arXiv subjects

Colm Talbot

Publications and source records attributed to Colm Talbot.

At least 37 records · Page 2Linked to original sources

arXiv2022

The orientations of the binary black holes in GWTC-3

It is expected that the orbital planes of gravitational-wave (GW) sources are isotropically distributed. However, both physical and technical factors, such as alternate theories of gravity with birefringence, catalog contamination, and search algorithm limitations, could result in inferring a non-isotropic distribution. Showing that the inferred astrophysical distribution of the orbital orientations is indeed isotropic can thus be used to rule out some violations of general relativity, as a null test about the purity of the GW catalog sample, and as a check that selection effects are being properly accounted for. We augment the default mass/spins/redshift model used by the LIGO-Virgo-KAGRA Collaboration in their most recent analysis to also measure the astrophysical distribution of orbital orientations. We show that the 69 binary black holes in GWTC-3 are consistent with having random orbital orientations. The inferred distribution is highly symmetric around $π/2$, with skewness $\mathcal{S}_{\rm{post}}=0.01^{+0.17}_{-0.17}$. Meanwhile, the median of the inferred distribution has a Jensen-Shannon divergence of $1.4\times 10^{-4}$ bits when compared to the expected isotropic distribution.

gr-qc↗

arXiv2022

The effect of spin mismodeling on gravitational-wave measurements of the binary neutron star mass distribution

The binary neutron star (BNS) mass distribution measured with gravitational-wave observations has the potential to reveal information about the dense matter equation of state, supernova physics, the expansion rate of the universe, and tests of General Relativity. As most current gravitational-wave analyses measuring the BNS mass distribution do not simultaneously fit the spin distribution, the implied population-level spin distribution is the same as the spin prior applied when analyzing individual sources. In this work, we demonstrate that introducing a mismatch between the implied and true BNS spin distributions can lead to biases in the inferred mass distribution. This is due to the strong correlations between the measurements of the mass ratio and spin components aligned with the orbital angular momentum for individual sources. We find that applying a low-spin prior which excludes the true spin magnitudes of some sources in the population leads to significantly overestimating the maximum neutron star mass and underestimating the minimum neutron star mass at the population level with as few as six BNS detections. The safest choice of spin prior that does not lead to biases in the inferred mass distribution is one which allows for high spin magnitudes and tilts misaligned with the orbital angular momentum.

astro-ph.HE↗

arXiv2022

Fast, flexible, and accurate evaluation of gravitational-wave Malmquist bias with machine learning

Many astronomical surveys are limited by the brightness of the sources, and gravitational-wave searches are no exception. The detectability of gravitational waves from merging binaries is affected by the mass and spin of the constituent compact objects. To perform unbiased inference on the distribution of compact binaries, it is necessary to account for this selection effect, which is known as Malmquist bias. Since systematic error from selection effects grows with the number of events, it will be increasingly important over the coming years to accurately estimate the observational selection function for gravitational-wave astronomy. We employ density estimation methods to accurately and efficiently compute the compact binary coalescence selection function. We introduce a simple pre-processing method, which significantly reduces the complexity of the required machine learning models. We demonstrate that our method has smaller statistical errors at comparable computational cost than the method currently most widely used allowing us to probe narrower distributions of spin magnitudes. The currently used method leaves $10-50\%$ of the interesting black hole spin models inaccessible; our new method can probe $>99\%$ of the models and has a lower uncertainty for $>80\%$ of the models.

gr-qc↗

arXiv2021

Hierarchical Inference of Binary Neutron Star Mass Distribution and Equation of State with Gravitational Waves

Gravitational wave observations of binary neutron star mergers provide valuable information about neutron star structure and the equation of state of dense nuclear matter. Numerous methods have been proposed to analyze the population of observed neutron stars and previous work has demonstrated the necessity of jointly fitting the astrophysical distribution and the equation of state in order to accurately constrain the equation of state. In this work, we introduce a new framework to simultaneously infer the distribution of binary neutron star masses and the nuclear equation of state using Gaussian mixture model density estimates which mitigates some of the limitations previously-used methods suffer from. Using our method, we reproduce previous projections for the expected precision of our joint mass distribution and equation of state inference with tens of observations. We also show that mismodeling the equation of state can bias our inference of the neutron star mass distribution. While we focus on neutron star masses and matter effects, our method is widely applicable to population inference problems.

astro-ph.HE↗

arXiv2021

Inference with finite time series: Observing the gravitational Universe through windows

