01-Sep-2021 | Market Research Store
The National Institute of Natural Sciences have recently discovered a new form of artificial intelligence (AI) based technique that can remove excessive noise from astronomical data that are produced from random variations caused by galaxy shapes. After extensive training and testing measures, the research team varied their AI on a large mock dataset created by supercomputer simulation. The team further applied this new tool to an actual data that was gathered from Japan’s Subaru Telescope and found out that the pertained results derived from the mass distributions are consistent with the currently accepted formats of the Universe. This new method is expected to pave the way for analyzing big data from the current formats and for the furtherplanned astronomy surveys that will be conducted.
Surveys regarding wide area data reception are the only accepted method that are used for studying large-scale structure of the Universe through measurement patterns related to the gravitational lensing patterns. In gravitational lensing, the gravity of a foreground object is measured, for example a cluster of galaxies, which are often said to distort the captured image of any background object such as a distant galaxy. The most recent object of gravitational lensing are the “Eye of Horus”.
These large-scaled structures consist of a mysterious “dark matter” that can further disturb the shapes of distant galaxies;however, the effect on the obvious result is extremely subtle. These resultswhile averaging over many galaxies is often pertained to an area that is required for creating a map of foreground dark matter distributions. However, this technique creates “funny looking” results created from the distortions. This issue was solved by the newly created AI which can compensate for shape noise, the team generated 25,000 mock galaxies that was based on real data. The algorithm was thentrained torecover previously unobservable fine details that helped clear the excessive noise.
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