2023-04-24 ジョージア大学 (UGA)
この発見は、科学者たちがより正確に調査を行い、時間をより効率的に経済的に使うために、人工知能を追加のツールとして活用することができることを示しています。機械学習によって、以前に検出されなかった信号をデータから検出することができたとのことです。
＜関連情報＞
- https://news.uga.edu/uga-researchers-discover-new-planet-outside-solar-system/
- https://iopscience.iop.org/article/10.3847/1538-4357/acc737
機械学習によって特定されたHD 142666の原始惑星の運動学的証拠。 Kinematic Evidence of an Embedded Protoplanet in HD 142666 Identified by Machine Learning
J. P. Terry, C. Hall, S. Abreau and S. Gleyzer
The Astrophysical Journal Published 2023 April 21
DOI:10.3847/1538-4357/acc737
Abstract
Observations of protoplanetary disks have shown that forming exoplanets leave characteristic imprints on the gas and dust of the disk. In the gas, these forming exoplanets cause deviations from Keplerian motion, which can be detected through molecular line observations. Our previous work has shown that machine learning can correctly determine if a planet is present in these disks. Using our machine-learning models, we identify strong, localized non-Keplerian motion within the disk HD 142666. Subsequent hydrodynamics simulations of a system with a 5 MJ planet at 75 au recreate the kinematic structure. By currently established standards in the field, we conclude that HD 142666 hosts a planet. This work represents a first step toward using machine learning to identify previously overlooked non-Keplerian features in protoplanetary disks.
