By National Astronomical Observatory of Japan.

Japanese astronomers have developed a new artificial intelligence (AI) technique to remove noise in astronomical data due to random variations in galaxy shapes. After extensive training and testing on large mock data created by supercomputer simulations, they then applied this new tool to actual data from Japan’s Subaru Telescope and found that the mass distribution derived from using this method is consistent with the currently accepted models of the Universe. This is a powerful new tool for analyzing big data from current and planned astronomy surveys.

Wide area survey data can be used to study the large-scale structure of the Universe through measurements of gravitational lensing patterns. In gravitational lensing, the gravity of a foreground object, like a cluster of galaxies, can distort the image of a background object, such as a more distant galaxy. Some examples of gravitational lensing are obvious, such as the “Eye of Horus.” The large-scale structure, consisting mostly of mysterious “dark” matter, can distort the shapes of distant galaxies as well, but the expected lensing effect is subtle. Averaging over many galaxies in an area is required to create a map of foreground dark matter distributions.

Image Text: Artist’s visualization of this research. Using AI-driven data analysis to peel back the noise and find the actual shape of the universe.
Credit: The Institute of Statistical Mathematics

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