Agent-Based Observation Assistant System to Approach AI Astrophysicist

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a summary:With rapid developments in LLMS models, LLM -based factors have provided comfortable and easy -to -use ways to take advantage of tools across various fields. In the field of astronomical observation, the construction of new telescopes has increased significantly from the burden of astronomers. The deployment of agents working with LLM leaders can reduce this burden effectively and reduce the costs associated with training employees. Within the nearby Galaxy Supernovae survey project (NGSS), which includes eight telescopes across three monitoring sites, with the aim of finding transit from galaxies at 50 MPC, we have developed \ Textbf {Starwhisper Telescope} to manage the entire monitoring process. This system automates tasks such as observing lists, making notes, analyzing data, and providing comments for the observer. Monitoring lists are allocated to different sites and strategies to ensure comprehensive coverage of heavenly things. After manual verification, these lists are loaded on telescopes through agents in the system, which start notes on a neutral language. The images are analyzed in the actual time, and the transients are immediately connected to the observer. The agent amends them in the actual follow -up monitoring proposal and send it to the Xinglong Observatory chat, then add it to the monitoring lists the next day. In addition, the integration of artificial intelligence agents within the system provides online access, providing the time of astronomers and encouraging greater participation of amateur astronomers in the NGSS project.