Machine-learning interpolation of population-synthesis simulations to interpret gravitational-wave observations: A case study

We report on advances to interpret current and future gravitational-wave events in light of astrophysical simulations. A machine-learning emulator is trained on numerical population-synthesis predictions and inserted into a Bayesian hierarchical framework. In this case study, a modest but state-of-the-art suite of simulations of isolated binary stars is interpolated across two event parameters and one population parameter. The validation process of our pipelines highlights how omitting some of the event parameters might cause errors in estimating selection effects, which propagates as systematics to the final population inference. Using LIGO/Virgo data from O1 and O2 we infer that black holes in binaries are most likely to receive natal kicks with one-dimensional velocity dispersion $\sigma$ = 105+44 km/s. Our results showcase potential applications of machine-learning tools in conjunction with population-synthesis simulations and gravitational-wave data.Comment: 6 pages, 3 figure

Precise LIGO Lensing Rate Predictions for Binary Black Holes

We show how LIGO is expected to detect coalescing binary black holes at $z>1$, that are lensed by the intervening galaxy population. Gravitational magnification, $\mu$, strengthens gravitational wave signals by $\sqrt{\mu}$, without altering their frequencies, which if unrecognised leads to an underestimate of the event redshift and hence an overestimate of the binary mass. High magnifications can be reached for coalescing binaries because the region of intense gravitational wave emission during coalescence is so small ($\sim$100km), permitting very close projections between lensing caustics and gravitational-wave events. Our simulations incorporate accurate waveforms convolved with the LIGO power spectral density. Importantly, we include the detection dependence on sky position and orbital orientation, which for the LIGO configuration translates into a wide spread in observed redshifts and chirp masses. Currently we estimate a detectable rate of lensed events \rateEarly{}, that rises to \rateDesign{}, at LIGO's design sensitivity limit, depending on the high redshift rate of black hole coalescence.Comment: 5 pages, 4 figure

Distinguishing double neutron star from neutron star-black hole binary populations with gravitational wave observations

Gravitational waves from the merger of two neutron stars cannot be easily distinguished from those produced by a comparable-mass mixed binary in which one of the companions is a black hole. Low-mass black holes are interesting because they could form in the aftermath of the coalescence of two neutron stars, from the collapse of massive stars, from matter overdensities in the primordial Universe, or as the outcome of the interaction between neutron stars and dark matter. Gravitational waves carry the imprint of the internal composition of neutron stars via the so-called tidal deformability parameter, which depends on the stellar equation of state and is equal to zero for black holes. We present a new data analysis strategy powered by Bayesian inference and machine learning to identify mixed binaries, hence low-mass black holes, using the distribution of the tidal deformability parameter inferred from gravitational-wave observations.Comment: 13 pages, 6 figures - v2: matches the published version in Phys. Rev. D 102, 02302

Multiband gravitational-wave event rates and stellar physics

Joint gravitational-wave detections of stellar-mass black-hole binaries by ground- and space-based observatories will provide unprecedented opportunities for fundamental physics and astronomy. We present a semianalytic method to estimate multiband event rates by combining selection effects of ground-based interferometers (like LIGO/Virgo) and space missions (like LISA). We forecast the expected number of multiband detections first by using information from current LIGO/Virgo data, and then through population synthesis simulations of binary stars. We estimate that few to tens of LISA detections can be used to predict mergers detectable on the ground. Conversely, hundreds of events could potentially be extracted from the LISA data stream using prior information from ground detections. In general, the merger signal of binaries observable by LISA is strong enough to be unambiguously identified by both current and future ground-based detectors. Therefore third-generation detectors will not increase the number of multiband detections compared to LIGO/Virgo. We use population synthesis simulations of isolated binary stars to explore some of the stellar physics that could be constrained with multiband events, and we show that specific formation pathways might be overrepresented in multiband events compared to ground-only detections.Comment: 17 pages, 11 figures. Database and python code available at https://github.com/dgerosa/spops - Published in PR