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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.
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
coincident observations of gravitational-wave mergers with gamma-ray burst prompt emission,
detections with kilonova observations, and
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
. These numbers indicate significant science potential for a single kilohertz gravitational-wave detector operating without a global network of other gravitational-wave observatories.
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
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.
Neutron stars are excellent emitters of gravitational waves. Squeezing matter beyond nuclear densities invites exotic physical processes, many of which violently transfer large amounts of mass at relativistic velocities, disrupting spacetime and generating copious quantities of gravitational radiation. I review mechanisms for generating gravitational waves with neutron stars. This includes gravitational waves from radio and millisecond pulsars, magnetars, accreting systems, and newly born neutron stars, with mechanisms including magnetic and thermoelastic deformations, various stellar oscillation modes, and core superfluid turbulence. I also focus on what physics can be learnt from a gravitational wave detection, and where additional research is required to fully understand the dominant physical processes at play.
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