Asymmetric emission of gravitational waves during mergers of black holes (BHs) produces a recoil kick, which can set a newly formed BH on a bound orbit around the centre of its host galaxy, or even completely eject it. To study this population of recoiling BHs we extract properties of galaxies with merging BHs from Illustris TNG300 simulation and then employ both analytical and numerical techniques to model unresolved process of BH recoil. This comparative analysis between analytical and numerical models shows that, on cosmological scales, numerically modelled recoiling BHs have a higher escape probability and predict a greater number of offset active galactic nuclei (AGN). BH escaped probability $>$40% is expected in 25$\%$ of merger remnants in numerical models, compared to 8$\%$ in analytical models. At the same time, the predicted number of offset AGN at separations ${>}5$ kpc changes from 58$\%$ for numerical models to 3$\%$ for analytical models. Since BH ejections in major merger remnants occur in non-virialised systems, static analytical models cannot provide an accurate description. Thus we argue that numerical models should be used to estimate the expected number density of escaped BHs and offset AGN.

The rapid formation of supermassive black holes (SMBHs) at high redshifts is still a puzzle. One hypothesis is that intermediate-mass black holes (IMBHs) serve as seeds for their formation, which could arise from hierarchical mergers in dense star clusters. There are two possible pathways for IMBH formation: 1) very massive stars may form in young star clusters, such as Pop3 clusters, and evolve into IMBHs within a few million years; 2) multiple stellar-mass black holes can merge into IMBHs in dense nuclear star clusters. Detailed insights into these scenarios can be obtained through high-resolution star-by-star simulations of dense star clusters. Furthermore, upcoming observations of faint quasars, nuclear star clusters, and Pop3 stars with the James Webb Space Telescope (JWST) will offer valuable data to constrain theoretical models and deepen our understanding of the rapid formation of SMBHs.

Bayesian inference is a powerful tool in gravitational-wave astronomy. It enables us to deduce the properties of merging compact-object binaries and to determine how these mergers are distributed as a population according to mass, spin, and redshift. As key results are increasingly derived using Bayesian inference, there is increasing scrutiny on Bayesian methods. In this review, we discuss the phenomenon of model misspecification, in which results obtained with Bayesian inference are misleading because of deficiencies in the assumed model(s). Such deficiencies can impede our inferences of the true parameters describing physical systems. They can also reduce our ability to distinguish the ‘best fitting’ model: it can be misleading to say that Model A is preferred over Model B if both models are manifestly poor descriptions of reality. Broadly speaking, there are two ways in which models fail. Firstly, models that fail to adequately describe the data (either the signal or the noise) have misspecified likelihoods. Secondly, population models—designed, for example, to describe the distribution of black hole masses—may fail to adequately describe the true population due to a misspecified prior. We recommend tests and checks that are useful for spotting misspecified models using examples inspired by gravitational-wave astronomy. We include companion python notebooks to illustrate essential concepts.

Massive stars are predominantly found in binaries and higher order multiples. While the period and eccentricity distributions of OB stars are now well established across different metallicity regimes, the determination of mass-ratios has been mostly limited to double-lined spectroscopic binaries. As a consequence, the mass-ratio distribution remains subject to significant uncertainties. Open questions include the shape and extent of the companion mass-function towards its low-mass end and the nature of undetected companions in single-lined spectroscopic binaries. In this contribution, we present the results of a large and systematic analysis of a sample of over 80 single-lined O-type spectroscopic binaries (SB1s) in the Milky Way and in the Large Magellanic Cloud (LMC). We report on the developed methodology, the constraints obtained on the nature of SB1 companions, the distribution of O star mass-ratios at LMC metallicity and the occurrence of quiescent OB+black hole binaries.

