Search for: All records

Since the first direct detection of gravitational waves by the LIGO–Virgo collaboration in 2015 (B. P. Abbott et al., 2016), the size of the gravitational-wave transient catalog has grown to nearly 100 events (R. Abbott et al., 2023), with the ongoing fourth observing run more than doubling the total number. Extracting astrophysical or cosmological information from these observations is a hierarchical Bayesian inference problem. GWPopulation is designed to provide simple-to-use, robust, and extensible tools for hierarchical inference in gravitational-wave astronomy or cosmology. It has been widely adopted for gravitational-wave astronomy, including producing flagship results for the LIGO-Virgo-KAGRA collaborations (Abac et al., 2024; R. Abbott et al., 2023). While designed to work with observations of compact binary coalescences, GWPopulation may be available to a wider range of hierarchical Bayesian inference problems. 

Abstract The detection of a sub-solar mass black hole could yield dramatic new insights into the nature of dark matter and early-Universe physics, as such objects lack a traditional astrophysical formation mechanism. Gravitational waves allow for the direct measurement of compact object masses during binary mergers, and we expect the gravitational-wave signal from a low-mass coalescence to remain within the LIGO frequency band for thousands of seconds. However, it is unclear whether one can confidently measure the properties of a sub-solar mass compact object and distinguish between a sub-solar mass black hole or other exotic objects. To this end, we perform Bayesian parameter estimation on simulated gravitational-wave signals from sub-solar mass black hole mergers to explore the measurability of their source properties. We find that the LIGO/Virgo detectors during the O4 observing run would be able to confidently identify sub-solar component masses at the threshold of detectability; these events would also be well-localized on the sky and may reveal some information on their binary spin geometry. Further, next-generation detectors such as Cosmic Explorer and the Einstein Telescope will allow for precision measurement of the properties of sub-solar mass mergers and tighter constraints on their compact-object nature. 

ABSTRACT Observations of gravitational waves emitted by merging compact binaries have provided tantalizing hints about stellar astrophysics, cosmology, and fundamental physics. However, the physical parameters describing the systems (mass, spin, distance) used to extract these inferences about the Universe are subject to large uncertainties. The most widely used method of performing these analyses requires performing many Monte Carlo integrals to marginalize over the uncertainty in the properties of the individual binaries and the survey selection bias. These Monte Carlo integrals are subject to fundamental statistical uncertainties. Previous treatments of this statistical uncertainty have focused on ensuring that the precision of the inferred inference is unaffected; however, these works have neglected the question of whether sufficient accuracy can also be achieved. In this work, we provide a practical exploration of the impact of uncertainty in our analyses and provide a suggested framework for verifying that astrophysical inferences made with the gravitational-wave transient catalogue are accurate. Applying our framework to models used by the LIGO–Virgo–KAGRA collaboration and in the wider literature, we find that Monte Carlo uncertainty in estimating the survey selection bias is the limiting factor in our ability to probe narrow population models and this will rapidly grow more problematic as the size of the observed population increases. 

ABSTRACT The global network of interferometric gravitational wave (GW) observatories (LIGO, Virgo, KAGRA) has detected and characterized nearly 100 mergers of binary compact objects. However, many more real GWs are lurking sub-threshold, which need to be sifted from terrestrial-origin noise triggers (known as glitches). Because glitches are not due to astrophysical phenomena, inference on the glitch under the assumption it has an astrophysical source (e.g. binary black hole coalescence) results in source parameters that are inconsistent with what is known about the astrophysical population. In this work, we show how one can extract unbiased population constraints from a catalogue of both real GW events and glitch contaminants by performing Bayesian inference on their source populations simultaneously. In this paper, we assume glitches come from a specific class with a well-characterized effective population (blip glitches). We also calculate posteriors on the probability of each event in the catalogue belonging to the astrophysical or glitch class, and obtain posteriors on the number of astrophysical events in the catalogue, finding it to be consistent with the actual number of events included. 

Context. The growing set of gravitational-wave sources is being used to measure the properties of the underlying astrophysical populations of compact objects, black holes, and neutron stars. Most of the detected systems are black hole binaries. While much has been learned about black holes by analyzing the latest LIGO-Virgo-KAGRA (LVK) catalog, GWTC-3, a measurement of the astrophysical distribution of the black hole spin orientations remains elusive. This is usually probed by measuring the cosine of the tilt angle (cos τ ) between each black hole spin and the orbital angular momentum, with cos τ  = +1 being perfect alignment. Aims. The LVK Collaboration has modeled the cos τ distribution as a mixture of an isotropic component and a Gaussian component with mean fixed at +1 and width measured from the data. We want to verify if the data require the existence of such a peak at cos τ  = +1. Methods. We used various alternative models for the astrophysical tilt distribution and measured their parameters using the LVK GWTC-3 catalog. Results. We find that (a) augmenting the LVK model, such that the mean μ of the Gaussian is not fixed at +1, returns results that strongly depend on priors. If we allow μ  >  +1, then the resulting astrophysical cos τ distribution peaks at +1 and looks linear, rather than Gaussian. If we constrain −1 ≤  μ  ≤ +1, the Gaussian component peaks at μ  = 0.48 −0.99 +0.46 (median and 90% symmetric credible interval). Two other two-component mixture models yield cos τ distributions that either have a broad peak centered at 0.19 −0.18 +0.22 or a plateau that spans the range [ − 0.5, +1], without a clear peak at +1. (b) All of the models we considered agree as to there being no excess of black hole tilts at around −1. (c) While yielding quite different posteriors, the models considered in this work have Bayesian evidences that are the same within error bars. Conclusions. We conclude that the current dataset is not sufficiently informative to draw any model-independent conclusions on the astrophysical distribution of spin tilts, except that there is no excess of spins with negatively aligned tilts.