Time series analysis is ubiquitous in many fields of science including gravitational-wave astronomy, where strain time series are analyzed to infer the nature of gravitational-wave sources, e.g., black holes and neutron stars. It is common in gravitational-wave transient studies to apply a tapered window function to reduce the effects of spectral artifacts from the sharp edges of data segments. We show that the conventional analysis of tapered data fails to take into account covariance between frequency bins, which arises for all finite time series -- no matter the choice of window function. We discuss the origin of this covariance and show that as the number of gravitational-wave detections grows, and as we gain access to more high signal-to-noise ratio events, this covariance will become a non-negligible source of systematic error. We derive a framework that models the correlation induced by the window function and demonstrate this solution using both data from the first LIGO--Virgo transient catalog and simulated Gaussian noise.

astro-ph.IM↗

arXiv2021

Probing Extremal Gravitational-Wave Events with Coarse-Grained Likelihoods

As catalogs of gravitational-wave transients grow, new records are set for the most extreme systems observed to date. The most massive observed black holes probe the physics of pair instability supernovae while providing clues about the environments in which binary black hole systems are assembled. The least massive black holes, meanwhile, allow us to investigate the purported neutron star-black hole mass gap, and binaries with unusually asymmetric mass ratios or large spins inform our understanding of binary and stellar evolution. Existing outlier tests generally implement leave-one-out analyses, but these do not account for the fact that the event being left out was by definition an extreme member of the population. This results in a bias in the evaluation of outliers. We correct for this bias by introducing a coarse-graining framework to investigate whether these extremal events are true outliers or whether they are consistent with the rest of the observed population. Our method enables us to study extremal events while testing for population model misspecification. We show that this ameliorates biases present in the leave-one-out analyses commonly used within the gravitational-wave community. Applying our method to results from the second LIGO--Virgo transient catalog, we find qualitative agreement with the conclusions of Abbott et al, ApJL 913 L7 (2021). GW190814 is an outlier because of its small secondary mass. We find that neither GW190412 nor GW190521 are outliers.

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arXiv2021

Bilby-MCMC: An MCMC sampler for gravitational-wave inference

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.

gr-qc↗

arXiv2021

Evidence for hierarchical black hole mergers in the second LIGO--Virgo gravitational-wave catalog

We study the population properties of merging binary black holes in the second LIGO--Virgo Gravitational-Wave Transient Catalog assuming they were all formed dynamically in gravitationally bound clusters. Using a phenomenological population model, we infer the mass and spin distribution of first-generation black holes, while self-consistently accounting for hierarchical mergers. Considering a range of cluster masses, we see compelling evidence for hierarchical mergers in clusters with escape velocities $\gtrsim 100~\mathrm{km\,s^{-1}}$. For our most probable cluster mass, we find that the catalog contains at least one second-generation merger with $99\%$ credibility. We find that the hierarchical model is preferred over an alternative model with no hierarchical mergers (Bayes factor $\mathcal{B} > 1400$) and that GW190521 is favored to contain two second-generation black holes with odds $\mathcal{O}>700$, and GW190519, GW190602, GW190620, and GW190706 are mixed-generation binaries with $\mathcal{O} > 10$. However, our results depend strongly on the cluster escape velocity, with more modest evidence for hierarchical mergers when the escape velocity is $\lesssim 100~\mathrm{km\,s^{-1}}$. Assuming that all binary black holes are formed dynamically in globular clusters with escape velocities on the order of tens of $\mathrm{km\,s^{-1}}$, GW190519 and GW190521 are favored to include a second-generation black hole with odds $\mathcal{O}>1$. In this case, we find that $99\%$ of black holes from the inferred total population have masses that are less than $49\,M_{\odot}$, and that this constraint is robust to our choice of prior on the maximum black hole mass.

astro-ph.HE↗

arXiv2020

Measuring the primordial gravitational-wave background in the presence of astrophysical foregrounds

Primordial gravitational waves are expected to create a stochastic background encoding information about the early Universe that may not be accessible by other means. However, the primordial background is obscured by an astrophysical foreground consisting of gravitational waves from compact binaries. We demonstrate a Bayesian method for estimating the primordial background in the presence of an astrophysical foreground. Since the background and foreground signal parameters are estimated simultaneously, there is no subtraction step, and therefore we avoid astrophysical contamination of the primordial measurement, sometimes referred to as "residuals". Additionally, since we include the non-Gaussianity of the astrophysical foreground in our model, this method represents the statistically optimal approach to the simultaneous detection of a multi-component stochastic background.

astro-ph.HE↗

arXiv2020

Probing the Black Hole Metric. I. Black Hole Shadows and Binary Black-Hole Inspirals

