Search

The expansion and upgrade of the global network of ground-based gravitational wave detectors promises to improve our capacity to infer the sky-localization of transient sources, enabling more effective multi-messenger follow-ups. At the same time, the increase in the signal-to-noise ratio of detected events allows for more precise estimates of the source parameters. This study aims to assess the performance of advanced-era networks of ground-based detectors, focusing on the Hanford, Livingston, Virgo, and KAGRA instruments. We use full Bayesian parameter estimation procedures to predict the scientific potential of a network. Assuming a fixed LIGO configuration, we find that the addition of the Virgo detector is beneficial to the sky localization starting from a binary neutron star horizon distance of 20 Mpc and improves significantly from 40 Mpc onwards for both a single and double LIGO detector network, reducing the inferred mean sky-area by up to 95%. Similarly, the KAGRA detector tightens the constraints, starting from a sensitivity range of 10 Mpc. Looking at highly-spinning binary black holes, we find significant improvements with increasing sensitivity in constraining the intrinsic source parameters when adding Virgo to the two LIGO detectors. Finally, we also examine the impact of the low-frequency cut-off data on the signal-to-noise ratio. We find that existing 20 Hz thresholds are sufficient and propose a metric to monitor this to study detector performance. Our findings quantify how future enhancements in detector sensitivity and network configurations will improve the localization of gravitational wave sources and allow for more precise identification of their intrinsic properties.

It has become increasingly useful to answer questions in gravitational-wave astronomy using transdimensional models where the number of free parameters can be varied depending on the complexity required to fit the data. Given the growing interest in transdimensional inference, we introduce a new package for the Bayesian inference Library (Bilby) called tBilby. The tBilby package allows users to set up transdimensional inference calculations using the existing Bilby architecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when we seek to test theoretically uncertain predictions described by phenomenological models. For example, bursts of gravitational waves can be modelled using a superposition of N wavelets where N is itself a free parameter. Short pulses are modelled with small values of N whereas longer, more complicated signals are represented with a large number of wavelets stitched together. Other transdimensional models have found use describing instrumental noise and the population properties of gravitational-wave sources. We provide a few demonstrations of tBilby, including fitting the gravitational-wave signal GW150914 with a superposition of N sine-Gaussian wavelets. We outline our plans to further develop the tbilby code suite for a broader range of transdimensional problems., Comment: 12 pages, 7 figures

In astronomy, we frequently face the decision problem: does this data contain a signal? Typically, a statistical approach is used, which requires a threshold. The choice of threshold presents a common challenge in settings where signals and noise must be delineated, but their distributions overlap. Gravitational-wave astronomy, which has gone from the first discovery to catalogues of hundreds of events in less than a decade, presents a fascinating case study. For signals from colliding compact objects, the field has evolved from a frequentist to a Bayesian methodology. However, the issue of choosing a threshold and validating noise contamination in a catalogue persists. Confusion and debate often arise due to the misapplication of statistical concepts, the complicated nature of the detection statistics, and the inclusion of astrophysical background models. We introduce Conformal Prediction (CP), a framework developed in Machine Learning to provide distribution-free uncertainty quantification to point predictors. We show that CP can be viewed as an extension of the traditional statistical frameworks whereby thresholds are calibrated such that the uncertainty intervals are statistically rigorous and the error rate can be validated. Moreover, we discuss how CP offers a framework to optimally build a meta-pipeline combining the outputs from multiple independent searches. We introduce CP with a toy cosmic-ray detector, which captures the salient features of most astrophysical search problems and allows us to demonstrate the features of CP in a simple context. We then apply the approach to a recent gravitational-wave Mock Data Challenge using multiple search algorithms for compact binary coalescence signals in interferometric gravitational-wave data. Finally, we conclude with a discussion on the future potential of the method for gravitational-wave astronomy., Comment: 18 pages, 20 figures, accepted in Phys. Rev. D

GW200129 is claimed to be the first-ever observation of the spin-disk orbital precession detected with gravitational waves (GWs) from an individual binary system. However, this claim warrants a cautious evaluation because the GW event coincided with a broadband noise disturbance in LIGO Livingston caused by the 45 MHz electro-optic modulator system. In this paper, we present a state-of-the-art neural network that is able to model and mitigate the broadband noise from the LIGO Livingston interferometer. We also demonstrate that our neural network mitigates the noise better than the algorithm used by the LIGO-Virgo-KAGRA collaboration. Finally, we re-analyse GW200129 with the improved data quality and show that the evidence for precession is still observed., Comment: Updating with the journal-reviewed version. 8 pages, 6 figures. Data frame available at DOI: 10.5281/zenodo.10143337

The inference of source parameters from gravitational-wave signals relies on theoretical models that describe the emitted waveform. Different model assumptions on which the computation of these models is based could lead to biases in the analysis of gravitational-wave data. In this work, we sample directly on four state-of-the-art binary black hole waveform models from different families, in order to investigate these systematic biases from the 13 heaviest gravitational-wave sources with moderate to high signal-to-noise ratios in the third Gravitational-Wave Transient Catalog (GWTC- 3). All models include spin-precession as well as higher-order modes. Using the "hypermodels" technique, we treat the waveform models as one of the sampled parameters, therefore directly getting the odds ratio of one waveform model over another from a single parameter estimation run. From the joint odds ratio over all 13 sources, we find the model NRSur7dq4 to be favoured over SEOBNRv4PHM, with an odds ratio of 29.43; IMRPhenomXPHM and IMRPhenomTPHM have an odds ratio, respectively, of 4.70 and 5.09 over SEOBNRv4PHM. However, this result is mainly determined by three events that show a strong preference for some of the models and that are all affected by possible data quality issues. If we do not consider these potentially problematic events, the odds ratio do not exhibit a significant preference for any of the models. Although further work studying a larger set of signals will be needed for robust quantitative results, the presented method highlights one possible avenue for future waveform model development.

