Dark Energy Survey: Scientists Unlock A New Window Into Dark Energy

A study by Dark Energy Survey scientists generates more specific estimates of the average density of matter as well as its ability to clump together — two essential parameters that assist physicists to probe the nature of dark energy and dark matter.

The universe is expanding day-by-day at an escalating rate, and while no one is sure why scientist with the Dark Energy Survey (DES) at least had a plan for solving it out: They would combine measurements of the distribution of galaxy clusters, galaxies, and matter, to adequately understand what’s going on.

Reaching that aim set out to be pretty complex, but now a group headed by scientists at the University of Arizona and Department of Energy’s SLAC National Accelerator Laboratory, Stanford University have come up with a solution. Their research, published on 6th April 2021 in Physical Review Letters, explains more explicit estimates of the average density of matter as well as its ability to clump mutually — two essential parameters that assist scientists to probe the nature of dark energy and dark matter, the strange matter that makes up the limitless majority of the universe.

“It is one of the greatest restraints from one of the most useful data sets to date,” says Chun-Hao To, lead author of the research, Cosmology Director Risa Wechsler, and a graduate scholar at SLAC and Stanford working with Kavli Institute for Particle Astrophysics.

dark energy and dark matter
A map of the sky displaying the density of matter, galaxies, and galaxy clusters in the universe over the part of the sky observed by the Dark Energy Survey. Red areas are denser, and blue areas are less dense than average. Source: Chun-Hao To/Stanford University, SLAC National Accelerator Laboratory

The Initial Aim

When DES was introduced in 2013 to draft an eighth of the sky, the purpose was to collect four sets of data: the distribution of matter in the universe; the distances to certain types of supernovae, or exploding stars; the distribution of galaxy clusters; and the distribution of galaxies. Each shows scientists something about how the universe has emerged.

Ideally, experts would place all four data sources collectively to enhance their evaluations, but there’s a difficulty: The distributions of galaxy clusters, galaxies, and matter are all closely linked. If scientists don’t take these links into a record, they will end up “double counting,” putting too much importance on some data and not enough on others, To says.

To bypass the mishandling of all this information, To, the University of Arizona astrophysicist Elisabeth Krause and his associates have formed a new model that could accurately account for the connections in the distributions of all three quantities: galaxy clusters, galaxies, and matter. In doing so, they were able to design the first-ever analysis to accurately join all these diverse data sets to study dark energy and dark matter.

Improving estimates

Combining that model into the DES study has two consequences, To says. First, measurements of the concentrations of galaxy clusters, galaxies, and matter tend to introduce various types of errors. Joining all three measurements makes it simpler to classify any such errors, making the analysis more sturdy. Second, the three measurements contrast in how sensitive they are to the average density of matter and its clumpiness. As a result, merging all three can enhance the accuracy with which the DES can cover the dark energy and dark matter.

In the new research, To, Krause, and his associates used their new techniques to the initial DES data and clarified the accuracy of prior estimates for matter’s density and clumpiness.

Now that the group can combine galaxy clusters, galaxies, and matter together in their analysis, connecting in supernova data will be comparatively straightforward, since that set of data is not as closely associated with the other three, To says.

“The subsequent step,” he says, “is to implement the machine to DES Year 3 data, which has three times more extensive coverage of the sky.” This is not as easy as it sounds: While the primary idea is the same, the new data will need extra efforts to enhance the model to keep up with the higher degree of the newer data, To says.

“This study is really interesting,” Wechsler said. “I think, it will set an innovative criterion in the way we can interpret data and understand dark energy from comprehensive 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 of Space and Time in a few years.”

Journal Reference:

C. To, E. Krause, H. Wu, D. Gruen, E. Rozo, R. H. Wechsler, T. F. Eifler, E. S. Rykoff, M. Costanzi,T. Giannantonio, M. R. Becker, J. Blazek, S. Bocquet, S. L. Bridle, G. M. Bernstein, R. Cawthon, A. Choi, M. Crocce, J. DeRose, A. Drlica-Wagner, C. Davis, J. Elvin-Poole, X. Fang, A. Farahi, O. Friedrich, M. Gatti, E. Gaztanaga, J. Annis, E. Sheldon, W. G. Hartley, A. J. Ross, B. Hoyle, M. Jarvis, A. Carnero Rosell, N. MacCrann, D. Brooks, T. McClintock, V. Miranda, M. E. S. Pereira, Y. Park, A. Porredon, J. Prat, M. M. Rau, S. Samuroff, A. Amon, C. Sánchez, I. Sevilla-Noarbe, M. A. Troxel, M. E. C. Swanson, G. Tarle, D. Thomas, T. N. Varga, P. Vielzeuf, Y. Zhang, J. Zuntz, T. M. C. Abbott, M. Aguena, S. Avila, E. Bertin, S. Bhargava, M. Carrasco Kind, J. Carretero, C. Chang, V. Scarpine, S. Serrano, M. Smith, E. Suchyta, C. Conselice, K. Honscheid, D. Huterer, D. J. James, T. Jeltema, R. Kron, T. M. Davis, S. Desai, H. T. Diehl, J. P. Dietrich, S. Everett, A. E. Evrard, I. Ferrero, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, R. A. Gruendl, G. Gutierrez, S. R. Hinton, A. Palmese, D. L. Hollowood, K. Kuehn, N. Kuropatkin, L. N. da Costa, M. Lima, M. A. G. Maia, J. L. Marshall, F. Menanteau, D. L. Burke, R. Miquel, R. Morgan, J. Muir, J. Myles,, F. Paz-Chinchón, A. A. Plazas, A. Roodman, E. Sanchez, B. Santiago, D. L. Tucker, J. Weller, W. Wester, R. D. Wilkinson, A. K. Romer. Dark Energy Survey Year 1 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy CorrelationsPhysical Review Letters, 2021; 126 (14) DOI: 10.1103/PhysRevLett.126.141301

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