Related papers: Machine-learning interpolation of population-synth…
Inferring the intrinsic population of compact binary mergers is complicated by detector selection biases and measurement uncertainties. Traditional parametric methods are limited by the need to presuppose functional forms, introducing…
Spectral-sirens inference enables the extraction of cosmological parameters from gravitational-wave data alone, without electromagnetic counterparts or galaxy catalogs. We introduce new parametric mass functions for the binary black hole…
We combine amortized neural posterior estimation with importance sampling for fast and accurate gravitational-wave inference. We first generate a rapid proposal for the Bayesian posterior using neural networks, and then attach importance…
We describe a Bayesian formalism for analyzing individual gravitational-wave events in light of the rest of an observed population. This analysis reveals how the idea of a "population-informed prior" arises naturally from a suitable…
Gravitational-wave events are interpreted in terms of Bayesian posteriors for their source properties inferred under unphysical reference priors. Though these parameter estimates are important intermediate data products for downstream…
The work presented here examines populations of double compact binary systems and tidally enhanced collapsars. We make use of BINPOP and BINKIN, two components of a recently developed population synthesis package. Results focus on…
Recently discovered bursts of gravitational waves provide a good opportunity to verify the current view on the evolution of close binary stars. Modern population synthesis computer programs help to study this evolution from two main…
From catalogs of gravitational-wave transients, the population-level properties of their sources and the formation channels of merging compact binaries can be constrained. However, astrophysical conclusions can be biased by misspecification…
Strong lensing of gravitational waves can produce several detectable images as repeated events in the upcoming observing runs, which can be detected with the posterior overlap analysis (Bayes factor). The choice of the binary black hole…
One of the key challenges of real-time detection and parameter estimation of gravitational waves from compact binary mergers is the computational cost of conventional matched-filtering and Bayesian inference approaches. In particular, the…
We combine hierarchical Bayesian modeling with a flow-based deep generative network, in order to demonstrate that one can efficiently constraint numerical gravitational wave (GW) population models at a previously intractable complexity.…
In the last five years, gravitational-wave astronomy has gone from a purely theoretical field into a thriving experimental science. Many gravitational-wave signals, emitted by stellar-mass binary black holes and binary neutron stars, have…
The LIGO and Virgo gravitational-wave observatories have detected many exciting events over the past five years. As the rate of detections grows with detector sensitivity, this poses a growing computational challenge for data analysis. With…
Study of gravitational-radiation induced merging rates of relativistic binary stars (double neutron stars; neutron star + black hole; double black holes) shows that the first-generation gravitational wave interferometers with an…
Gravitational-wave detections have revealed a previously unknown population of stellar mass black holes with masses above $20\, M_{\odot}$. These observations provide a new way to test models of stellar evolution for massive stars. By…
We introduce a new technique to search for gravitational wave events from compact binary mergers that produce a clear signal only in a single gravitational wave detector, and marginal signals in other detectors. Such a situation can arise…
Gravitational memory is an important prediction of classical General Relativity, which is intimately related to asymptotic symmetries at null infinity and the so-called soft graviton theorem first shown by Weinberg. For a given transient…
We introduce a technique for gravitational-wave analysis, where Gaussian process regression is used to emulate the strain spectrum of a stochastic background using population-synthesis simulations. This leads to direct Bayesian inference on…
We reanalyse the LIGO-Virgo strain data of the 10 binary black hole mergers reported to date and compute the likelihood function in terms of chirp mass, mass ratio and effective spin. We discuss the strong degeneracy between mass ratio and…
The Advanced LIGO observatory recently reported (Abbott et al., 2016a) the first direct detection of gravitational waves predicted by Einstein (1916). The detection of this event was predicted in 1997 on the basis of the Scenario Machine…