Year: 2026
Type: preprint
Abstract: Star clusters are born with massive stars that leave behind a large population of stellar mass black holes. These black holes may account for a large fraction of binary black hole mergers seen in gravitational waves as the dense environment enables retention of black holes and the formation of binaries. However, direct measurements of stellar mass black holes in globular clusters are limited, with just a few found in binary systems thus far. In this paper, we examine the possibility of detecting black holes through microlensing in the Milky Way's most massive star cluster, Omega Centauri. We take advantage of a unique dataset of nearly 200 single-band images taken over 13 years with the Hubble Space Telescope to look for the $\sim$1 year long events expected from microlensing of cluster stars by stellar mass black holes. We develop a novel cost function to fit the lensing signatures that we verify using synthetic events, quantifying our completeness. These synthetic events are based on a recent Monte Carlo simulation of Omega Centauri. We also use these synthetic events to train a neural network to most efficiently distinguish observed lensing events. Application of this algorithm to our observed data, and subsequent visual follow-up, show no convincing candidate black hole lensing events. Based on analysis of the simulation data and our completeness, we find that no events would be expected in the data contrary to the expectations from earlier work. We release the photometric dataset used in this work for future use.
Source: arXiv (Cornell University)
Institutions: University of Utah, European Southern Observatory, University of Colorado Boulder, University of North Carolina at Chapel Hill, Northwestern University, Space Telescope Science Institute, Max Planck Institute for Astronomy, Liverpool John Moores University, Osservatorio Astronomico di Padova, National Institute for Astrophysics, Michigan State University
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7223381718