Proposed next-generation networks of gravitational-wave observatories include dedicated kilohertz instruments that target neutron star science, such as the proposed Neutron Star Extreme Matter Observatory, NEMO. The original proposal for NEMO highlighted the need for it to exist in a network of gravitational-wave observatories to ensure detection confidence and sky localisation of sources. We show that NEMO-like observatories have significant utility on their own as coincident electromagnetic observations can provide the detection significance and sky localisation. We show that, with a single NEMO-like detector and expected electromagnetic observatories in the late 2020 s and early 2030 s such as the Vera C. Rubin observatory and SVOM, approximately 40% of all binary neutron star mergers detected with gravitational waves could be confidently identified as coincident multimessenger detections. We show that we expect $2^{+10}_{-1}{yr^{-1}}{}$ coincident observations of gravitational-wave mergers with gamma-ray burst prompt emission, $13^{+23}_{-10}{yr^{-1}}{}$ detections with kilonova observations, and $4^{+18}_{-3}{yr^{-1}}{}$ with broadband afterglows and kilonovae, where the uncertainties are 90% confidence intervals arising from uncertainty in current merger-rate estimates. Combined, this implies a coincident detection rate of $14^{+25}_{-11}{yr^{-1}}{}$ out to $300\,\mathrm{Mpc}$ . These numbers indicate significant science potential for a single kilohertz gravitational-wave detector operating without a global network of other gravitational-wave observatories.

We present an overview of the SkyMapper optical follow-up programme for gravitational-wave event triggers from the LIGO/Virgo observatories, which aims at identifying early GW170817-like kilonovae out to $\sim200\,\mathrm{Mpc}$ distance. We describe our robotic facility for rapid transient follow-up, which can target most of the sky at $\delta<+10\deg $ to a depth of $i_\mathrm{AB}\approx 20\,\mathrm{mag}$ . We have implemented a new software pipeline to receive LIGO/Virgo alerts, schedule observations and examine the incoming real-time data stream for transient candidates. We adopt a real-bogus classifier using ensemble-based machine learning techniques, attaining high completeness ( $\sim98\%$ ) and purity ( $\sim91\%$ ) over our whole magnitude range. Applying further filtering to remove common image artefacts and known sources of transients, such as asteroids and variable stars, reduces the number of candidates by a factor of more than 10. We demonstrate the system performance with data obtained for GW190425, a binary neutron star merger detected during the LIGO/Virgo O3 observing campaign. In time for the LIGO/Virgo O4 run, we will have deeper reference images allowing transient detection to $i_\mathrm{AB}\approx 21\,\mathrm{mag}$ .

We discuss observational strategies to detect prompt bursts associated with gravitational wave (GW) events using the Australian Square Kilometre Array Pathfinder (ASKAP). Many theoretical models of binary neutron stars mergers predict that bright, prompt radio emission would accompany the merger. The detection of such prompt emission would greatly improve our knowledge of the physical conditions, environment, and location of the merger. However, searches for prompt emission are complicated by the relatively poor localisation for GW events, with the 90% credible region reaching hundreds or even thousands of square degrees. Operating in fly’s eye mode, the ASKAP field of view can reach $\sim1\,000$ deg$^2$ at $\sim$$888\,{\rm MHz}$. This potentially allows observers to cover most of the 90% credible region quickly enough to detect prompt emission. We use skymaps for GW170817 and GW190814 from LIGO/Virgo’s third observing run to simulate the probability of detecting prompt emission for GW events in the upcoming fourth observing run. With only alerts released after merger, we find it difficult to slew the telescope sufficiently quickly as to capture any prompt emission. However, with the addition of alerts released before merger by negative-latency pipelines, we find that it should be possible to search for nearby, bright prompt fast radio burst-like emission from GW events. Nonetheless, the rates are low: we would expect to observe $\sim$0.012 events during the fourth observing run, assuming that the prompt emission is emitted microseconds around the merger.

We describe 14 yr of public data from the Parkes Pulsar Timing Array (PPTA), an ongoing project that is producing precise measurements of pulse times of arrival from 26 millisecond pulsars using the 64-m Parkes radio telescope with a cadence of approximately 3 weeks in three observing bands. A comprehensive description of the pulsar observing systems employed at the telescope since 2004 is provided, including the calibration methodology and an analysis of the stability of system components. We attempt to provide full accounting of the reduction from the raw measured Stokes parameters to pulse times of arrival to aid third parties in reproducing our results. This conversion is encapsulated in a processing pipeline designed to track provenance. Our data products include pulse times of arrival for each of the pulsars along with an initial set of pulsar parameters and noise models. The calibrated pulse profiles and timing template profiles are also available. These data represent almost 21 000 h of recorded data spanning over 14 yr. After accounting for processes that induce time-correlated noise, 22 of the pulsars have weighted root-mean-square timing residuals of $<\!\!1\,\mu\text{s}$ in at least one radio band. The data should allow end users to quickly undertake their own gravitational wave analyses, for example, without having to understand the intricacies of pulsar polarisation calibration or attain a mastery of radio frequency interference mitigation as is required when analysing raw data files.