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Abstract Gravitational-wave observations provide the unique opportunity of studying black hole formation channels and histories—but only if we can identify their origin. One such formation mechanism is the dynamical synthesis of black hole binaries in dense stellar systems. Given the expected isotropic distribution of component spins of binary black holes in gas-free dynamical environments, the presence of antialigned or in-plane spins with respect to the orbital angular momentum is considered a tell-tale sign of a merger’s dynamical origin. Even in the scenario where birth spins of black holes are low, hierarchical mergers attain large component spins due to the orbital angular momentum of the prior merger. However, measuring such spin configurations is difficult. Here, we quantify the efficacy of the spin parameters encoding aligned-spin (χ_eff) and in-plane spin (χ_p) at classifying such hierarchical systems. Using Monte Carlo cluster simulations to generate a realistic distribution of hierarchical merger parameters from globular clusters, we can infer mergers’χ_effandχ_p. The cluster populations are simulated using Advanced LIGO-Virgo sensitivity during the detector network’s third observing period and projections for design sensitivity. Using a “likelihood-ratio”-based statistic, we find that ∼2% of the recovered population by the current gravitational-wave detector network has a statistically significantχ_pmeasurement, whereas noχ_effmeasurement was capable of confidently determining a system to be antialigned with the orbital angular momentum at current detector sensitivities. These results indicate that measuring spin-precession throughχ_pis a more detectable signature of hierarchical mergers and dynamical formation than antialigned spins. 

Abstract The Gravity Spy project aims to uncover the origins of glitches, transient bursts of noise that hamper analysis of gravitational-wave data. By using both the work of citizen-science volunteers and machine learning algorithms, the Gravity Spy project enables reliable classification of glitches. Citizen science and machine learning are intrinsically coupled within the Gravity Spy framework, with machine learning classifications providing a rapid first-pass classification of the dataset and enabling tiered volunteer training, and volunteer-based classifications verifying the machine classifications, bolstering the machine learning training set and identifying new morphological classes of glitches. These classifications are now routinely used in studies characterizing the performance of the LIGO gravitational-wave detectors. Providing the volunteers with a training framework that teaches them to classify a wide range of glitches, as well as additional tools to aid their investigations of interesting glitches, empowers them to make discoveries of new classes of glitches. This demonstrates that, when giving suitable support, volunteers can go beyond simple classification tasks to identify new features in data at a level comparable to domain experts. The Gravity Spy project is now providing volunteers with more complicated data that includes auxiliary monitors of the detector to identify the root cause of glitches. 

Abstract The formation histories of compact binary mergers, especially stellar-mass binary black hole mergers, have recently come under increased scrutiny and revision. We revisit the question of the dominant formation channel and efficiency of forming binary neutron star (BNS) mergers. We use the stellar and binary evolution codeMESAand implement a detailed method for common envelope and mass transfer. We perform simulations for donor masses between 7 M_⊙and 20 M_⊙with a neutron star (NS) companion of 1.4 M_⊙and 2.0 M_⊙ at two metallicities, using varying common envelope efficiencies and two different prescriptions to determine if the donor undergoes core collapse or electron capture, given their helium and carbon–oxygen cores. In contrast to the case of binary black hole mergers, for an NS companion of 1.4 M_⊙, all BNS mergers are formed following a common envelope phase. For an NS mass of 2.0 M_⊙, we identify a small subset of mergers following only stable mass transfer if the NS receives a natal kick sampled from a Maxwellian distribution with velocity dispersionσ= 265 km s⁻¹. Regardless of the supernova prescription, we find more BNS mergers at subsolar metallicity compared to solar. 