Precision pulsar timing is integral to the detection of the nanohertz stochastic gravitational-wave background as well as understanding the physics of neutron stars. Conventional pulsar timing often uses fixed time and frequency-averaged templates to determine the pulse times of arrival, which can lead to reduced accuracy when the pulse profile evolves over time. We illustrate a dynamic timing method that fits each observing epoch using basis functions. By fitting each epoch separately, we allow for the evolution of the pulse shape epoch to epoch. We apply our method to PSR J1103$-$5403 and demonstrate that it undergoes mode changing, making it the fourth millisecond pulsar to exhibit such behaviour. Our method, which is able to identify and time a single mode, yields a timing solution with a root-mean-square error of 1.343 $\mu \mathrm{s}$, a factor of 1.78 improvement over template fitting on both modes. In addition, the white-noise amplitude is reduced 4.3 times, suggesting that fitting the full data set causes the mode changing to be incorrectly classified as white noise. This reduction in white noise boosts the signal-to-noise ratio of a gravitational-wave background signal for this particular pulsar by 32%. We discuss the possible applications for this method of timing to study pulsar magnetospheres and further improve the sensitivity of searches for nanohertz gravitational waves., Comment: Accepted in MNRAS, 8 pages, 8 figures

The global network of interferometric gravitational wave (GW) observatories (LIGO, Virgo, KAGRA) has detected and characterized nearly 100 mergers of binary compact objects. However, many more real GWs are lurking sub-threshold, which need to be sifted from terrestrial-origin noise triggers (known as glitches). Because glitches are not due to astrophysical phenomena, inference on the glitch under the assumption it has an astrophysical source (e.g. binary black hole coalescence) results in source parameters that are inconsistent with what is known about the astrophysical population. In this work, we show how one can extract unbiased population constraints from a catalog of both real GW events and glitch contaminants by performing Bayesian inference on their source populations simultaneously. In this paper, we assume glitches come from a specific class with a well-characterized effective population (blip glitches). We also calculate posteriors on the probability of each event in the catalog belonging to the astrophysical or glitch class, and obtain posteriors on the number of astrophysical events in the catalog, finding it to be consistent with the actual number of events included., Comment: 13 pages, 10 figures

Interferometric gravitational-wave observatories have opened a new era in astronomy. The rich data produced by an international network enables detailed analysis of the curved space-time around black holes. With nearly one hundred signals observed so far and thousands expected in the next decade, their population properties enable insights into stellar evolution and the expansion of our Universe. However, the detectors are afflicted by transient noise artefacts known as "glitches" which contaminate the signals and bias inferences. Of the 90 signals detected to date, 18 were contaminated by glitches. This feasibility study explores a new approach to transient gravitational-wave data analysis using Gaussian processes, which model the underlying physics of the glitch-generating mechanism rather than the explicit realisation of the glitch itself. We demonstrate that if the Gaussian process kernel function can adequately model the glitch morphology, we can recover the parameters of simulated signals. Moreover, we find that the Gaussian processes kernels used in this work are well-suited to modelling long-duration glitches which are most challenging for existing glitch-mitigation approaches. Finally, we show how the time-domain nature of our approach enables a new class of time-domain tests of General Relativity, performing a re-analysis of the inspiral-merger-ringdown test on the first observed binary black hole merger. Our investigation demonstrates the feasibility of the Gaussian processes as an alternative to the traditional framework but does not yet establish them as a replacement. Therefore, we conclude with an outlook on the steps needed to realise the full potential of the Gaussian process approach., Comment: 12 pages, published in MNRAS

There are at present ${\cal O}(100)$ gravitational-wave candidates from compact binary mergers reported in the astronomical literature. As detector sensitivities are improved, the catalog will swell in size: first to ${\cal O}(1000)$ events in the A+ era and then to ${\cal O}(10^6)$ events in the era of third-generation observatories like Cosmic Explorer and the Einstein Telescope. Each event is analyzed using Bayesian inference to determine properties of the source including component masses, spins, tidal parameters, and the distance to the source. These inference products are the fodder for some of the most exciting gravitational-wave science, enabling us to measure the expansion of the Universe with standard sirens, to characterise the neutron star equation of state, and to unveil how and where gravitational-wave sources are assembled. In order to maximize the science from the coming deluge of detections, we introduce GWCloud, a searchable repository for the creation and curation of gravitational-wave inference products. It is designed with five pillars in mind: uniformity of results, reproducibility of results, stability of results, access to the astronomical community, and efficient use of computing resources. We describe how to use GWCloud with examples, which readers can replicate using the companion code to this paper. We describe our long-term vision for GWCloud., Comment: 14 pages, 9 figures

