Gravitational Wave Data Research Articles

Inferring prompt black-hole formation in neutron star mergers from gravitational-wave data

The gravitational-wave GW170817 is associated to the inspiral phase of a binary neutron star coalescence event. The LIGO-Virgo detectors sensitivity at high frequencies was not sufficient to detect the signal corresponding to the merger and post-merger phases. Hence, the question whether the merger outcome was a prompt black hole formation or not must be answered using either the pre-merger gravitational wave signal or electromagnetic counterparts. In this work we present two methods to infer the probability of prompt black hole formation, using the analysis of the inspiral gravitational-wave signal. Both methods combine the posterior distribution from the gravitational-wave data analysis with numerical relativity results. One method relies on the use of phenomenological models for the equation of state and on the estimate of the collapse threshold mass. The other is based on the estimate of the tidal polarizability parameter $\tilde{\Lambda}$ that is correlated in an equation-of-state agnostic way with the prompt BH formation. We analyze GW170817 data and find that the two methods consistently predict a probability of ~ 50-70% for prompt black-hole formation, which however may significantly decrease below 10% if the maximum mass constraint from PSR J0348+0432 or PSR J0740+6620 is imposed.

Fast evaluation of multidetector consistency for real-time gravitational wave searches

Gravitational waves searches for compact binary mergers with LIGO and Virgo are presently a two stage process. First, a gravitational wave signal is identified. Then, an exhaustive search over possible signal parameters is performed. It is critical that the identification stage is efficient in order to maximize the number of gravitational wave sources that are identified. Initial identification of gravitational wave signals with LIGO and Virgo happens in real-time which requires that less than one second of computational time must be used for each one second of gravitational wave data collected. In contrast, subsequent parameter estimation may require hundreds of hours of computational time to analyze the same one second of gravitational wave data. The real-time identification requirement necessitates efficient and often approximate methods for signal analysis. We describe one piece of real-time gravitational-wave identification: an efficient method for ascertaining a signal's consistency between multiple gravitational wave detectors suitable for real-time gravitational wave searches for compact binary mergers. This technique was used in analyses of Advanced LIGO's second observing run and Advanced Virgo's first observing run.

Model comparison from LIGO–Virgo data on GW170817’s binary components and consequences for the merger remnant

GW170817 is the very first observation of gravitational waves originating from the coalescence of two compact objects in the mass range of neutron stars, accompanied by electromagnetic counterparts, and offers an opportunity to directly probe the internal structure of neutron stars. We perform Bayesian model selection on a wide range of theoretical predictions for the neutron star equation of state. For the binary neutron star hypothesis, we find that we cannot rule out the majority of theoretical models considered. In addition, the gravitational-wave data alone does not rule out the possibility that one or both objects were low-mass black holes. We discuss the possible outcomes in the case of a binary neutron star merger, finding that all scenarios from prompt collapse to long-lived or even stable remnants are possible. For long-lived remnants, we place an upper limit of 1.9 kHz on the rotation rate. If a black hole was formed any time after merger and the coalescing stars were slowly rotating, then the maximum baryonic mass of non-rotating neutron stars is at most , and three equations of state considered here can be ruled out. We obtain a tighter limit of for the case that the merger results in a hypermassive neutron star.

A self-consistent method to estimate the rate of compact binary coalescences with a Poisson mixture model

The recently published GWTC-1 (Abbott B P et al (LIGO Scientific Collaboration and Virgo Collaboration) 2019 Phys. Rev. X 9 031040)—a journal article summarizing the search for gravitational waves (GWs) from coalescing compact binaries in data produced by the LIGO-Virgo network of ground-based detectors during their first and second observing runs—quoted estimates for the rates of binary neutron star, neutron star black hole binary, and binary black hole mergers, as well as assigned probabilities of astrophysical origin for various significant and marginal GW candidate events. In this paper, we delineate the formalism used to compute these rates and probabilities, which assumes that triggers above a low ranking statistic threshold, whether of terrestrial or astrophysical origin, occur as independent Poisson processes. In particular, we include an arbitrary number of astrophysical categories by redistributing, via mass-based template weighting, the foreground probabilities of candidate events, across source classes. We evaluate this formalism on synthetic GW data, and demonstrate that this method works well for the kind of GW signals observed during the first and second observing runs.