In General Relativity, the spacetimes of black holes have three fundamental properties: (i) they are the same, to lowest order in spin, as the metrics of stellar objects; (ii) they are independent of mass, when expressed in geometric units; and (iii) they are described by the Kerr metric. In this paper, we quantify the upper bounds on potential black-hole metric deviations imposed by observations of black-hole shadows and of binary black-hole inspirals in order to explore the current experimental limits on possible violations of the last two predictions. We find that both types of experiments provide correlated constraints on deviation parameters that are primarily in the tt-components of the spacetimes, when expressed in areal coordinates. We conclude that, currently, there is no evidence for a deviations from the Kerr metric across the 8 orders of magnitudes in masses and 16 orders in curvatures spanned by the two types of black holes. Moreover, because of the particular masses of black holes in the current sample of gravitational-wave sources, the correlations imposed by the two experiments are aligned and of similar magnitudes when expressed in terms of the far field, post-Newtonian predictions of the metrics. If a future coalescing black-hole binary with two low-mass (e.g., ~3 Msun) components is discovered, the degeneracy between the deviation parameters can be broken by combining the inspiral constraints with those from the black-hole shadow measurements.

gr-qc↗

arXiv2020

Black hole genealogy: Identifying hierarchical mergers with gravitational waves

In dense stellar environments, the merger products of binary black hole mergers may undergo additional mergers. These hierarchical mergers are predicted to have higher masses than the first generation of black holes made from stars. The components of hierarchical mergers are expected to have significant characteristic spins $χ\sim 0.7$. However, since the population properties of first-generation black holes are uncertain, it is difficult to know if any given merger is first-generation or hierarchical. We use observations of gravitational waves to reconstruct the binary black hole mass and spin spectrum of a population containing hierarchical merger events. We employ a phenomenological model that captures the properties of merging binary black holes from simulations of dense stellar environments. Inspired by recent work on the isolated formation of low-spin black holes, we include a zero-spin subpopulation. We analyze binary black holes from LIGO and Virgo's first two observing runs, and find that this catalog is consistent with having no hierarchical mergers. We find that the most massive system in this catalog, GW170729, is mostly likely a first-generation merger, having a $4\%$ probability of being a hierarchical merger assuming a $5 \times 10^5 M_{\odot}$ globular cluster mass. Using our model, we find that $99\%$ of first-generation black holes in coalescing binaries have masses below 44 $M_{\odot}$, and the fraction of binaries with near-zero spin is $0.051^{+0.156}_{-0.048}$ ($90\%$ credible interval). Upcoming observations will determine if hierarchical mergers are a common source of gravitational waves.

astro-ph.HE↗

arXiv2020

Gravitational-wave astronomy with a physical calibration model

We carry out astrophysical inference for compact binary merger events in LIGO-Virgo's first gravitational-wave transient catalog (GWTC-1) using a physically motivated calibration model. We demonstrate that importance sampling can be used to reduce the cost of what would otherwise be a computationally challenging analysis. We show that including the physical estimate for the calibration error distribution has negligible impact on the inference of parameters for the events in GWTC-1. Studying a simulated signal with matched filter signal-to-noise ratio $\text{SNR}=200$, we project that a calibration error estimate typical of GWTC-1 is likely to be negligible for the current generation of gravitational-wave detectors. We argue that other sources of systematic error---from waveforms, prior distributions, and noise modelling---are likely to be more important. Finally, using the events in GWTC-1 as standard sirens, we infer an astrophysically-informed improvement on the estimate of the calibration error in the LIGO interferometers.

astro-ph.IM↗

arXiv2020

Gravitational-wave astronomy with an uncertain noise power spectral density

In order to extract information about the properties of compact binaries, we must estimate the noise power spectral density of gravitational-wave data, which depends on the properties of the gravitational-wave detector. In practice, it is not possible to know this perfectly, only to estimate it from the data. Multiple estimation methods are commonly used and each has a corresponding statistical uncertainty. However, this uncertainty is widely ignored when measuring the physical parameters describing compact binary coalescences, and the appropriate likelihoods which account for the uncertainty are not well known. In order to perform increasingly precise astrophysical inference and model selection, it will be essential to account for this uncertainty. In this work, we derive the correct likelihood for one of the most widely used estimation methods in gravitational-wave transient analysis, the median average. We demonstrate that simulated Gaussian noise follows the predicted distributions. We then examine real gravitational-wave data at and around the time of GW151012, a relatively low-significance binary black hole merger event. We show that the data are well described by stationary-Gaussian noise and explore the impact of different noise power spectral density estimation methods on the astrophysical inferences we draw about GW151012.

