Machine learning regressors trained on Rapster simulations forecast that globular clusters rarely host black holes above 100 solar masses while a few nuclear star clusters may exceed this threshold.
A Search for Wandering Black Holes in the Milky Way with Gaia and DECaLS
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abstract
We present a search for "hyper-compact" star clusters in the Milky Way using a combination of Gaia and the Dark Energy Camera Legacy Survey (DECaLS). Such putative clusters, with sizes of ~1 pc and containing 500-5000 stars, are expected to remain bound to intermediate-mass black holes (Mbh~10^3-10^5 M-sun) that may be accreted into the Milky Way halo within dwarf satellites. Using the semi-analytic model SatGen we find an expected ~100 wandering intermediate-mass black holes with if every infalling satellite hosts a black hole. We do not find any such clusters in our search. Our upper limits rule out 100% occupancy, but do not put stringent constraints on the occupation fraction. Of course, we need stronger constraints on the properties of the putative star clusters, including their assumed sizes as well as the fraction of stars that would be compact remnants.
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Central black holes in ASTRID and TNG300 follow a tight, redshift-invariant M_BH–M_⋆ relation from z=2 to 0.5; departures mark merger-driven high-mass quenchers, tidally stripped overmassive satellites, and undermassive wanderers.
citing papers explorer
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Predicting intermediate-mass black hole formation in star clusters with machine learning
Machine learning regressors trained on Rapster simulations forecast that globular clusters rarely host black holes above 100 solar masses while a few nuclear star clusters may exceed this threshold.
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Tracing black hole and galaxy growth across environments since cosmic noon
Central black holes in ASTRID and TNG300 follow a tight, redshift-invariant M_BH–M_⋆ relation from z=2 to 0.5; departures mark merger-driven high-mass quenchers, tidally stripped overmassive satellites, and undermassive wanderers.