A new map of dark matter in the universe sheds more light on the many previously unknown filament structures that connect galaxies together.
The map, developed using machine learning by an international team that includes an astrophysicist from Pennsylvania, could enable studies of the nature of dark matter and the history and future of the universe.
What is dark matter
Dark matter is elusive matter that makes up 80% of the universe. It also contains the “skeleton” of what cosmologists use Cosmic web, The large structure of the universe which, with its gravitational influence, determines the movement of galaxies and other cosmic materials.
However, the distribution of dark matter is currently unknown. We still don’t know how to directly measure it.
The researchers infer their distribution due to the effect of gravity on other objects in the universe, such as B. Galaxies.
So far so close
Ironically, it is easier to study the distribution of dark matter further, “because it reflects a very distant past, which is much less complex,” he says. Donghui Jeong, Associate Professor of Astronomy and Astrophysics at Penn State and author of the study.
“Over time, the complexity of the universe increased as the large-scale structure of the universe grew, making the measurement of dark matter locally inherently more difficult.”
Previous attempts to map the cosmic web began with a model of the early universe. Then evolution over billions of years was simulated from this model. An extensive calculation method that has not yet provided sufficient detailed results.
Chasing the structure of galaxies
In the new study, the researchers took a completely different approach. Using machine learning, they developed a model that uses information about the distribution and movement of galaxies to predict the distribution of dark matter.
Researchers built and trained their model using a variety of galaxy simulations Alluminary-TNG, Which includes galaxies, gas, and other visible matter, and dark matter. The team specifically selected simulated galaxies that could be compared to those in the Milky Way, and finally determined the galaxy properties needed to predict the distribution of dark matter.
“If certain information is provided, the model can basically fill in the gaps based on its previous observations,” Jeong says.
“The map of our models doesn’t exactly match the simulated data, but we can still reconstruct the very detailed structures. We found that including the movement and distribution of galaxies greatly improved the quality of the map and allowed us to see more detail.
The map resulting from the Local Cosmic Network was published in an article It appeared online May 26 in The Astrophysical Journal.
How is the new galaxy map created
“Having a local map of the cosmic web opens a new chapter in the cosmic study,” Jeong said. We can study how the dark matter distribution relates to other emission data, which will help us understand the nature of dark matter. And we can study these filamentous structures, these hidden bridges between galaxies, directly. “
For example, it has been suggested that the Milky Way and Andromeda could move slowly towards each other, but it is unclear if they could collide over billions of years. Examining the strands of dark matter connecting the two galaxies could provide important insights into their future.
“Since dark matter dominates the dynamics of the universe, it basically determines our destiny,” Jeong said. “So we can ask a computer to develop the map for billions of years to see what will happen in the local universe. And we can develop the model in time to understand the history of our cosmic neighborhood.”
Researchers think they can improve the accuracy of their map by adding more galaxies.