Radio pulsar glitches probe far-from-equilibrium processes involving stress accumulation and relaxation in neutron star interiors. Previous studies of glitch rates have focused on individual pulsars with as many recorded glitches as possible. In this work we analyze glitch rates using all available data including objects that have glitched never or once. We assume the glitch rate follows a homogeneous Poisson process, and therefore exclude pulsars which exhibit quasiperiodic glitching behavior. Calculating relevant Bayes factors shows that a model in which the glitch rate $\lambda$ scales as a power of the characteristic age $\tau$ is preferred over models which depend arbitrarily on powers of the spin frequency $\nu$ and/or its time derivative $\dot{\nu}$. For $\lambda = A (\tau/\tau\vref)^{-\gamma}$, where $\tau_{\rm ref}=1\ {\rm yr}$ is a reference time, the posterior distributions are unimodal with $A=\ModelAAglitch\ \rm{yr}^{-1}$, and $\gamma=\ModelAgammaglitch$. Importantly, the data exclude with 99\% confidence the possibility $\gamma=1$ canvassed in the literature. When objects with zero recorded glitches are included, the age-based rate law is still preferred and the posteriors change to give $A=\ModelAAall\ \rm{yr}^{-1}$, and $\gamma=\ModelAgammaall$. The updated estimates still support increased glitch activity for younger pulsars, while demonstrating that the large number of objects with zero glitches contain important statistical information about the rate, provided that they are part of the same population as opposed to a disjoint population which never glitches for some unknown physical reason., Comment: 18 pages, 11 figures. Accepted for publication in MNRAS

The upcoming Laser Interferometer Space Antenna (LISA) will detect a large gravitational-wave foreground of Galactic white dwarf binaries. These sources are exceptional for their probable detection at electromagnetic wavelengths, some long before LISA flies. Studies in both gravitational and electromagnetic waves will yield strong constraints on system parameters not achievable through measurements of one messenger alone. In this work, we present a Bayesian inference pipeline and simulation suite in which we study potential constraints on binaries in a variety of configurations. We show how using LISA detections and parameter estimation can significantly improve constraints on system parameters when used as a prior for the electromagnetic analyses. We also provide rules of thumb for how current measurements will benefit from LISA measurements in the future., Comment: 8 pages, 5 figures, accepted to MNRAS

Gravitational waves from the collision of binary neutron stars provide a unique opportunity to study the behaviour of supranuclear matter, the fundamental properties of gravity, and the cosmic history of our Universe. However, given the complexity of Einstein's Field Equations, theoretical models that enable source-property inference suffer from systematic uncertainties due to simplifying assumptions. We develop a hypermodel approach to compare and measure the uncertainty gravitational-wave approximants. Using state-of-the-art models, we apply this new technique to the binary neutron star observations GW170817 and GW190425 and the sub-threshold candidate GW200311_103121. Our analysis reveals subtle systematic differences between waveform models, and a frequency-dependence study suggests that this is due to the treatment of the tidal sector. This new technique provides a proving ground for model development, and a means to identify waveform-systematics in future observing runs where detector improvements will increase the number and clarity of binary neutron star collisions we observe., Comment: 10 pages, 5 figures, 1 table. Published Nature Astronomy

Gravitational-wave observations of binary neutron star mergers and their electromagnetic counterparts provide an independent measurement of the Hubble constant, $H_0$, through the standard-sirens approach. Current methods of determining $H_0$, such as measurements from the early universe and the local distance ladder, are in tension with one another. If gravitational waves are to break this tension a thorough understanding of systematic uncertainty for gravitational-wave observations is required. To accurately estimate the properties of gravitational-wave signals measured by LIGO and Virgo, we need to understand the characteristics of the detectors noise. Non-gaussian transients in the detector data and rapid changes in the instrument, known as non-stationary noise, can both add a systematic uncertainty to inferred results. We investigate how non-stationary noise affects the estimation of the luminosity distance of the source, and therefore of $H_0$. Using a population of 200 simulated binary neutron star signals, we show that non-stationary noise can bias the estimation of the luminosity distance by up to 2.4\%. However, only $\sim$15\% of binary neutron star signals would be affected around their merger time with non-stationary noise at a similar level to that seen in the first half of LIGO-Virgo's third observing run. Comparing the expected bias to other systematic uncertainties, we argue that non-stationary noise in the current generation of detectors will not be a limiting factor in resolving the tension on $H_0$ using standard sirens. Although, evaluating non-stationarity in gravitational-wave data will be crucial to obtain accurate estimates of $H_0$., Comment: 10 pages, 5 figures, 1 table

The two interferometric LIGO gravitational-wave observatories provide the most sensitive data to date to study the gravitational-wave Universe. As part of a global network, they have just completed their third observing run in which they observed many tens of signals from merging compact binary systems. It has long been known that a limiting factor in identifying transient gravitational-wave signals is the presence of transient non-Gaussian noise, which reduce the ability of astrophysical searches to detect signals confidently. Significant efforts are taken to identify and mitigate this noise at the source, but its presence persists, leading to the need for software solutions. Taking a set of transient noise artefacts categorised by the GravitySpy software during the O3a observing era, we produce parameterised population models of the noise projected into the space of astrophysical model parameters of merging binary systems. We compare the inferred population properties of transient noise artefacts with observed astrophysical systems from the GWTC2.1 catalogue. We find that while the population of astrophysical systems tend to have near equal masses and moderate spins, transient noise artefacts are typically characterised by extreme mass ratios and large spins. This work provides a new method to calculate the consistency of an observed candidate with a given class of noise artefacts. This approach could be used in assessing the consistency of candidates found by astrophysical searches (i.e. determining if they are consistent with a known glitch class). Furthermore, the approach could be incorporated into astrophysical searches directly, potentially improving the reach of the detectors, though only a detailed study would verify this., Comment: 15 pages, submitted to Phys. Rev. D

