Scientists prepare for most ambitious sky survey yet, predicting new insights into dark matter and dark energy

On a mountain in northern Chile, scientists are carefully assembling the intricate components of the NSF-DOE Vera C. Rubin Observatory, one of the most advanced astronomical facilities in history. Equipped with an innovative telescope and the world’s largest digital camera, the observatory will soon begin the Legacy Survey of Space and Time (LSST).

During LSST’s 10-year exploration of the cosmos, the Rubin Observatory will acquire 5.5 million data-rich images of the sky. Wider and deeper in volume than all previous surveys combined, LSST will provide an unprecedented amount of information to astronomers and cosmologists working to answer some of the most fundamental questions in science.

Heavily involved in the LSST Dark Energy Science Collaboration (DESC), scientists at DOE’s Argonne National Laboratory are working to uncover the true nature of dark energy and dark matter. In preparation for LSST, they are running advanced cosmological simulations and working with the Rubin Observatory to shape and process its data to maximize the potential for discovery.

Simulating the dark side

Together, dark energy and dark matter make up 95% of the energy and matter in the universe, but scientists understand very little about them. They see the effects of dark matter on the formation and motion of galaxies, but when they look for it, it doesn’t seem to be there. Meanwhile, space itself is expanding faster and faster over time, and scientists don’t know why. They refer to this unknown influence as dark energy.

“At the moment, we have no idea what their physical origin is, but we have theories,” said Katrin Heitmann, deputy director of Argonne’s High Energy Physics (HEP) division. “With LSST and the Rubin Observatory, we really think we can get good constraints on what dark matter and dark energy might be, which will help the community pursue the most promising directions.”

In preparation for LSST, Argonne scientists are taking theories about the special attributes of dark matter and dark energy and simulating the evolution of the universe under these assumptions.

It is important that scientists find ways to map their theories to the signatures that the survey can actually detect. For example, what would the universe look like today if dark matter had a light temperature, or if dark energy was super strong right after the universe began? Maybe some structures would end up more blurry, or maybe galaxies would cluster in a certain way.

Simulations can help researchers predict what features will show up in real-world data from LSST that would indicate a particular theory is true.

The simulations also allow the collaboration to validate the code they will use to process and analyze the data. For example, together with LSST DESC and the collaboration behind NASA’s Rome Nancy Grace Space Telescope, Argonne scientists recently simulated images of the night sky as each telescope will actually see it. To make sure their software works as intended, scientists can test it on this clean, simulated image data before they start processing the real thing.

To perform their simulations, Argonne scientists leverage the computing resources of the Argonne Leadership Facility (ALCF), a user facility of the DOE Office of Science. Among its array of supercomputers, ALCF houses the Aurora, one of the world’s first exascale machines, which can perform over a quintillion or billion billion calculations per second.

“Aurora’s impressive memory and speed will allow us to simulate larger volumes of the universe and compute more physics in simulations than ever before, while maintaining enough resolution to capture important details,” said Heitmann, who previously served as LSST DESC spokesperson.

What to expect when you expect an astronomical amount of data

During LSST, light emitted long ago from distant galaxies will reach the observatory. Sensors on the observatory’s camera will convert the light into data, which will travel from the mountain to several Ruby Project data facilities around the world. These facilities will then prepare the data to be sent to the larger community for analysis.

As part of LSST DESC, Argonne scientists are currently working with the Rubin Observatory to ensure that the data is processed in ways that are most conducive to their scientific goals. For example, Argonne physicist Matthew Becker is working closely with the Rubin Project to develop data-processing algorithms that will enable the investigation of dark matter and dark energy through a phenomenon called weak gravitational lensing.

“As light from distant galaxies travels toward the observatory, its path is affected by the gravitational pull of the mass in between, including dark matter,” Becker said.

“This means that, as the observatory will see, the shapes and orientations of galaxies are slightly correlated across the sky. If we can measure this correlation, we can learn about the distribution of matter – including dark matter – in the universe.”

Weak gravitational lensing can also reveal how the structure of the universe has changed over time, which could shed light on the nature of dark energy. The challenge is that the signals indicating weak gravitational lensing in the LSST data will be, well, weak. The signal strength the scientists are looking for will be approximately 30 times less than the expected level of noise, or unwanted signal disturbance, in the data.

This means that scientists need a lot of data to make sure their measurements are accurate and they are ready to get them. Once complete, LSST will have generated 60 petabytes of image data, or 60 million gigabytes. It would take over 11,000 years of Netflix viewing to use that amount of data.

Becker and his colleagues are developing methods to compress data to make analysis manageable and fruitful. For example, by combining images of the same parts of the sky taken at different times, scientists can validate features in the images to reveal correlations in the shapes of galaxies that might otherwise have been too faint to detect.

Becker is also focused on determining the level of confidence the community can expect to have in the conclusions drawn from compressed data.

“If we know how confident we can be in our analysis, it enables us to compare our results with other experiments to understand the current state of knowledge across cosmology,” Becker said. “With the data from LSST, things are going to get a lot more interesting.”