Exploring the “L–σ” Relation of H ii Galaxies and Giant Extragalactic H ii Regions Acting as Standard Candles

Abstract Cosmological applications of H ii galaxies and giant extragalactic H ii regions (GEHRs) to construct the Hubble diagram at high redshifts require knowledge of the “L–σ” relation of the standard candles used. In this paper, we study the properties of a large sample of 156 sources (25 high-z H ii galaxies, 107 local H ii galaxies, and 24 GEHRs) compiled by Terlevich et al. Using the cosmological distances reconstructed through two new cosmology-independent methods, we investigate the correlation between the Hβ emission-line luminosity L and the ionized gas velocity dispersion σ. The method is based on non-parametric reconstruction using the measurements of Hubble parameters from cosmic clocks, as well as the simulated data of gravitational waves from the third-generation gravitational wave detector (the Einstein Telescope, ET), which can be considered as standard sirens. Assuming the relation between emission-line luminosity and ionized gas velocity dispersion, , we find that the full sample provides a tight constraint on the correlation parameters. However, similar analysis done on three different subsamples seems to support the scheme of treating H ii galaxies and GEHRs with distinct strategies. Using the corrected “L–σ” relation for the H ii observational sample beyond the current reach of Type Ia supernovae, we obtain values of the matter density parameter, Ω m = 0.314 ± 0.054 (calibrated with standard clocks) and Ω m = 0.311 ± 0.049 (calibrated with standard sirens), in the spatially flat ΛCDM cosmology.

Constraining the Observer Angle of the Kilonova AT2017gfo Associated with GW170817: Implications for the Hubble Constant

There is a strong degeneracy between the luminosity distance (DL) and the observer viewing angle (θobs; hereafter viewing angle) of the gravitational wave (GW) source with an electromagnetic counterpart, GW170817. Here, for the first time, we present independent constraints on from broadband photometry of the kilonova (kN) AT2017gfo associated with GW170817. These constraints are consistent with independent results presented in the literature using the associated gamma-ray burst GRB 170817A. Combining the constraints on θobs with the GW data, we find an improvement of 24% on H0. The observer angle constraints are insensitive to other model parameters, e.g., the ejecta mass, the half-opening angle of the lanthanide-rich region and the temperature. A broad wavelength coverage extending to the near-infrared is helpful to robustly constrain θobs. While the improvement on H0 presented here is smaller than the one from high angular resolution imaging of the radio counterpart of GW170817, kN observations are significantly more feasible at the typical distances of such events from current and future LIGO–Virgo collaboration observing runs (DL ∼ 100 Mpc). Our results are insensitive to the assumption of the peculiar velocity of the kN host galaxy.

Identifying and Characterizing Cyclicality and Seasonality in Environmental Data with An Adaptive Filter Implementation of A Phase Locked Loop

Phase Locked Loops are provided as a manner of assessing, monitoring and forecasting with seasonal or cyclical data. Phase Locked Loops using adaptive filtering were initially utilized for gravitational wave data analysis. In this paper we examine this implementation as an alternative approach for identifying the presence of one or more cycles in environmental data. Unlike most techniques for assessing seasonality phase lock loops can identify the presence of cycles without prior suspicion of their nature and existence. This is important for identifying either the initiation of new cycles or changes in existing cycles. As environmental data can be impacted by the presence of numerous cyclical phenomena and these cycles can change over time, this is a suitable and valuable technique. The technique can be used on existing data sets or assessing data streams. Phase Locked Loops are advantageous over many currently as the presence of multiple different cycles can be identified without prior suspicion and specification of the nature of the cyclicality of the data. The speed and parsimonious nature of the technique makes Phase Lock Loops ideal for Big Data and data flows that are so large that they must be assessed on a real time basis. The technique can manage and advise of changes in frequency, amplitude and phase shifts. The technique is illustrated utilizing weather data.

Probing the cosmic opacity from future gravitational wave standard sirens

In this work, using the Gaussian Process, we explore the potentiality of future gravitational wave (GW) measurement to probe cosmic opacity through comparing its opacity-free luminosity distance (LD) with the opacity-dependent one from type Ia supernovae (SNIa). GW data points are simulated from the third generation Einstein Telescope, and SNIa data are taken from the Joint Light Analysis (JLA) or Pantheon compilation. The advantages of using Gaussian Process are that one may match SNIa data with GW data at the same redshift and use all available data to probe cosmic opacity. We obtain that the error bar of the constraint on cosmic opacity can be reduced to $\sigma_{\epsilon}\sim 0.011$ and $0.006$ at $1\sigma$ confidence level (CL) for JLA and Pantheon respectively in a cosmological-independent way. Thus, the future GW measurements can give competitive results on the cosmic opacity test. Furthermore, we propose a method to probe the spatial homogeneity of the cosmic transparency through comparing the reconstructed LD from the mock GW with the reconstructed one from SNIa data in a flat $\Lambda$CDM with the Gaussian Process. The result shows that a transparent universe is favored at $1\sigma$ CL, although the best-fit value of cosmic opacity is redshift-dependent.

