The universe is expanding at an ever-increasing rate, and while no one is sure why, the Dark Energy Survey (DES) researchers at least had one strategy for finding out: They would combine measurements of the distribution of matter, galaxies, and clusters of galaxies to better understand what is happening.
Reaching that goal turned out to be quite difficult, but now a team led by researchers from the Department of Energy’s SLAC National Accelerator Laboratory, Stanford University and the University of Arizona have found a solution. Their analysis, published April 6 in Physical Review Letters, produces more accurate estimates of matter’s average density, as well as its propensity to cluster, two key parameters that help physicists investigate the nature of dark matter and dark energy, the mysterious substances that make up the vast majority of the universe.
“It’s one of the best limitations of one of the best data sets to date,” says Chun-Hao To, lead author of the new paper and a graduate student at SLAC and Stanford who works with the Kavli Institute for Particle Astrophysics and Director of Cosmology. Risa Wechsler.
An early goal
When DES set out in 2013 to map an eighth of the sky, the goal was to collect four types of data: the distances to certain types of supernovae or exploding stars; the distribution of matter in the universe; the distribution of galaxies; and the distribution of galaxy clusters. Each one tells researchers something about how the universe has evolved over time.
Ideally, scientists would put all four data sources together to improve their estimates, but there is a catch: the distributions of matter, galaxies, and galaxy clusters are closely related. If researchers don’t account for these relationships, they’ll end up “counting twice,” putting too much weight on some data and not enough on others, To says.
To avoid mishandling all this information, University of Arizona astrophysicist Elisabeth Krause and her colleagues have developed a new model that could adequately explain the connections in the distributions of the three quantities: matter, galaxies, and galaxy clusters. In doing so, they were able to produce the first analysis to properly combine all these disparate data sets to learn about dark matter and dark energy.
Adding that model to the DES analysis has two effects, says To. First, measurements of the distributions of matter, galaxies, and galaxy clusters tend to introduce different types of errors. The combination of the three measurements makes it easier to identify these errors, making the analysis more robust. Second, the three measurements differ in their sensitivity to the mean density of matter and its agglomeration. As a result, the combination of all three can improve the precision with which DES can measure dark matter and dark energy.
In the new paper, To, Krause, and their colleagues applied their new methods to the first year of DES data and fine-tuned the precision of previous estimates for matter density and clumping.
Now that the team can incorporate matter, galaxies and galaxy clusters simultaneously into their analysis, adding supernova data will be relatively straightforward, since those kinds of data are not as closely related to the other three, says To.
“The immediate next step,” he says, “is to apply the machinery to the DES year 3 data, which has three times the sky coverage.” This isn’t as simple as it sounds: while the basic idea is the same, the new data will require additional efforts to improve the model and keep up with the higher quality of the newer data, says To.
“This analysis is really exciting,” Wechsler said. “I hope it sets a new standard in the way we can analyze data and learn about dark energy from large surveys, not only for DES, but also looking forward to the incredible data that we will get from the Vera Rubin Observatory’s Legacy survey. Space and Time in a few years “.
The smallest galaxies in our universe bring more dark matter to light
C. To et al, Dark Energy Survey Year 1 Results: Cosmological Constraints on Cluster Abundance, Faint Lens, and Galaxy Correlations, Physical Review Letters (2021). DOI: 10.1103 / PhysRevLett.126.141301
Provided by SLAC National Accelerator Laboratory
Citation: Dark Energy Survey Physicists Open New Window to Dark Energy (2021, April 6) Retrieved April 6, 2021 from https://phys.org/news/2021-04-dark-energy-survey- physicists-window.html
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