Abstract We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-wave Optical Transient Observer (GOTO) in its prototype 4-telescope configuration (GOTO-4). While no viable electromagnetic counterpart candidate was identified, we estimate our 3D (volumetric) coverage using test light curves of on- and off-axis gamma-ray bursts and kilonovae. In cases where the source region was observable immediately, GOTO-4 was able to respond to a GW alert in less than a minute. The average time of first observation was 8.79 hours after receiving an alert (9.90 hours after trigger). A mean of 732.3 square degrees were tiled per event, representing on average 45.3 per cent of the LVC probability map, or 70.3 per cent of the observable probability. This coverage will further improve as the facility scales up alongside the localisation performance of the evolving gravitational-wave detector network. Even in its 4-telescope prototype configuration, GOTO is capable of detecting AT2017gfo-like kilonovae beyond 200 Mpc in favourable observing conditions. We cannot currently place meaningful electromagnetic limits on the population of distant ($\hat{D}_L = 1.3$ Gpc) binary black hole mergers because our test models are too faint to recover at this distance. However, as GOTO is upgraded towards its full 32-telescope, 2 node (La Palma & Australia) configuration, it is expected to be sufficiently sensitive to cover the predicted O4 binary neutron star merger volume, and will be able to respond to both northern and southern triggers.

The past few decades have seen the burgeoning of wide-field, high-cadence surveys, the most formidable of which will be the Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory. So new is the field of systematic time-domain survey astronomy; however, that major scientific insights will continue to be obtained using smaller, more flexible systems than the LSST. One such example is the Gravitational-wave Optical Transient Observer (GOTO) whose primary science objective is the optical follow-up of gravitational wave events. The amount and rate of data production by GOTO and other wide-area, high-cadence surveys presents a significant challenge to data processing pipelines which need to operate in near-real time to fully exploit the time domain. In this study, we adapt the Rubin Observatory LSST Science Pipelines to process GOTO data, thereby exploring the feasibility of using this ‘off-the-shelf’ pipeline to process data from other wide-area, high-cadence surveys. In this paper, we describe how we use the LSST Science Pipelines to process raw GOTO frames to ultimately produce calibrated coadded images and photometric source catalogues. After comparing the measured astrometry and photometry to those of matched sources from PanSTARRS DR1, we find that measured source positions are typically accurate to subpixel levels, and that measured L-band photometries are accurate to $\sim50$ mmag at $m_L\sim16$ and $\sim200$ mmag at $m_L\sim18$ . These values compare favourably to those obtained using GOTO’s primary, in-house pipeline, gotophoto, in spite of both pipelines having undergone further development and improvement beyond the implementations used in this study. Finally, we release a generic ‘obs package’ that others can build upon, should they wish to use the LSST Science Pipelines to process data from other facilities.

Investigation of the triggering mechanisms of radio AGN is important for improving our general understanding of galaxy evolution. In the first paper in this series, detailed morphological analysis of high-excitation radio galaxies (HERGs) with intermediate radio powers suggested that the importance of triggering via galaxy mergers and interactions increases strongly with AGN radio power and weakly with optical emission-line luminosity. Here, we use an online classification interface to expand our morphological analysis to a much larger sample of 155 active galaxies (3CR radio galaxies, radio-intermediate HERGs and Type 2 quasars) that covers a broad range in both 1.4 GHz radio power and [OIII]λ5007 emission-line luminosity. All active galaxy samples are found to exhibit excesses in their rates of morphological disturbance relative to 378 stellar-mass- and redshift-matched non-active control galaxies classified randomly and blindly alongside them. These excesses are highest for the 3CR HERGs (4.7 σ) and Type 2 quasar hosts (3.7 σ), supporting the idea that galaxy mergers provide the dominant triggering mechanism for these subgroups. When the full active galaxy sample is considered, there is clear evidence to suggest that the enhancement in the rate of disturbance relative to the controls increases strongly with [OIII]λ5007 emission-line luminosity but not with 1.4 GHz radio power. Evidence that the dominant AGN host types change from early-type galaxies at high radio powers to late-type galaxies at low radio powers is also found, suggesting that triggering by secular, disk-based processes holds more importance for lower-power radio AGN.

Large-scale sky surveys have played a transformative role in our understanding of astrophysical transients, only made possible by increasingly powerful machine learning-based filtering to accurately sift through the vast quantities of incoming data generated. In this paper, we present a new real-bogus classifier based on a Bayesian convolutional neural network that provides nuanced, uncertainty-aware classification of transient candidates in difference imaging, and demonstrate its application to the datastream from the GOTO wide-field optical survey. Not only are candidates assigned a well-calibrated probability of being real, but also an associated confidence that can be used to prioritise human vetting efforts and inform future model optimisation via active learning. To fully realise the potential of this architecture, we present a fully-automated training set generation method which requires no human labelling, incorporating a novel data-driven augmentation method to significantly improve the recovery of faint and nuclear transient sources. We achieve competitive classification accuracy (FPR and FNR both below 1%) compared against classifiers trained with fully human-labelled datasets, whilst being significantly quicker and less labour-intensive to build. This data-driven approach is uniquely scalable to the upcoming challenges and data needs of next-generation transient surveys. We make our data generation and model training codes available to the community.

The Gravitational-wave Optical Transient Observer (GOTO) is an array of wide-field optical telescopes, designed to exploit new discoveries from the next generation of gravitational wave detectors (LIGO, Virgo, KAGRA), study rapidly evolving transients, and exploit multimessenger opportunities arising from neutrino and very high energy gamma-ray triggers. In addition to a rapid response mode, the array will also perform a sensitive, all-sky transient survey with few day cadence. The facility features a novel, modular design with multiple 40-cm wide-field reflectors on a single mount. In June 2017 the GOTO collaboration deployed the initial project prototype, with 4 telescope units, at the Roque de los Muchachos Observatory (ORM), La Palma, Canary Islands. Here we describe the deployment, commissioning, and performance of the prototype hardware, and discuss the impact of these findings on the final GOTO design. We also offer an initial assessment of the science prospects for the full GOTO facility that employs 32 telescope units across two sites.