Artificial intelligence tool developed to predict the structure of the universe
Advancements in telescopes have enabled researchers to study the universe with greater detail, and to establish a standard cosmological model that explains various observational facts simultaneously. But there are many things researchers still do not understand. Remarkably, the majority of the universe is made up of dark matter and dark energy of an unknown nature. A promising avenue to solving these mysteries is studying the structure of the universe. The universe is made up of filaments where galaxies cluster together. These filaments resemble threads from far away, surrounding voids where there appears to be nothing. The discovery of the cosmic microwave background has given researchers a snapshot of what the universe looked like close to its beginning; understanding how its structure evolved to what it is today would reveal valuable characteristics about dark matter and dark energy.
A team of researchers, including Kyoto University Yukawa Institute for Theoretical Physics Project Associate Professor Takahiro Nishimichi, and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU) Principal Investigator Masahiro Takada used the world's fastest astrophysical simulation supercomputers ATERUI and ATERUI II to develop the Dark Emulator. Using the emulator on data recorded by several of the world's largest observational surveys allows researchers to study possibilities concerning the origin of cosmic structures and how dark matter distribution could have changed over time.
"We built an extraordinarily large database using a supercomputer, which took us three years to finish, but now we can recreate it on a laptop in a matter of seconds. I feel like there is great potential in data science. Using this result, I hope we can work our way toward uncovering the greatest mystery of modern physics, which is to uncover what dark energy is. I also think this method we've developed will be useful in other fields such as natural sciences or social sciences," says lead author Nishimichi.
This tool uses an aspect of artificial intelligence called machine learning. By changing several important characteristics of the universe, such as those of dark matter and dark energy, ATERUI and ATERUI II have created hundreds of virtual universes. Dark Emulator learns from the data, and guesses outcomes for new sets of characteristics without having to create entirely new simulations every time. When testing the resulting tool with real-life surveys, it successfully predicted weak gravitational lensing effects in the Hyper Suprime-Cam survey, along with the three-dimensional galaxy distribution patterns recorded in the Sloan Digital Sky Survey to within 2 to 3% accuracy in a matter of seconds. In comparison, running simulations individually through a supercomputer without the AI, would take several days.
The researchers hope to apply their tool using data from upcoming surveys in the 2020s, enabling deeper studies of the origin on the universe.