with the expectation that, later on, some theories can be falsified.”

Pioneering a new approach

When the Dark Energy Survey  collaboration internally unveiled their supernova results, it was a culmination of a decade’s worth of effort and an emotional time for many of the astrophysicists involved. “I was shaking,”said Davis. “It was definitely an exciting moment.”

To come to a definitive conclusion, scientists will need more data. But the Dark Energy Survey won’t be able to provide that; the survey stopped taking data in January 2019. The supernova team, led by many Ph.D. students and postdoctoral fellows, will soon have extracted all they can from the Dark Energy Survey observations.

However, the innovative techniques the Dark Energy Survey pioneered will shape and further drive future astrophysical analyses.

The new study pioneers a new approach to use photometry — with an unprecedented four filters — to find the supernovae, classify them and measure their light curves. Follow-up spectroscopy of the host galaxy with the Anglo-Australian Telescope provided precise redshifts for every supernova. The use of the additional filters also enabled data that is more precise than previous surveys and is a major advancement compared to the Nobel-winning supernovae samples, which only used one or two filters.

The Dark Energy Survey researchers also used advanced machine-learning techniques to aid in supernova classification. Among the data from about two million distant observed galaxies, the Dark Energy Survey found several thousand supernovae. Scientists ultimately used 1,499 type Ia supernovae with high-quality data, making it the largest, deepest supernova sample from a single telescope ever compiled.

Projects like the Legacy Survey of Space and Time, LSST, to be conducted at the Vera C. Rubin Observatory,and NASA’s Nancy Grace Roman Space Telescope, will pick up where the Dark Energy Survey left off.

“We’re pioneering these techniques that will be directly beneficial for the next generation of supernova surveys,” said Kron.

Adapted from a press release first published by Fermilab.

Citation: "The Dark Energy Survey: Cosmology results with ~1500 new high-redshift type Ia supernovae using the full 5-year dataset.” Accepted to Astrophysical Journal Letters.

Funding: Funding for the DES Projects has been provided by the U.S. Department of Energy, the U.S. National Science Foundation, the Ministry of Science and Education of Spain, the Science and Technology Facilities Council of the United Kingdom, the Higher Education Funding Council for England, the National Center for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics at the University of Chicago, Funding Authority for Funding and Projects in Brazil, Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro, Brazilian National Council for Scientific and Technological Development and the Ministry of Science and Technology, the German Research Foundation and the collaborating institutions in the Dark Energy Survey.