The detection of an intermediate-mass black hole population ($10^2-10^6$ $M_{\odot}$) will provide clues to their formation environments (e.g., disks of active galactic nuclei, globular clusters) and illuminate a potential pathway to produce supermassive black holes. Ground-based gravitational-wave detectors are sensitive to mergers that can form intermediate-mass black holes weighing up to $\sim 450\ M_{\odot}$. However, ground-based detector data contain numerous incoherent short duration noise transients that can mimic the gravitational-wave signals from merging intermediate-mass black holes, limiting the sensitivity of searches. Here we follow-up on binary black hole merger candidates using a ranking statistic that measures the coherence or incoherence of triggers in multiple-detector data. We use this statistic to rank candidate events, initially identified by all-sky search pipelines, with lab-frame total masses $>55\ M_{\odot}$ using data from LIGO's second observing run. Our analysis does not yield evidence for new intermediate-mass black holes. However, we find support for eight stellar-mass binary black holes not reported in the first LIGO-Virgo gravitational wave transient catalog GWTC-1, seven of which have been previously reported by other catalogs., Comment: 10 pages, 3 figures

The Maximum Entropy Spectral Analysis (MESA) method, developed by Burg, offers a powerful tool for spectral estimation of a time-series. It relies on Jaynes' maximum entropy principle, allowing the spectrum of a stochastic process to be inferred using the coefficients of an autoregressive process AR($p$) of order $p$. A closed-form recursive solution provides estimates for both the autoregressive coefficients and the order $p$ of the process. We provide a ready-to-use implementation of this algorithm in a Python package called \texttt{memspectrum}, characterized through power spectral density (PSD) analysis on synthetic data with known PSD and comparisons of different criteria for stopping the recursion. Additionally, we compare the performance of our implementation with the ubiquitous Welch algorithm, using synthetic data generated from the GW150914 strain spectrum released by the LIGO-Virgo-Kagra collaboration. Our findings indicate that Burg's method provides PSD estimates with systematically lower variance and bias. This is particularly manifest in the case of a small (O($5000$)) number of data points, making Burg's method most suitable to work in this regime. Since this is close to the typical length of analysed gravitational waves data, improving the estimate of the PSD in this regime leads to more reliable posterior profiles for the system under study. We conclude our investigation by utilising MESA, and its particularly easy parametrisation where the only free parameter is the order $p$ of the AR process, to marginalise over the interferometers noise PSD in conjunction with inferring the parameters of GW150914., Comment: 15 pages, 11 figures

We introduce Bilby-MCMC, a Markov-Chain Monte-Carlo sampling algorithm tuned for the analysis of gravitational waves from merging compact objects. Bilby-MCMC provides a parallel-tempered ensemble Metropolis-Hastings sampler with access to a block-updating proposal library including problem-specific and machine learning proposals. We demonstrate that learning proposals can produce over a 10-fold improvement in efficiency by reducing the autocorrelation time. Using a variety of standard and problem-specific tests, we validate the ability of the Bilby-MCMC sampler to produce independent posterior samples and estimate the Bayesian evidence. Compared to the widely-used dynesty nested sampling algorithm, Bilby-MCMC is less efficient in producing independent posterior samples and less accurate in its estimation of the evidence. However, we find that posterior samples drawn from the Bilby-MCMC sampler are more robust: never failing to pass our validation tests. Meanwhile, the dynesty sampler fails the difficult-to-sample Rosenbrock likelihood test, over constraining the posterior. For CBC problems, this highlights the importance of cross-sampler comparisons to ensure results are robust to sampling error. Finally, Bilby-MCMC can be embarrassingly and asynchronously parallelised making it highly suitable for reducing the analysis wall-time using a High Throughput Computing environment. Bilby-MCMC may be a useful tool for the rapid and robust analysis of gravitational-wave signals during the advanced detector era and we expect it to have utility throughout astrophysics., Comment: 16 pages, 7 figures, accepted to MNRAS

The Zwicky Transient Facility recently announced the detection of an optical transient AT2020blt at redshift $z=2.9$, consistent with the afterglow of an on-axis gamma-ray burst. However, no prompt emission was observed. We analyse AT2020blt with detailed models, showing the data are best explained as the afterglow of an on-axis long gamma-ray burst, ruling out other hypotheses such as a cocoon and a low-Lorentz factor jet. We search \textit{Fermi} data for prompt emission, setting deeper upper limits on the prompt emission than in the original detection paper. Together with KONUS-\textit{Wind} observations, we show that the gamma-ray efficiency of AT2020blt is $\lesssim 0.3 - 4.5\%$. We speculate that AT2020blt and AT2021any belong to the low-efficiency tail of long gamma-ray burst distributions that are beginning to be readily observed due to the capabilities of new observatories like the Zwicky Transient Facility., Comment: Published in MNRAS. 11 pages, 4 figures

