Accelerated inference of binary black-hole populations from the stochastic gravitational-wave background

Now, there are a lot of black holes out there. So many that their gravitational-wave signals won’t even be separable, all piling up on top of each other (if/when we’ll have a detector to pick that up). Analyzing this stochastic background can tell us about the details of those black holes; that’s the good old “population” problem in GW astronomy, here tackled in a different way. And, why not, let’s throw in a neural network.

G. Giarda, A. I. Renzini, C. Pacilio, D. Gerosa.
arXiv:2506.12572 [gr-qc].