The universe is expanding at an ever-increasing rate, and while no one is sure why, scientists with the Dark Energy Survey (DES) at least had a strategy for finding out: They would combine measurements of the distribution of matter, galaxies and galaxy cluster to better understand what’s going on.
Achieving this goal proved to be quite difficult, but now a team led by researchers at the Department of Energy’s SLAC National Accelerator Laboratory, Stanford University and the University of Arizona has come up with a solution. Their analysis, published on April 6 in Physical review letters, provides more accurate estimates of the average density of matter as well as its propensity to clump together – two key parameters that help physicists study 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 datasets to date,” said Chun-Hao To, a lead author on the new paper and a graduate student at SLAC and Stanford working with the Kavli Institute for Particle Astrophysics and Cosmology. Director. Risa Wechsler.
An early goal
When DES set out in 2013 to map one-eighth of the sky, the goal was to collect four kinds of data: distances to specific types of supernovae or exploding stars; the distribution of matter in the universe; distribution of galaxies and the distribution of galaxy clusters. Each tells scientists 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 pick: The distributions of matter, galaxies, and galaxy clusters are all closely related. If researchers do not take these factors into account, they end up with “double counting” and placing too much emphasis on some data and not enough on others, To says.
To avoid mishandling all this information, astrophysicist Elisabeth Krause of the University of Arizona and colleagues have developed a new model that could properly take into account the connections in the distribution of all three sizes: matter, galaxies, and galaxy clusters. In doing so, they were able to produce the first analysis ever to properly combine all of these different data sets to learn about dark matter and dark energy.
Adding this model to the DES analysis has two effects, To says. First, measurements of matter distributions, galaxies, and galaxy clusters tend to introduce different kinds of errors. Combining all three measurements makes it easier to identify such errors, making the analysis more robust. Second, the three measurements differ in how sensitive they are to the average density of matter and its lumpiness. As a result, combining all three can improve the precision with which DES can measure dark matter and dark energy.
In the new paper, To, Krause, and colleagues applied their new methods to the first year of DES data, sharpening the precision of previous estimates of the substance’s density and lumpiness.
Now that the team can incorporate matter, galaxies, and galaxy clusters simultaneously into their analysis, addition in supernova data will be relatively straightforward, as that kind of data is not so closely related to the other three, To says.
“The immediate next step,” he says, “is to apply the machines to DES Year 3 data, which has three times the coverage of the sky.” This is not as simple as it sounds: While the basic idea is the same, the new data will require further efforts to improve the model to keep pace with the higher quality of the newer data, says To.
“This analysis is really exciting,” Wechsler said. “I expect it to set a new standard in the way we are able to analyze data and learn about dark energy from large studies, not only for DES, but also looking forward to the incredible data we get from Vera Rubin. The Observatory’s Legacy Survey of Space and Time in a Few Years. ”
The smallest galaxies in our universe bring more about dark matter to light
C. To et al, Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, 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 in Dark Energy (2021, April 6) Retrieved April 6, 2021 from https://phys.org/news/2021-04-dark-energy-survey-physicists-window.html
This document is subject to copyright. Except for fair trade for private examination or research, no parts may be reproduced without written permission. The content is provided for informational purposes only.