CDF-S XT1 is a fast-rising non-thermal X-ray transient detected by \textit{Chandra} in the Deep-Field South Survey. Although various hypotheses have been suggested, the origin of this transient remains unclear. Here, we show that the observations of CDF-S XT1 are well explained as the X-ray afterglow produced by a relativistic structured jet viewed off-axis. We measure properties of the jet, showing that they are similar to those of GRB170817A, albeit at cosmological distances. We measure the observers viewing angle to be $\theta_{\textrm{obs}} = 10^{\circ}\pm3^{\circ}$ and the core of the ultra-relativistic jet to be $\theta_{\textrm{core}} = 4.4^{\circ}\pm0.9^{\circ}$, where the uncertainties are the $68\%$ credible interval. The inferred properties and host galaxy combined with Hubble, radio, and optical non detections favour the hypothesis that CDF-S XT1 is the off-axis afterglow of a binary neutron star merger. We find that other previously suggested hypotheses are unable to explain all properties of CDF-S XT1. At a redshift of $z=2.23$, this is potentially the most distant observed neutron star merger to date and the first orphan afterglow of a short gamma-ray burst. We discuss the implications of a binary neutron star merger at such a high redshift for the star-formation rate in the early Universe, the nucleosynthesis of heavy elements, and the prospect of identifying other off-axis afterglows., Comment: Submitted to ApJL, 8 Pages, 3 figures

The Advanced LIGO and Virgo gravitational wave observatories have opened a new window with which to study the inspiral and mergers of binary compact objects. These observations are most powerful when coordinated with multi-messenger observations. This was underlined by the first observation of a binary neutron star merger GW170817, coincident with a short Gamma-ray burst, GRB170817A, and the identification of the host galaxy NGC~4993 from the optical counterpart AT~2017gfo. Finding the fast-fading optical counterpart critically depends on the rapid production of a sky-map based on LIGO/Virgo data. Currently, a rapid initial sky map is produced followed by a more accurate, high-latency, $\gtrsim{12}{\rm{hr}}$ sky map. We study optimization choices of the Bayesian prior and signal model which can be used alongside other approaches such as reduced order quadrature. We find these yield up to a $60\%$ reduction in the time required to produce the high-latency localisation for binary neutron star mergers., Comment: 9 pages, 10 figures, accepted to MNRAS

Gravitational waves in the sensitivity band of ground-based detectors can be emitted by a number of astrophysical sources, including not only binary coalescences, but also individual spinning neutron stars. The most promising signals from such sources, although not yet detected, are long-lasting, quasi-monochromatic Continuous Waves (CWs). The PyFstat package provides tools to perform a range of CW data-analysis tasks. It revolves around the F-statistic, a matched-filter detection statistic for CW signals that has been one of the standard methods for LIGO-Virgo CW searches for two decades. PyFstat is built on top of established routines in LALSuite but through its more modern Python interface it enables a flexible approach to designing new search strategies. Hence, it serves a dual function of (i) making LALSuite CW functionality more easily accessible through a Python interface, thus facilitating the new user experience and, for developers, the exploratory implementation of novel methods; and (ii) providing a set of production-ready search classes for use cases not yet covered by LALSuite itself, most notably for MCMC-based followup of promising candidates from wide-parameter-space searches., Comment: 4 pages, updated to match published version. Software repository: https://github.com/PyFstat/PyFstat/

The first pulse-to-pulse observations of a neutron star glitch in the Vela pulsar identified a null pulse hinting at the sudden disruption of the neutron star's magnetosphere. The only physical model connecting the glitch and the null pulse relies on a starquake either triggering, or being triggered by, the glitch itself. Until now, this was the only null pulse identified from over 50 years of observing the Vela pulsar. We identify five other null-like pulses, that we term quasi-nulls, before and after the glitch, separated by hundreds of seconds. We verify that such nulls are not found in data away from the glitch. We speculate that the quasi-nulls are associated with foreshocks and aftershocks preceding and following the main quake, analogously with terrestrial quakes. This implies the energy reservoir built up between glitches is not released suddenly, but over a period of minutes to hours around the time of the glitch., Comment: 8 pages, 7 figures; updated to fix presentation issues

Recently, Graham et al. (2020) identified ZTF19abanrhr as a candidate electromagnetic counterpart to the binary black hole merger GW190521. The authors argue that the observations are consistent with a kicked binary black hole interacting with the accretion disk of the activate galactic nucleus AGN J124942.3+344929. If a real association (rather than happenstance), this has implications for the sources of LIGO/Virgo binary mergers, future prospects for electromagnetic counterparts, and measurements of the expansion rate of the Universe. In this Letter, we provide a re-analysis of the multi-messenger coincidence significance based on the localisation overlap and find that that the odds of a common source for GW190521 andZTF19abanrhr range between 1 and 12 depending on the waveform model used; we consider this insufficient evidence to warrant confidently associating GW190521 with ZTF19abanrhr., Comment: 5 pages, 1 figure, 2 tables, submitted to MNRASL. Updated following review

