StarWhisper Telescope: An AI framework for automating end-to-end astronomical observations
Cunshi Wang, Yu Zhang, Yuyang Li, Xinjie Hu, Yiming Mao, Xunhao Chen, Pengliang Du, Rui Wang, Ying Wu, Hang Yang, Yansong Li, Beichuan Wang, Haiyang Mu, Zheng Wang, Jianfeng Tian, Liang Ge, Yongna Mao, Shengming Li, Xiaomeng Lu, Jinhang Zou, Yang Huang, Ningchen Sun, Jie Zheng

TL;DR
StarWhisper Telescope is an AI framework that automates the entire process of astronomical observations, from planning to data analysis, significantly reducing human effort and enabling scalable, autonomous survey operations.
Contribution
It introduces a novel AI agent system integrating large language models with modular workflows for end-to-end autonomous astronomical observations.
Findings
Successfully deployed on 10 amateur telescopes for supernova detection
Achieved real-time transient detection with promising response times
Provides a scalable blueprint for future large-scale autonomous telescope arrays
Abstract
The exponential growth of large-scale telescope arrays has boosted time-domain astronomy development but introduced operational bottlenecks, including labor-intensive observation planning, data processing, and real-time decision-making. Here we present the StarWhisper Telescope system, an AI agent framework automating end-to-end astronomical observations for surveys like the Nearby Galaxy Supernovae Survey. By integrating large language models with specialized function calls and modular workflows, StarWhisper Telescope autonomously generates site-specific observation lists, executes real-time image analysis via pipelines, and dynamically triggers follow-up proposals upon transient detection. The system reduces human intervention through automated observation planning, telescope controlling and data processing, while enabling seamless collaboration between amateur and professional…
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Taxonomy
TopicsDistributed and Parallel Computing Systems
