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Some analyses of the third gravitational wave catalogue released by the LIGO-Virgo-KAGRA collaboration (LVK) suggest an excess of black holes around $15\!-\!20 \, {\rm M}_{\odot }$. In order to investigate this feature, we introduce two flexible population models, a semiparametric one and a non-parametric one. Both make use of reversible jump Markov chain Monte-Carlo to optimise their complexity. We also illustrate how the latter can be used to efficiently perform model selection. Our parametric model broadly agrees with the fiducial analysis of the LVK, but finds a peak of events at slightly larger masses. Our non-parametric model shows this same displacement. Moreover, it also suggests the existence of an excess of black holes around $20 \, {\rm M}_{\odot }$. We assess the robustness of this prediction by performing mock injections and running simplified hierarchical analyses on those (i.e. without selection effects and observational uncertainties). We estimate that such a feature might be due to statistical fluctuations, given the small number of events observed so far, with a 5 per cent probability. We estimate that with a few hundreds of observations, as expected for O4, our non-parametric model will be able to robustly determine the presence of this excess. It will then allow for an efficient agnostic inference of the properties of black holes.

 

We derive a Fisher matrix for the parameters characterizing a population of gravitational-wave events. This provides a guide to the precision with which population parameters can be estimated with multiple observations, which becomes increasingly accurate as the number of events and the signal-to-noise ratio of the sampled events increase. The formalism takes into account individual event measurement uncertainties and selection effects, and can be applied to arbitrary population models. We illustrate the framework with two examples: an analytical calculation of the Fisher matrix for the mean and variance of a Gaussian model describing a population affected by selection effects, and an estimation of the precision with which the slope of a power-law distribution of supermassive black hole masses can be measured using extreme-mass-ratio inspiral observations. We compare the Fisher predictions to results from Monte Carlo analyses, finding very good agreement.

 

The search for gravitational waves using Pulsar Timing Arrays (PTAs) is a computationally expensive complex analysis that involves source-specific noise studies. As more pulsars are added to the arrays, this stage of PTA analysis will become increasingly challenging. Therefore, optimizing the number of included pulsars is crucial to reduce the computational burden of data analysis. Here, we present a suite of methods to rank pulsars for use within the scope of PTA analysis. First, we use the maximization of the signal-to-noise ratio as a proxy to select pulsars. With this method, we target the detection of stochastic and continuous gravitational wave signals. Next, we present a ranking that minimizes the coupling between spatial correlation signatures, namely monopolar, dipolar, and Hellings & Downs correlations. Finally, we also explore how to combine these two methods. We test these approaches against mock data using frequentist and Bayesian hypothesis testing. For equal-noise pulsars, we find that an optimal selection leads to an increase in the log-Bayes factor two times steeper than a random selection for the hypothesis test of a gravitational wave background versus a common uncorrelated red noise process. For the same test but for a realistic European PTA (EPTA) data set, a subset of 25 pulsars selected out of 40 can provide a log-likelihood ratio that is 89 % of the total, implying that an optimally selected subset of pulsars can yield results comparable to those obtained from the whole array. We expect these selection methods to play a crucial role in future PTA data combinations.

 

Standard sirens have been the central paradigm in gravitational-wave cosmology so far. From the gravitational wave signature of compact star binaries, it is possible to measure the luminosity distance of the source directly, and if additional information on the source redshift is provided, a measurement of the cosmological expansion can be performed. This review article discusses several methodologies that have been proposed to use gravitational waves for cosmological studies. Methods that use only gravitational-wave signals and methods that use gravitational waves in conjunction with additional observations such as electromagnetic counterparts and galaxy catalogs will be discussed. The review also discusses the most recent results on gravitational-wave cosmology, starting from the binary neutron star merger GW170817 and its electromagnetic counterpart and finishing with the population of binary black holes, observed with the third Gravitational-wave Transient Catalog GWTC–3. 

Abstract We outline the “dark siren” galaxy catalog method for cosmological inference using gravitational wave (GW) standard sirens, clarifying some common misconceptions in the implementation of this method. When a confident transient electromagnetic counterpart to a GW event is unavailable, the identification of a unique host galaxy is in general challenging. Instead, as originally proposed by Schutz, one can consult a galaxy catalog and implement a dark siren statistical approach incorporating all potential host galaxies within the localization volume. Trott & Huterer recently claimed that this approach results in a biased estimate of the Hubble constant, H 0 , when implemented on mock data, even if optimistic assumptions are made. We demonstrate explicitly that, as previously shown by multiple independent groups, the dark siren statistical method leads to an unbiased posterior when the method is applied to the data correctly. We highlight common sources of error possible to make in the generation of mock data and implementation of the statistical framework, including the mismodeling of selection effects and inconsistent implementations of the Bayesian framework, which can lead to a spurious bias. 

Abstract Using ground-based gravitational-wave detectors, we probe the mass function of intermediate-mass black holes (IMBHs) wherein we also include BHs in the upper mass gap at ∼60–130 M ⊙ . Employing the projected sensitivity of the upcoming LIGO and Virgo fourth observing run (O4), we perform Bayesian analysis on quasi-circular nonprecessing, spinning IMBH binaries (IMBHBs) with total masses 50–500 M ⊙ , mass ratios 1.25, 4, and 10, and dimensionless spins up to 0.95, and estimate the precision with which the source-frame parameters can be measured. We find that, at 2 σ , the mass of the heavier component of IMBHBs can be constrained with an uncertainty of ∼10%–40% at a signal-to-noise ratio of 20. Focusing on the stellar-mass gap with new tabulations of the 12 C( α , γ ) 16 O reaction rate and its uncertainties, we evolve massive helium core stars using MESA to establish the lower and upper edges of the mass gap as ≃ 59 − 13 + 34 M ⊙ and ≃ 139 − 14 + 30 M ⊙ respectively, where the error bars give the mass range that follows from the ±3 σ uncertainty in the 12 C( α , γ ) 16 O nuclear reaction rate. We find that high resolution of the tabulated reaction rate and fine temporal resolution are necessary to resolve the peak of the BH mass spectrum. We then study IMBHBs with components lying in the mass gap and show that the O4 run will be able to robustly identify most such systems. Finally, we reanalyze GW190521 with a state-of-the-art aligned-spin waveform model, finding that the primary mass lies in the mass gap with 90% credibility.