中国科学家创建了ASTERIS AI,以提升深空成像,揭示微弱的星系和推进天文学。 Chinese scientists created ASTERIS AI to boost deep-space imaging, revealing faint galaxies and advancing astronomy.

清华大学的中国科学家开发了一个名为ASTERIS的AI模型,该模型通过减少噪音和改进对微弱天体的探测来增强深空成像。 Chinese scientists from Tsinghua University have developed an AI model named ASTERIS that enhances deep-space imaging by reducing noise and improving detection of faint celestial objects. 模型利用自我监督的时空分解和光度测定适应性筛选机制,将望远镜数据作为3D体积处理,将敏感度提高1.0级,并能够从早期宇宙中发现160多个高度变化的星系候选星群,而早期宇宙的预测速率是原来的两倍。 Using self-supervised spatiotemporal denoising and a photometric adaptive screening mechanism, the model processes telescope data as 3D volumes, increasing sensitivity by 1.0 magnitude and enabling the discovery of over 160 high-redshift galaxy candidates from the early universe—tripling prior rates. 它应用到詹姆斯·韦伯空间望远镜数据,将观测扩展至红外线中波长,并披露比以前低2.5倍的物体。 Applied to James Webb Space Telescope data, it extended observations into mid-infrared wavelengths and revealed objects 2.5 times fainter than before. 该技术与多台望远镜兼容,可以推进对暗能、暗物质和外行星的研究,并有可能用于下一代观测台。 The technology is compatible with multiple telescopes and could advance research on dark energy, dark matter, and exoplanets, with potential use in next-generation observatories. 研究结果在《科学》中发表。 The findings were published in Science.