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Astronomers have developed a new method for analyzing three-dimensional maps of galaxies that could change scientific understanding of dark matter and dark energy. The new approach, proposed by researchers at the University of Tokyo and the Max Planck Institute, allows for the extraction of hidden information that was previously lost through data compression.
Traditionally, n-point correlation functions have been used to analyze cosmic structures, which simplify massive calculations. However, this method does not reveal all the details in the distribution of galaxies. A new approach, field-level inference (FLI), works directly with 3D maps and uses powerful algorithms to compare observed galaxies with simulations of their evolution.
Preliminary results show that FLI can improve the accuracy of analysis by a factor of 3-5 compared to traditional methods. This opens up the possibility of investigating anomalies in the distribution of matter that may indicate new physical phenomena or even revise our understanding of the force of gravity.
The next step will be to apply FLI to real-world data from the Euclid telescope, the Dark Energy Spectroscopic Instrument, and the upcoming Nancy Grace Roman Space Telescope. Scientists hope the new method will help unlock mysteries of the structure of the universe, including the influence of dark matter on galaxy formation.
These studies could hold the key to understanding some of the cosmos' greatest mysteries, such as the nature of dark energy and the mechanisms of galaxy cluster formation. The study results were published in the journal Physical Review Letters.
Astronomers have developed a new method for analyzing three-dimensional maps of galaxies that could change scientific understanding of dark matter and dark energy. The new approach, proposed by researchers at the University of Tokyo and the Max Planck Institute, allows for the extraction of hidden information that was previously lost through data compression.
Traditionally, n-point correlation functions have been used to analyze cosmic structures, which simplify massive calculations. However, this method does not reveal all the details in the distribution of galaxies. A new approach, field-level inference (FLI), works directly with 3D maps and uses powerful algorithms to compare observed galaxies with simulations of their evolution.
Preliminary results show that FLI can improve the accuracy of analysis by a factor of 3-5 compared to traditional methods. This opens up the possibility of investigating anomalies in the distribution of matter that may indicate new physical phenomena or even revise our understanding of the force of gravity.
The next step will be to apply FLI to real-world data from the Euclid telescope, the Dark Energy Spectroscopic Instrument, and the upcoming Nancy Grace Roman Space Telescope. Scientists hope the new method will help unlock mysteries of the structure of the universe, including the influence of dark matter on galaxy formation.
These studies could hold the key to understanding some of the cosmos' greatest mysteries, such as the nature of dark energy and the mechanisms of galaxy cluster formation. The study results were published in the journal Physical Review Letters.
