Adaptive Optics Astrometry for Black Hole Science

黑洞是天体物理学中最奇特的现象之一，代表了基础物理学在引力和量子力学之间的崩溃。在我们银河系的中心，通过世界上最大的望远镜进行高精度天文测量观测，发现了一个超大质量黑洞，这一发现在2020年获得了诺贝尔奖。除了中央的黑洞，银河系可能还包含一千万到十亿个恒星质量的黑洞，或者是质量是太阳几倍的黑洞。迄今为止，孤立的恒星质量黑洞还没有被明确地探测到，只有24个黑洞被测量到质量——都是双黑洞。从根本上说，对黑洞的研究，无论大小，都取决于我们对恒星在天空平面上的运动进行极其精确测量的能力。加州大学伯克利分校（University of California-Berkeley）的一个研究小组将利用他们正在开发的自适应光学技术（AO）来提高我们进行此类测量的能力，该技术是为了消除凯克天文台（w.m. Keck Observatory）望远镜对地球大气的模糊影响。研究人员还将通过扩大AstroTech项目，在为期一周的暑期学校和外部实习项目之间建立桥梁，加强对下一代天文仪器学家的培训和多样性，这是一个历史上同质的群体。每年约有30名AstroTech参与者将是一个多元化的群体，其中约75%是女性或代表性不足的少数族裔学生。世界上最大的（8米）地面望远镜配备了AO，为黑洞研究提供了最好的天文测量能力。然而，目前来自AO系统的天文测量仅限于~0.1毫弧秒的相对精度和~1毫弧秒的绝对精度。研究人员的目标是将我们获得高精度天体测量的能力提高5倍，使他们能够发现和测量自由漂浮和双星中的大型恒星质量黑洞样本，测量银河系中心超大质量黑洞的旋转，并改进广义相对论在强重力环境中的测试。首先，该团队将通过建立和部署精密校准单元来校准几何扭曲，从而减少最大的天文测量误差项。其次，该团队将通过使用最先进的点扩散函数（PSF）重建技术来改善第二个主要误差，以更好地模拟PSF在空间和时间上的变化。最后，该团队将把机器学习技术应用于AO系统、望远镜、天气监测器和大气监测站的遥测，以了解和优化系统性能，最终提高图像质量。黑洞研究所需要的天体测量改进，也将为天体物理学许多其他领域的新探索奠定基础。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Black holes are one of the most exotic phenomena in astrophysics and represent a breakdown in fundamental physics between gravity and quantum mechanics. At the center of our Galaxy, a supermassive black hole was discovered thanks to high-precision astrometric observations from the world’s largest telescopes – a discovery awarded the Nobel Prize in 2020. In addition to the central black hole, the Milky Way Galaxy likely contains between ten million and a billion stellar-mass black holes, or black holes with masses a few times that of the Sun. To date, isolated stellar-mass black holes have not been definitively detected and only two dozen black holes have measured masses – all in binaries. Fundamentally, the study of black holes, both large and small, depends on our ability to make extremely precise measurements of the motions of stars on the plane of the sky. A research group at the University of California-Berkeley will improve our ability to make such measurements using adaptive optics (AO) they are developing to remove the blurring of the Earth’s atmosphere at the W. M. Keck Observatory telescopes. The investigators will also enhance the training and diversity of the next generation of astronomical instrumentalists, a historically homogeneous group, through an expansion of the AstroTech program to include sessions that bridge between the one-week summer school and external internship programs. The roughly 30 AstroTech participants each year will be a diverse cohort with an estimated 75% women or under-represented minority students. The world’s largest ( 8 m), ground-based telescopes equipped with AO deliver the best astrometric capabilities for black hole studies. However, current astrometric measurements from AO systems are limited to a relative precision of ~0.1 milli-arcseconds and an absolute precision of ~1 milli-arcseconds. The investigators aim to improve our ability to obtain high-precision astrometric measurements by a factor of 5X, allowing them to find and weigh large samples of stellar mass black holes both free-floating and in binaries, measure the spin of the supermassive black hole at the Galactic Center, and improve tests of General Relativity in a strong-gravity environment. First, the team will reduce the largest astrometric error term by building and deploying a precision calibration unit to calibrate geometric distortions. Second, the team will improve the second dominant error by using state-of-the-art point-spread-function (PSF) reconstruction techniques to better model the PSF variability in space and time. Finally, the team will apply machine learning techniques to telemetry from the AO system, telescope, weather monitors, and atmospheric monitoring stations in order to learn about and optimize system performance, ultimately improving the image quality. The proposed astrometric improvements, needed for black hole studies, will also lay a foundation for new explorations in many other areas of astrophysics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.