用大模型自动匹配引力波与电磁信号，提升多信使天文研究效率
An agentic framework for gravitational-wave counterpart association in the multi-messenger era
- 基于大语言模型构建自主代理框架，实现引力波与电磁候选事件的自动关联
- 支持自然语言交互，可完成星图可视化、目录管理等辅助任务
- 适用于下一代引力波与电磁探测器时代的海量数据处理场景
随着引力波的探测，多信使天文学为推进对致密物质、引力和宇宙学的理解开辟了新途径。迄今探测到的引力波源均来自致密天体双星并合，这些事件可能产生可探测的电磁对应体。寻找引力波信号与其电磁对应体之间的关联，是开展后续多信使研究的关键步骤。在下一代引力波与电磁探测器时代，事件数量的急剧增加不仅带来前所未有的科学机遇，也对现有数据分析范式构成巨大挑战。为此，我们开发了GW-Eyes——一个由大语言模型驱动的自主代理框架。首次将领域专用工具与自主决策能力结合，实现引力波与候选电磁事件的自动关联。该框架支持自然语言交互，可协助人类专家完成目录管理、天空图可视化及快速验证等辅助任务。其利用大语言模型复杂的决策能力与可追溯的推理过程，为多信使天文学提供了全新视角。
原文摘要 · Abstract (English)
With the detection of gravitational waves (GWs), multi-messenger astronomy has opened a new window for advancing our understanding of astrophysics, dense matter, gravitation, and cosmology. The GW sources detected to date are from mergers of compact object binaries, which possess the potential to generate detectable electromagnetic (EM) counterparts. Searching for associations between GW signals and their EM counterparts is an essential step toward enabling subsequent multi-messenger studies. In the era of next-generation GW and EM detectors, the rapid increase in the number of events brings not only unprecedented scientific opportunities, but also substantial challenges to the existing data analysis paradigm. To help address these challenges, we develop GW-Eyes, an agentic framework powered by large language models (LLMs). For the first time, GW-Eyes integrates domain-specific tools and autonomously performs counterpart association tasks between GW and candidate EM events. It supports natural language interaction to assist human experts with auxiliary tasks such as catalog management, skymap visualization, and rapid verification. Our framework leverages the complex decision-making capabilities of LLMs and their traceable reasoning processes, offering a new perspective to the multi-messenger astronomy.
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