Toward Autonomous Radio Follow-up of Multi-messenger Transients with RADAR: From Alert Parsing to Inference and Observation Scheduling
用RADAR实现多信使暂现源自主射电后随:从警报解析到推理与观测排程
Multi-messenger astronomy (MMA), the joint study of cosmic sources through gravitational waves (GWs), electromagnetic (EM) radiation, neutrinos, and cosmic rays, is rapidly reshaping time-domain astrophysics. Realizing the promise of MMA will require coordinating heterogeneous observing resources and automating the chain from alert to analysis to follow-up. RADAR (Radio Afterglow Detection and AI-driven Response) is a federated, privacy-enhancing framework for the radio follow-up of GW events, previously validated on GW170817. Here, we extend it along three axes. First, we benchmark three large language models (LLMs; GPT-5.5, Claude-Opus-4.7, and Gemini-3.5-Flash) against the GW170817 radio light curve dataset. GPT-5.5 attains the highest event-level $F_1$ score, the harmonic mean of precision and recall, at $0.893 \pm 0.010$, and the highest GCN-level recall, $0.794 \pm 0.013$, improving on previous GPT-4.1 results by 16\% and 10\%, respectively, while Claude-Opus-4.7 achieves the highest precision, $0.978 \pm 0.014$. Second, we introduce concurrent likelihood evaluation, which speeds up the MCMC computation by a factor of $40\times$ over our previous results. Third, we present an LLM-driven scheme that converts natural-language observing requests into submission-ready scheduling blocks for the Karl G. Jansky Very Large Array. Together, these developments advance RADAR toward a scalable, largely autonomous system for GW radio follow up.
展开 ▾首次将LLM解析器、加速联邦推理与自动化观测排程整合为近乎全自主的闭环流程;分布式MCMC采样速率提升40倍,端到端延迟从数小时降至数分钟。
在 Patel et al. Patel+ 2025 提出的联邦射电后随框架RADAR基础上,本文将GCN解析器升级至GPT-5.5等新一代大模型,将事件级F1提升至0.893,显著减少人工复查。通过服务端线程池与站点子进程池实现的并发似然评估,消除了网络延迟瓶颈,使afterglowpy的分布式MCMC速率匹配本地并行水平,4小时拟合缩短至约6分钟。同时构建了LLM驱动的SAGE引擎,可将自然语言请求直接转换为VLA就绪的调度块,合规率超过95%。这三项进展打通了从引力波警报到数据收集的自主流程,为应对Cosmic Explorer等下一代设施的高事件率奠定基础。未来可结合FIESTA Koehn+ 2025 的JAX向量化进一步加速单次似然评估,并拓展至更多设施和波长。
预印本 2026-09-16 · 收录 2026-09-17