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.
Identifying heavy stellar black holes at cosmological distances with next-generation gravitational-wave observatories
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ET-Δ outperforms ET-2L on luminosity distance and source-frame masses for BBH events because its redundancy produces higher multi-detector uptime under realistic duty-cycle modeling.
LGWA could observe more than one third of known binary black hole events, detect ~90 mergers per year, and measure chirp mass better than third-generation detectors for massive systems.
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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Impact of the Einstein Telescope's duty cycle on the estimation of binary black holes parameters
ET-Δ outperforms ET-2L on luminosity distance and source-frame masses for BBH events because its redundancy produces higher multi-detector uptime under realistic duty-cycle modeling.
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Gravitational-wave parameter estimation to the Moon and back: massive binaries and the case of GW231123
LGWA could observe more than one third of known binary black hole events, detect ~90 mergers per year, and measure chirp mass better than third-generation detectors for massive systems.