Abstract In their most recent observing run, the LIGO-Virgo-KAGRA Collaboration observed gravitational waves from compact binary mergers with highly asymmetric mass ratios, including both binary black holes (BBHs) and neutron star-black holes (NSBHs). It appears that NSBHs with mass ratiosq≃ 0.2 are more common than equally asymmetric BBHs, but the reason for this remains unclear. We use the binary population synthesis codecosmicto investigate the evolutionary pathways leading to the formation and merger of asymmetric compact binaries. We find that within the context of isolated binary stellar evolution, most asymmetric mergers start off as asymmetric stellar binaries. Because of the initial asymmetry, these systems tend to first undergo a dynamically unstable mass transfer phase. However, after the first star collapses into a compact object, the mass ratio is close to unity and the second phase of mass transfer is usually stable. According to our simulations, this stable mass transfer fails to shrink the orbit enough on its own for the system to merge. Instead, the natal kick received by the second-born compact object during its collapse is key in determining how many of these systems can merge. For the most asymmetric systems with mass ratios ofq≤ 0.1, the merging systems in our models receive an average kick magnitude of 255 km s⁻¹during the second collapse, while the average kick for non-merging systems is 59 km s⁻¹. Because lower mass compact objects, like neutron stars, are expected to receive larger natal kicks than higher mass BHs, this may explain why asymmetric NSBH systems merge more frequently than asymmetric BBH systems. 

Abstract There are few observed high-mass X-ray binaries (HMXBs) that harbor massive black holes (BHs), and none are likely to result in a binary black hole (BBH) that merges within a Hubble time; however, we know that massive merging BBHs exist from gravitational-wave (GW) observations. We investigate the role that X-ray and GW observational selection effects play in determining the properties of their respective detected binary populations. We find that, as a result of selection effects, detectable HMXBs and detectable BBHs form at different redshifts and metallicities, with detectable HMXBs forming at much lower redshifts and higher metallicities than detectable BBHs. We also find disparities in the mass distributions of these populations, with detectable merging BBH progenitors pulling to higher component masses relative to the full detectable HMXB population. Fewer than 3% of detectable HMXBs host BHs >35M_⊙in our simulated populations. Furthermore, we find the probability that a detectable HMXB will merge as a BBH system within a Hubble time is ≃0.6%. Thus, it is unsurprising that no currently observed HMXB is predicted to form a merging BBH with high probability. 

Abstract Understanding the noise in gravitational-wave detectors is central to detecting and interpreting gravitational-wave signals. Glitches are transient, non-Gaussian noise features that can have a range of environmental and instrumental origins. The Gravity Spy project uses a machine-learning algorithm to classify glitches based upon their time–frequency morphology. The resulting set of classified glitches can be used as input to detector-characterisation investigations of how to mitigate glitches, or data-analysis studies of how to ameliorate the impact of glitches. Here we present the results of the Gravity Spy analysis of data up to the end of the third observing run of advanced laser interferometric gravitational-wave observatory (LIGO). We classify 233981 glitches from LIGO Hanford and 379805 glitches from LIGO Livingston into morphological classes. We find that the distribution of glitches differs between the two LIGO sites. This highlights the potential need for studies of data quality to be individually tailored to each gravitational-wave observatory. 

Abstract We introduce the first complete nonparametric model for the astrophysical distribution of the binary black hole (BBH) population. Constructed from basis splines, we use these models to conduct the most comprehensive data-driven investigation of the BBH population to date, simultaneously fitting nonparametric models for the BBH mass ratio, spin magnitude and misalignment, and redshift distributions. With GWTC-3, we report the same features previously recovered with similarly flexible models of the mass distribution, most notably the peaks in merger rates at primary masses of ∼10M_⊙and ∼35M_⊙. Our model reports a suppressed merger rate at low primary masses and a mass-ratio distribution consistent with a power law. We infer a distribution for primary spin misalignments that peaks away from alignment, supporting conclusions of recent work. We find broad agreement with the previous inferences of the spin magnitude distribution: the majority of BBH spins are small (a< 0.5), the distribution peaks ata∼ 0.2, and there is mild support for a nonspinning subpopulation, which may be resolved with larger catalogs. With a modulated power law describing the BBH merger rate’s evolution in redshift, we see hints of the rate evolution either flattening or decreasing atz∼ 0.2–0.5, but the full distribution remains entirely consistent with a monotonically increasing power law. We conclude with a discussion of the astrophysical context of our new findings and how nonparametric methods in gravitational-wave population inference are uniquely poised to complement to the parametric approach as we enter the data-rich era of gravitational-wave astronomy.