The spin-down energy of millisecond magnetars has been invoked to explain X-ray afterglow observations of a significant fraction of short and long gamma-ray bursts. Here, we extend models previously introduced in the literature, incorporating radiative losses with the spin down of a magnetar central engine through an arbitrary braking index. Combining this with a model for the tail of the prompt emission, we show that our model can better explain the data than millisecond-magnetar models without radiative losses or those that invoke spin down solely through vacuum dipole radiation. We find that our model predicts a subset of X-ray flares seen in some gamma-ray bursts. We can further explain the diversity of X-ray plateaus by altering the radiative efficiency and measure the braking index of newly-born millisecond magnetars. We measure the braking index of GRB061121 as $n=4.85^{+0.11}_{-0.15}$ suggesting the millisecond-magnetar born in this gamma-ray burst spins down predominantly through gravitational-wave emission., Comment: Published in MNRAS

Merging binary neutron stars are thought to be formed predominantly via isolated binary evolution. In this standard formation scenario, the first-born neutron star goes through a recycling process and might be rapidly spinning during the final inspiral, whereas the second-born star is expected to have effectively zero spin at merger. Based on this feature, we propose a new framework for the astrophysical characterization of binary neutron stars observed from their gravitational wave emission. We further propose a prior for the dimensionless spins of recycled neutron stars, given by a gamma distribution with a shape parameter of 2 and a scale parameter of 0.012, extrapolated from radio pulsar observations of Galactic binary neutron stars. Interpreting GW170817 and GW190425 in the context of the standard formation scenario and adopting the gamma-distribution prior, we find positive support (with a Bayes factor of 6, over the nonspinning hypothesis) for a spinning recycled neutron star in GW190425, whereas the spin of the recycled neutron star in GW170817 is small and consistent with our prior. We measure the masses of the recycled (slow) neutron stars in GW170817 and GW190425 to be $1.34_{-0.09}^{+0.12}$ $(1.38_{-0.11}^{+0.11})$ $M_{\odot}$ and $1.64_{-0.11}^{+0.13}$ $(1.66_{-0.12}^{+0.12})$ $M_{\odot}$, with $68\%$ credibility, respectively. We discuss implications for the astrophysical origins of these two events and outline future prospects of studying binary neutron stars using our framework., Comment: To match the published version on ApJ Letters; 18 pages, 12 figures, 2 tables

The gravitational-wave candidate GW151216 is a proposed binary black hole event from the first observing run of the Advanced LIGO detectors. Not identified as a bona fide signal by the LIGO--Virgo collaboration, there is disagreement as to its authenticity, which is quantified by $p_\text{astro}$, the probability that the event is astrophysical in origin. Previous estimates of $p_\text{astro}$ from different groups range from 0.18 to 0.71, making it unclear whether this event should be included in population analyses, which typically require $p_\text{astro}>0.5$. Whether GW151216 is an astrophysical signal or not has implications for the population properties of stellar-mass black holes and hence the evolution of massive stars. Using the astrophysical odds, a Bayesian method which uses the signal coherence between detectors and a parameterised model of non-astrophysical detector noise, we find that $p_\text{astro}=0.03$, suggesting that GW151216 is unlikely to be a genuine signal. We also analyse GW150914 (the first gravitational-wave detection) and GW151012 (initially considered to be an ambiguous detection) and find $p_\text{astro}$ values of 1 and 0.997 respectively. We argue that the astrophysical odds presented here improve upon traditional methods for distinguishing signals from noise., Comment: 6 pages, 1 figure, 1 table, publised in MNRAS

Gravitational-wave astronomy provides a unique new way to study the expansion history of the Universe. In this work, we investigate the impact future gravitational-wave observatories will have on cosmology. Third-generation observatories like the Einstein Telescope and Cosmic Explorer will be sensitive to essentially all of the binary black hole coalescence events in the Universe. Recent work by \cite{farr2019future} points out that features in the stellar-mass black hole population break the mass-redshift degeneracy, facilitating precise determination of the Hubble parameter without electromagnetic counterparts or host galaxy catalogues. Using a hierarchical Bayesian inference model, we show that with one year of observations by the Einstein Telescope, the Hubble constant will be measured to $\lesssim 1\%$. We also show that this method can be used to perform Bayesian model selection between cosmological models. As an illustrative example, we find that a decisive statement can be made comparing the $\Lambda$CDM and RHCT cosmological models using two weeks of data from the Einstein Telescope., Comment: 10 pages, 7 figures, Accepted by ApJ

We infer the collapse times of long-lived neutron stars into black holes using the X-ray afterglows of 18 short gamma-ray bursts. We then apply hierarchical inference to infer properties of the neutron star equation of state and dominant spin-down mechanism. We measure the maximum non-rotating neutron star mass $M_\mathrm{TOV} = 2.31 ^{+0.36}_{-0.21} M_{\odot}$ and constrain the fraction of remnants spinning down predominantly through gravitational-wave emission to $\eta = 0.69 ^{+0.21}_{-0.39}$ with $68 \%$ uncertainties. In principle, this method can determine the difference between hadronic and quark equation of states. In practice, however, the data is not yet informative with indications that these neutron stars do not have hadronic equation of states at the $1\sigma$ level. These inferences all depend on the underlying progenitor mass distribution for short gamma-ray bursts produced by binary neutron star mergers. The recently announced gravitational-wave detection of GW190425 suggests this underlying distribution is different from the locally-measured population of double neutron stars. We show that $M_\mathrm{TOV}$ and $\eta$ constraints depend on the fraction of binary mergers that form through a distribution consistent with the locally-measured population and a distribution that can explain GW190425. The more binaries that form from the latter distribution, the larger $M_\mathrm{TOV}$ needs to be to satisfy the X-ray observations. Our measurements above are marginalised over this unknown fraction. If instead, we assume GW190425 is not a binary neutron star merger, i.e the underlying mass distribution of double neutron stars is the same as observed locally, we measure $M_\mathrm{TOV} = 2.26 ^{+0.31}_{-0.17} M_{\odot}$., Comment: Published in Phys. Rev. D: Vol 101, Issue 6

