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<p>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 astronomers. Deployed across Nearby Galaxy Supernovae Survey’s network of 10 amateur telescopes, StarWhisper Telescope has detected transients with promising response times relative to existing surveys. Furthermore, StarWhisper Telescope’s scalable agent architecture provides a blueprint for future facilities like the Global Open Transient Telescope Array, where AI-driven autonomy will be critical for managing 60 telescopes.</p>

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StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月6日

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  • 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,
  • Xiaohan Chen,
  • Shunxuan He,
  • Hao Mo,
  • Liyue Zhang,
  • Lin Du,
  • Yunning Zhao,
  • Jianfeng Tian,
  • Liang Ge,
  • Yongna Mao,
  • Shengming Li,
  • Zheng Wang,
  • Xiaomeng Lu,
  • Jinhang Zou,
  • Yang Huang,
  • Ningchen Sun,
  • Jie Zheng,
  • Min He,
  • Yu Bai,
  • Junjie Jin,
  • Hong Wu,
  • Jifeng Liu

摘要

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 astronomers. Deployed across Nearby Galaxy Supernovae Survey’s network of 10 amateur telescopes, StarWhisper Telescope has detected transients with promising response times relative to existing surveys. Furthermore, StarWhisper Telescope’s scalable agent architecture provides a blueprint for future facilities like the Global Open Transient Telescope Array, where AI-driven autonomy will be critical for managing 60 telescopes.