此次合作成功获取了8个球状星团中43颗脉冲星的偏振旋转测量，这是衡量宇宙磁场强度的关键指标。研究发现，其中7个球状星团中都没 有可探测的电离气体，异常"干净"。 球状星团是银河系中最古老的天体之一，通常由数百万颗恒星构成，包括脉冲中子星。高度磁化的脉冲星以极高的精度发出规律的电磁脉 冲信号，这些信号穿越广漠的星际空间到达地球，携带了星际物质和磁场的宝贵信息。FAST的500米口径反射面擅长捕捉最微弱的宇宙涟漪 ——那些来自数百万光年外的脉冲星信号；MeerKAT的64面天线阵则专注追踪更广阔天区中的信号。此次这两台全球顶尖射电望远镜在球状 星团研究领域首次深度合作，刷新了观测极限。 清华大学教授 李菂：结合地球南半球的设备和地球北半球的设备一起观测，并且两个设备的能力也是不一样的，这样合起来，观测的样 本就扩大了一倍以上。 共同揭示银河系古老天体的"无尘之境" 央视网消息：近日，清华大学联合意大利、澳大利亚、德国等多国天文学家，利用中国天眼FAST和南非MeerKAT阵列望远镜对银河系球 状星团进行了高精度观测，绘制出更清晰的银河磁场图谱，为理解星团演化和银河系磁场提供了新的视角。 清华大学教授 李菂：我们管 ...

Core Viewpoint - The exploration for extraterrestrial life is being revolutionized by the integration of artificial intelligence (AI) into astronomical research, enhancing data analysis and hypothesis generation capabilities [1][2][6]. Group 1: AI in Astrobiology - NASA's "AstroAgents" system, consisting of eight AI agents, is designed to autonomously conduct research in astrobiology, analyzing data and generating scientific hypotheses [2][3]. - The system aims to study Martian samples to identify organic molecules that may indicate past or present life [2][3]. - AI agents utilize large language models to actively participate in research, determining research content and methods, and evaluating results [2][3]. Group 2: Discovering Exoplanets - The ExoMiner project, developed by NASA scientists, has successfully identified 370 previously unknown exoplanets using machine learning techniques [4][5]. - Despite the discovery, none of the identified exoplanets have environments similar to Earth, indicating a challenging search for habitable conditions [4][5]. Group 3: SETI and Electromagnetic Signal Monitoring - The SETI program is employing AI to analyze electromagnetic signals across a wide wavelength range, enhancing the search for extraterrestrial intelligence [6][7]. - A new AI-driven software system is being developed for the Very Large Array (VLA) to process vast amounts of data, significantly improving the efficiency of signal detection [6][7]. - SETI's efforts include scanning millions of stars and hundreds of galaxies for signs of life, with AI also being used to analyze Martian rock samples for biological indicators [6][7].