Bayesian inference of gravitational wave signals is subject to systematic error due to modelling uncertainty in waveform signal models, coined approximants. A growing collection of approximants are available which use different approaches and make different assumptions to ease the process of model development. We provide a method to marginalize over the uncertainty in a set of waveform approximants by constructing a mixture-model multi-waveform likelihood. This method fits into existing workflows by determining the mixture parameters from the per-waveform evidences, enabling the production of marginalized combined sample sets from independent runs., Comment: 6 pages, 5 figures, 3 tables, accepted in Phys. Rev. D

In order to separate astrophysical gravitational-wave signals from instrumental noise, which often contains transient non-Gaussian artifacts, astronomers have traditionally relied on bootstrap methods such as time slides. Bootstrap methods sample with replacement, comparing single-observatory data to construct a background distribution, which is used to assign a false-alarm probability to candidate signals. While bootstrap methods have played an important role establishing the first gravitational-wave detections, there are limitations. First, as the number of detections increases, it makes increasingly less sense to treat single-observatory data as bootstrap-estimated noise, when we know that the data are filled with astrophysical signals, some resolved, some unresolved. Second, it has been known for a decade that background estimation from time-slides eventually breaks down due to saturation effects, yielding incorrect estimates of significance. Third, the false alarm probability cannot be used to weight candidate significance, for example when performing population inference on a set of candidates. Given recent debate about marginally resolved gravitational-wave detection claims, the question of significance has practical consequences. We propose a Bayesian framework for calculating the odds that a signal is of astrophysical origin versus instrumental noise without bootstrap noise estimation. We show how the astrophysical odds can safely accommodate glitches. We argue that it is statistically optimal. We demonstrate the method with simulated noise and provide examples to build intuition about this new approach to significance., Comment: 9 pages, 3 figures, 1 table, submitted to Phys. Rev. D, v2 fixed typo's

Understanding the properties of transient gravitational waves and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astro-physical measurement in transient gravitational-wave astronomy. Usually, stochastic sampling algorithms are used to estimate posterior probability distributions over the parameter spaces of models describing experimental data. The most physically accurate models typically come with a large computational overhead which can render data analysis extremely time consuming, or possibly even prohibitive. In some cases highly specialized optimizations can mitigate these issues, though they can be difficult to implement, as well as to generalize to arbitrary models of the data. Here, we propose an accurate, flexible and scalable method for astro-physical inference: parallelized nested sampling. The reduction in the wall-time of inference scales almost linearly with the number of parallel processes running on a high-performance computing cluster. By utilizing a pool of several hundreds or thousands of CPUs in a high-performance cluster, the large wall times of many astrophysical inferences can be alleviated while simultaneously ensuring that any gravitational-wave signal model can be used "out of the box", i.e., without additional optimization or approximation. Our method will be useful to both the LIGO-Virgo-KAGRA collaborations and the wider scientific community performing astrophysical analyses on gravitational waves. An implementation is available in the open source gravitational-wave inference library $\texttt{pBilby}$ (parallel $\texttt{bilby}$)., Comment: 9 pages, 2 figures, 1 table

The 2016 Vela glitch observed by the Mt Pleasant radio telescope provides the first opportunity to study pulse-to-pulse dynamics of a pulsar glitch, opening up new possibilities to study the neutron star's interior. We fit models of the star's rotation frequency to the pulsar data, and present three new results. First, we constrain the glitch rise time to less than 12.6s with 90% confidence, almost three times shorter than the previous best constraint. Second, we find definitive evidence for a rotational-frequency overshoot and fast relaxation following the glitch. Third, we find evidence for a slow-down of the star's rotation immediately prior to the glitch. The overshoot is predicted theoretically by some models; we discuss implications of the glitch rise and overshoot decay times on internal neutron-star physics. The slow down preceding the glitch is unexpected; we propose the slow-down may trigger the glitch by causing a critical lag between crustal superfluid and the crust., Comment: 6 pages, 5 figures, 2 tables, accepted by Nature Astronomy

Bayesian parameter estimation is fast becoming the language of gravitational-wave astronomy. It is the method by which gravitational-wave data is used to infer the sources' astrophysical properties. We introduce a user-friendly Bayesian inference library for gravitational-wave astronomy, Bilby. This python code provides expert-level parameter estimation infrastructure with straightforward syntax and tools that facilitate use by beginners. It allows users to perform accurate and reliable gravitational-wave parameter estimation on both real, freely-available data from LIGO/Virgo, and simulated data. We provide a suite of examples for the analysis of compact binary mergers and other types of signal model including supernovae and the remnants of binary neutron star mergers. These examples illustrate how to change the signal model, how to implement new likelihood functions, and how to add new detectors. Bilby has additional functionality to do population studies using hierarchical Bayesian modelling. We provide an example in which we infer the shape of the black hole mass distribution from an ensemble of observations of binary black hole mergers., Comment: Submitted for publication