The impact of the crust equation of state on the analysis of GW170817

The detection of GW170817, the first neutron star-neutron star merger observed by Advanced LIGO and Virgo, and its following analyses represent the first contributions of gravitational wave data to understanding dense matter. Parameterizing the high density section of the equation of state of both neutron stars through spectral decomposition, and imposing a lower limit on the maximum mass value, led to an estimate of the stars’ radii of km and km (Abbott et al 2018 Phys. Rev. Lett. 121 161101). These values do not, however, take into account any uncertainty owed to the choice of the crust low-density equation of state, which was fixed to reproduce the SLy equation of state model (Douchin and Haensel 2001 Astron. Astrophys. 380 151). We here re-analyze GW170817 data and establish that different crust models do not strongly impact the mass or tidal deformability of a neutron star—it is impossible to distinguish between low-density models with gravitational wave analysis. However, the crust does have an effect on inferred radius. We predict the systematic error due to this effect using neutron star structure equations, and compare the prediction to results from full parameter estimation runs. For GW170817, this systematic error affects the radius estimate by 0.3 km, approximately of the neutron stars’ radii.

Gravitational waves and higher dimensions: Love numbers and Kaluza-Klein excitations

Gravitational-wave (GW) observations provide a wealth of information on the nature and properties of black holes. Among these, tidal Love numbers or the multipole moments of the inspiralling and final objects are key to a number of constraints. Here, we consider these observations in the context of higher-dimensional scenarios, with flat large extra dimensions. We show that -- as might be anticipated, but not always appreciated in the literature -- physically motivated set-ups are unconstrained by gravitational-wave data. Dynamical processes that do not excite the Kaluza-Klein (KK) modes lead to a signal identical to that in four-dimensional general relativity in vacuum . In addition, any possible excitation of the KK modes is highly suppressed relative to the dominant quadrupolar term; given existing constraints on the extra dimensions and the masses of the objects seen in gravitational-wave observations, KK modes appear at post-Newtonian order $\sim 10^{11}$. Finally, we re-compute the tidal Love numbers of spherical black holes in higher dimensions. We confirm that these are different from zero, but comparing with previous computations we find a different magnitude and sign.

Beyond Whittle: Nonparametric Correction of a Parametric Likelihood with a Focus on Bayesian Time Series Analysis

Nonparametric Bayesian inference has seen a rapid growth over the last decade but only few nonparametric Bayesian approaches to time series analysis have been developed. Most existing approaches use Whittle’s likelihood for Bayesian modelling of the spectral density as the main nonparametric characteristic of stationary time series. It is known that the loss of efficiency using Whittle’s likelihood can be substantial. On the other hand, parametric methods are more powerful than nonparametric methods if the observed time series is close to the considered model class but fail if the model is misspecified. Therefore, we suggest a nonparametric correction of a parametric likelihood that takes advantage of the efficiency of parametric models while mitigating sensitivities through a nonparametric amendment. We use a nonparametric Bernstein polynomial prior on the spectral density with weights induced by a Dirichlet process and prove posterior consistency for Gaussian stationary time series. Bayesian posterior computations are implemented via an MH-within-Gibbs sampler and the performance of the nonparametrically corrected likelihood for Gaussian time series is illustrated in a simulation study and in three astronomy applications, including estimating the spectral density of gravitational wave data from the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO).

Finite tidal effects in GW170817: Observational evidence or model assumptions?