astro-ph.IM↗

arXiv2020

Measuring the neutron star equation of state with gravitational waves: the first forty binary neutron star mergers

Gravitational waves from binary neutron star coalescences contain rich information about matter at supranuclear densities encoded by the neutron star equation of state. We can measure the equation of state by analyzing the tidal interactions between neutron stars, which is quantified by the tidal deformability. Multiple merger events are required to probe the equation of state over a range of neutron star masses. The more events included in the analysis, the stronger the constraints on the equation of state. In this paper, we build on previous work to explore the constraints that LIGO and Virgo are likely to place on the neutron star equation of state by combining the first forty binary neutron star detections, a milestone we project to be reached during the first year of accumulated design-sensitivity data. We carry out Bayesian inference on a realistic mock dataset of binaries to obtain posterior distributions for neutron star tidal parameters. In order to combine posterior samples from multiple observations, we employ a random forest regressor, which allows us to efficiently interpolate the likelihood distribution. Assuming a merger rate of 1540 Gpc$^{-3}$ yr$^{-1}$ and a LIGO-Virgo detector network operating for one year at the sensitivity of the third-observation run, plus an additional eight months of design sensitivity, we find that the radius of a 1.4 $M_\odot$ neutron star can be constrained to $\sim 10$% at 90% confidence. At the same time, the pressure at twice the nuclear saturation density can be constrained to $\sim 45$ % at 90% confidence. Finally, we add an appendix following publication of the paper in the journal, showing the posterior distribution of the maximum neutron star mass allowed by the equation of state. We find that the maximum mass can be constrained to $\sim 0.3$ $M_\odot$ at 90% confidence.

gr-qc↗

arXiv2020

Massively parallel Bayesian inference for transient gravitational-wave astronomy

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 $\texttt{bilby}$).

gr-qc↗

arXiv2020

Inferring the population properties of binary black holes from unresolved gravitational waves

The vast majority of compact binary mergers in the Universe produce gravitational waves that are too weak to yield unambiguous detections; they are unresolved. We present a method to infer the population properties of compact binaries -- such as their merger rates, mass spectrum, and spin distribution -- using both resolved and unresolved gravitational waves. By eliminating entirely the distinction between resolved and unresolved signals, we eliminate bias from selection effects. To demonstrate this method, we carry out a Monte Carlo study using an astrophysically motivated population of binary black holes. We show that some population properties of compact binaries are well constrained by unresolved signals after about one week of observation with Advanced LIGO at design sensitivity.

astro-ph.HE↗

arXiv2020

Constraining the Gravitational-Wave Afterglow From a Binary Neutron Star Coalescence

Binary neutron star mergers are rich laboratories for physics, accessible with ground-based interferometric gravitational-wave detectors such as the Advanced LIGO and Advanced Virgo. If a neutron star remnant survives the merger, it can emit gravitational waves that might be detectable with the current or next generation detectors. The physics of the long-lived post-merger phase is not well understood and makes modelling difficult. In particular the phase of the gravitational-wave signal is not well modelled. In this paper, we explore methods for using long duration post-merger gravitational-wave signals to constrain the parameters and the properties of the remnant. We develop a phase-agnostic likelihood model that uses only the spectral content for parameter estimation and demonstrate the calculation of a Bayesian upper limit in the absence of a signal. With the millisecond magnetar model, we show that for an event like GW170817, the ellipticity of a long-lived remnant can be constrained to less than about 0.5 in the parameter space used.

astro-ph.IM↗

arXiv2019

Gravitational-wave inference in the catalog era: evolving priors and marginal events

As the number of gravitational-wave transient detections grows, the inclusion of marginally significant events in gravitational-wave catalogs will lead to increasing contamination from false positives. In this paper, we address the question of how to carry out population studies in light of the fact that some fraction of marginally significant gravitational-wave events are of terrestrial origin. We show that previously published estimates of $p_\text{astro}$, the probability that an event is of astrophysical origin, imply an effective noise likelihood, which can be used to take into account the uncertain origin of marginal events in population studies. We derive a formalism to carry out population studies with ambiguous gravitational-wave events. We demonstrate this formalism using events from the LIGO/Virgo Gravitational-Wave Transient Catalog 1 (GWTC-1) as well as events from the Venumadhav et al. "IAS catalog." We derive posterior distributions for population parameters and discuss how they change when we take into account $p_\text{astro}$. We provide updated individual-event posterior distributions by including population information.

astro-ph.HE↗