The F-statistic is an established method to search for continuous gravitational waves from spinning neutron stars. Prix et al. (2011) introduced a variant for transient quasi-monochromatic signals. Possible astrophysical scenarios for such transients include glitching pulsars, newborn neutron stars and accreting systems. Here we present a new implementation of the transient F-statistic, using pyCUDA to leverage the power of modern graphics processing units (GPUs). The obtained speedup allows efficient searches over much wider parameter spaces, especially when using more realistic transient signal models including time-varying (e.g. exponentially decaying) amplitudes. Hence, it can enable comprehensive coverage of glitches in known nearby pulsars, improve the follow-up of outliers from continuous-wave searches, and might be an important ingredient for future blind all-sky searches for unknown neutron stars., Comment: 13 pages, 3 figures; v2: updated reference to 1710.02327 and its erratum

Continuous gravitational-wave signals from isolated non-axisymmetric rotating neutron stars may undergo episodic spin-up events known as glitches. If unmodelled by a search, these can result in missed or misidentified detections. We outline a semicoherent glitch-robust search method that allows identification of glitching signal candidates and inference about the model parameters., Comment: 9 pages, 6 figures, 2 tables

Leveraging Markov chain Monte Carlo (MCMC) optimization of the F-statistic, we introduce a method for the hierarchical follow-up of continuous gravitational wave candidates identified by wide-parameter space semi-coherent searches. We demonstrate parameter estimation for continuous wave sources and develop a framework and tools to understand and control the effective size of the parameter space, critical to the success of the method. Monte Carlo tests of simulated signals in noise demonstrate that this method is close to the theoretical optimal performance., Comment: 16 pages, 9 figures, 3 tables; updated following acceptance for publication in Phys. Rev. D

We highlight the advances and difficulties in understanding PSR B1828-11, which undergoes long-term periodic modulations in its timing and pulse shape over several years. A model comparison of precession and magnetospheric switching models based on the long-term modulation data favours the former; we discuss the implications of this in the context of short timescale switching observed in this pulsar. Furthermore, we highlight the difficulties this pulsar poses for our understanding of pulsars due to the increasing rate of the modulation period and its behaviour during a recent glitch., Comment: 2 pages, submitted on 19/10/2017 to "Proceedings of Pulsar Astrophysics: The Next Fifty Years, IAU Symposium 337"

We derive a Bayesian criterion for assessing whether signals observed in two separate data sets originate from a common source. The Bayes factor for a common vs. unrelated origin of signals includes an overlap integral of the posterior distributions over the common source parameters. Focusing on multimessenger gravitational-wave astronomy, we apply the method to the spatial and temporal association of independent gravitational-wave and electromagnetic (or neutrino) observations. As an example, we consider the coincidence between the recently discovered gravitational-wave signal GW170817 from a binary neutron star merger and the gamma-ray burst GRB 170817A: we find that the common source model is enormously favored over a model describing them as unrelated signals., Comment: 7 pages, 1 figure

Continuous gravitational waves from neutron stars could provide an invaluable resource to learn about their interior physics. A common search method involves matched filtering a modeled template against the noisy gravitational-wave data to find signals. This method suffers a mismatch (i.e., relative loss of the signal-to-noise ratio) if the signal deviates from the template. One possible instance in which this may occur is if the neutron star undergoes a glitch, a sudden rapid increase in the rotation frequency seen in the timing of many radio pulsars. In this work, we use a statistical characterization of the glitch rate and size in radio pulsars to estimate how often neutron star glitches would occur within the parameter space of continuous gravitational-wave searches and how much mismatch putative signals would suffer in the search due to these glitches. We find that for many previous and potential future searches continuous-wave signals have an elevated probability of undergoing one or more glitches and that these glitches will often lead to a substantial fraction of the signal-to-noise ratio being lost. This could lead to a failure to identify candidate gravitational-wave signals in the initial stages of a search and also to the false dismissal of candidates in subsequent follow-up stages., Comment: 23 pages, 9 figures; published version as in Phys. Rev. D

Recently, Abedi, Dykaar and Afshordi claimed evidence for a repeating damped echo signal following the binary black hole merger gravitational-wave events recorded in the first observational period of the Advanced LIGO interferometers. We discuss the methods of data analysis and significance estimation leading to this claim, and identify several important shortcomings. We conclude that their analysis does not provide significant observational evidence for the existence of Planck-scale structure at black hole horizons, and suggest renewed analysis correcting for these shortcomings.

Nowadays, micromagnetic simulations are a common tool for studying a wide range of different magnetic phenomena, including the ferromagnetic resonance. A technique for evaluating reliability and validity of different micromagnetic simulation tools is the simulation of proposed standard problems. We propose a new standard problem by providing a detailed specification and analysis of a sufficiently simple problem. By analyzing the magnetization dynamics in a thin permalloy square sample, triggered by a well defined excitation, we obtain the ferromagnetic resonance spectrum and identify the resonance modes via Fourier transform. Simulations are performed using both finite difference and finite element numerical methods, with \textsf{OOMMF} and \textsf{Nmag} simulators, respectively. We report the effects of initial conditions and simulation parameters on the character of the observed resonance modes for this standard problem. We provide detailed instructions and code to assist in using the results for evaluation of new simulator tools, and to help with numerical calculation of ferromagnetic resonance spectra and modes in general.