After the detection of gravitational waves caused by the coalescence of compact objects in the mass range of neutron stars, GW170817, several studies have searched for an imprint of tidal effects in the signal, employing different model assumptions. One important distinction is whether or not to assume that both objects are neutron stars and obey the same equation of state. Some studies assumed independent properties. Others assume a universal equation of state, and in addition that the tidal deformability follows certain phenomenological relations. An important question is whether the gravitational-wave data alone constitute observational evidence for finite tidal effects. All studies provide Bayesian credible intervals, often without sufficiently discussing the impact of prior assumptions, especially in the case of lower limits on the neutron-star tidal deformability or radius. In this article, we scrutinize the implicit and explicit prior assumptions made in those studies. Our findings strongly indicate that existing lower credible bounds are mainly a consequence of prior assumptions combined with information gained about the system's masses. Importantly, those lower bounds are typically not informed by the observation of tidal effects in the gravitational-wave signal. Thus, regarding them as observational evidence might be misleading without a more detailed discussion. Further, we point out technical problems and conceptual inconsistencies in existing studies. We also assess the limitations due to systematic waveform model uncertainties in a novel way, demonstrating that differences between existing models are not guaranteed to be small enough for an unbiased estimation of lower bounds on the tidal deformability. Finally, we propose strategies for gravitational-wave data analysis designed to avoid some of the problems we uncovered.

Constraining the Fraction of Binary Black Holes Formed in Isolation and Young Star Clusters with Gravitational-wave Data

Abstract Ten binary black hole mergers have already been detected during the first two observing runs of advanced LIGO and Virgo, and many more are expected to be observed in the near future. This opens the possibility for gravitational-wave (GW) astronomy to better constrain the properties of black hole binaries—not only as single sources, but as a whole astrophysical population. In this paper, we address the problem of using GW measurements to estimate the proportion of merging black holes produced either via isolated binaries or binaries evolving in young star clusters. To this end, we use a Bayesian hierarchical modeling approach applied to catalogs of merging binary black holes generated using state-of-the-art population synthesis and N-body codes. In particular, we show that, although current advanced LIGO/Virgo observations only mildly constrain the mixing fraction between the two formation channels, we expect to narrow down the fractional errors on to 10%–20% after a few hundreds of detections.

Measurement of the Nuclear Symmetry Energy Parameters from Gravitational-wave Events

Abstract The nuclear symmetry energy plays a role in determining both the nuclear properties of terrestrial matter as well as the astrophysical properties of neutron stars. The first measurement of the neutron star tidal deformability, from gravitational-wave event GW170817, provides a new way of probing the symmetry energy. In this work, we report on new constraints on the symmetry energy from GW170817. We focus in particular on the low-order coefficients: namely, the value of the symmetry energy at the nuclear saturation density, S 0, and the slope of the symmetry energy, L 0. We find that the gravitational-wave data are relatively insensitive to S 0, but that they depend strongly on L 0 and point to lower values of L 0 than have previously been reported, with a peak likelihood near L 0 ∼ 23 MeV. Finally, we use the inferred posteriors on L 0 to derive new analytic constraints on higher-order nuclear terms.

Gravitational wave denoising of binary black hole mergers with deep learning

Gravitational wave detection requires an in-depth understanding of the physical properties of gravitational wave signals, and the noise from which they are extracted. Understanding the statistical properties of noise is a complex endeavor, particularly in realistic detection scenarios. In this article we demonstrate that deep learning can handle the non-Gaussian and non-stationary nature of gravitational wave data, and showcase its application to denoise the gravitational wave signals generated by the binary black hole mergers GW150914, GW170104, GW170608 and GW170814 from advanced LIGO noise. To exhibit the accuracy of this methodology, we compute the overlap between the time-series signals produced by our denoising algorithm, and the numerical relativity templates that are expected to describe these gravitational wave sources, finding overlaps O≳0.99. We also show that our deep learning algorithm is capable of removing noise anomalies from numerical relativity signals that we inject in real advanced LIGO data. We discuss the implications of these results for the characterization of gravitational wave signals.

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

Estimating the parameters of gravitational wave signals detected by ground-based detectors requires an understanding of the properties of the detectors' noise. In particular, the most commonly used likelihood function for gravitational wave data analysis assumes that the noise is Gaussian, stationary, and of known frequency-dependent variance. The variance of the colored Gaussian noise is used as a whitening filter on the data before computation of the likelihood function. In practice the noise variance is not known and it evolves over timescales of dozens of seconds to minutes. We study two methods for estimating this whitening filter for ground-based gravitational wave detectors with the goal of performing parameter estimation studies. The first method uses large amounts of data separated from the specific segment we wish to analyze and computes the power spectral density of the noise through the mean-median Welch method. The second method uses the same data segment as the parameter estimation analysis, which potentially includes a gravitational wave signal, and obtains the whitening filter through a fit of the power spectrum of the data in terms of a sum of splines and Lorentzians. We compare these two methods and argue that the latter is more reliable for gravitational wave parameter estimation.

