Adaptive Optics Astrometry for Black Hole Science

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.