The Equation of State and Some Key Parameters of Neutron Stars: Constraints from GW170817, the Nuclear Data, and the Low-mass X-Ray Binary Data

Abstract In this work we parameterize the equation of state of dense neutron star (NS) matter with four pressure parameters of and then set the combined constraints with the data of GW170817 and the data of six low-mass X-ray binaries (LMXBs) with thermonuclear burst or alternatively the symmetry energy of the nuclear interaction. We find that the nuclear data effectively narrow down the possible range of , the gravitational-wave data plays the leading role in bounding , and the LMXB data as well as the lower bound on the maximal gravitational mass of non-rotating NSs govern the constraints on and . Using posterior samples of pressure parameters and some universal relations, we further investigate how the current data sets can advance our understanding of tidal deformability (Λ), moment of inertia (I), and binding energy (BE) of NSs. For a canonical mass of 1.4 M ⊙, we have , , , and if the constraints from the nuclear data and the gravitational-wave data have been jointly applied. For the joint analysis of gravitational-wave data and the LMXB data, we have , , , and . These results suggest that the current constraints on Λ and R still suffer from significant systematic uncertainties, while I 1.4 and BE1.4 are better constrained.

Machine-learning interpolation of population-synthesis simulations to interpret gravitational-wave observations: A case study

We report on advances to interpret current and future gravitational-wave events in light of astrophysical simulations. A machine-learning emulator is trained on numerical population-synthesis predictions and inserted into a Bayesian hierarchical framework. In this case study, a modest but state-of-the-art suite of simulations of isolated binary stars is interpolated across two event parameters and one population parameter. The validation process of our pipelines highlights how omitting some of the event parameters might cause errors in estimating selection effects, which propagates as systematics to the final population inference. Using LIGO/Virgo data from O1 and O2 we infer that black holes in binaries are most likely to receive natal kicks with one-dimensional velocity dispersion $\sigma$ = 105+44 km/s. Our results showcase potential applications of machine-learning tools in conjunction with population-synthesis simulations and gravitational-wave data.

More than the sum of its parts: Combining parametrized tests of extreme gravity

We connect two formalisms that describe deformations away from general relativity, one valid in the strong-field regime of neutrons stars and another valid in the radiative regime of gravitational waves: the post-Tolman-Oppenheimer-Volkoff and the parametrized-post-Einsteinian formalisms respectively. We find that post-Tolman-Oppenheimer-Volkoff deformations of the exterior metric of an isolated neutron star induce deformations in the orbital binding energy of a neutron star binary. Such a modification to the binding energy then percolates into the gravitational waves emitted by such a binary, with the leading-order post-Tolman-Oppenheimer-Volkoff modifications introducing a second post-Newtonian order correction to the gravitational wave phase. The lack of support in gravitational wave data for general relativity deformations at this post-Newtonian order can then be used to place constraints post-Tolman-Oppenheimer-Volkoff parameters. As an application, we use the binary neutron star merger event GW170817 to place the constraint $-2.4 \leq \chi \leq 44$ (at 90% credibility) on a combination of post-Tolman-Oppenheimer-Volkoff parameters. We also explore the implications of this result to the possible deformations of the mass-radius relation of neutron stars allowed within this formalism. This work opens the path towards theory-independent tests of gravity, combining astronomical observations of neutron stars and gravitational wave observations.

Gravitational wave observations, distance measurement uncertainties, and cosmology

Gravitational waves from the coalescence of compact binaries, together with an associated electromagnetic counterpart, are ideal probes of cosmological models. As demonstrated with GW170817, such multimessenger observations allow one to use the source as a standard siren, analog of standard candles in conventional astronomy, in order to measure cosmological parameters such as the Hubble constant. No cosmological ladder is needed to estimate the source luminosity distance from the detected gravitational waves. The error on the luminosity distance plays a crucial r\^ole in the error budget for the inference of the Hubble constant. In this paper, we provide analytic expressions for the statistical errors on the luminosity distance inferred from gravitational wave data as a function of the sky position and the detector network. In particular, we take into account degeneracy in the parameter space of the gravitational waveform showing that in certain conditions on the gravitational-wave detector network and the source sky position it may not be possible to estimate the luminosity distance of the source. Our analytic approximants shows a good agreement with the uncertainties measured with Bayesian samplers and simulated data. We also present implications for the estimation error on the Hubble constant.