Numerical Relativity Waveforms Research Articles

Phenomenological model of gravitational self-force enhanced tides in inspiraling binary neutron stars

Gravitational waves from inspiraling binary neutron stars provide unique access to ultradense nuclear matter and offer the ability to constrain the currently unknown neutron star equation-of-state through tidal measurements. This, however, requires the availability of accurate and efficient tidal waveform models. In this paper we present henom, a new phenomenological tidal phase model for the inspiral of neutron stars in the frequency domain, which captures the gravitational self-force informed tidal contributions of the time-domain effective-one-body model esum. henom is highly faithful and computationally efficient, and by choosing a modular approach, it can be used in conjunction with frequency-domain binary black hole waveform model to generate the complete phase for a binary neutron star inspiral. henom is valid for neutron star binaries with unequal masses and mass ratios between 1 and 3, and dimensionless tidal deformabilities up to 5000. Furthermore, henom does not assume universal relations or parametrized equations of state, hence allowing for exotic matter analyses and beyond standard model physics investigations. We demonstrate the efficacy and accuracy of our model through comparisons against esum, numerical relativity waveforms and full Bayesian inference, including a reanalysis of the binary neutron star observation GW170817. Published by the American Physical Society 2024

Iterative extraction of overtones from black hole ringdown

Abstract Extraction of multiple quasinormal modes (QNMs) from ringdown gravitational waves emitted from a binary black hole coalescence is a touchstone to test whether a remnant black hole is described by the Kerr spacetime in general relativity. However, it is not straightforward to check the consistency between the ringdown signal and the QNM frequencies predicted by the linear perturbation theory. While the longest-lived mode can be extracted in a stable manner, the higher overtones damp more quickly and hence the fitting of overtones tends to end up with the overfit. To improve the extraction of overtones, we propose an iterative procedure consisting of fitting and subtraction of the longest-lived mode of the ringdown waveform in the time domain. Through the analyses of the mock waveform and numerical relativity waveform, we clarify that the iterative procedure allows us to extract the overtones in a more stable manner.

Differentiable and hardware-accelerated waveforms for gravitational wave data analysis

We propose the use of automatic differentiation through the programming framework for accelerating a variety of analysis tasks throughout gravitational wave (GW) science. Firstly, we demonstrate that complete waveforms which cover the inspiral, merger, and ringdown of binary black holes (i.e., IMRPhenomD) can be written in and demonstrate that the serial evaluation speed of the waveform (and its derivative) is similar to the implementation in . Moreover, allows for graphics processing unit–accelerated waveform calls which can be over an order of magnitude faster than serial evaluation on a CPU. We then focus on three applications where efficient and differentiable waveforms are essential. Firstly, we demonstrate how gradient descent can be used to optimize the ∼200 coefficients that are used to calibrate the waveform model. In particular, we demonstrate that the typical with numerical relativity waveforms can be improved by more than 50%. Secondly, we show that Fisher forecasting calculations can be sped up by ∼3–5× (on a CPU) with no loss in accuracy. This increased speed makes Fisher forecasting for a population of events substantially simpler. Finally, we show that gradient-based samplers like Hamiltonian Monte Carlo lead to significantly reduced autocorrelation values when compared to traditional Monte Carlo methods. Since differentiable waveforms have substantial advantages for a variety of tasks throughout GW science, we propose that waveform developers use to build new waveforms moving forward. Our waveform code, , can be found on GitHub website and will continue to be updated with new waveforms as they are implemented. Published by the American Physical Society 2024

Accuracy limitations of existing numerical relativity waveforms on the data analysis of current and future ground-based detectors

Accuracy limitations of existing numerical relativity waveforms on the data analysis of current and future ground-based detectors

Measuring source properties and quasinormal mode frequencies of heavy massive black-hole binaries with LISA

The Laser Interferometer Space Antenna (LISA) will be launched in the mid-2030s. It promises to observe the coalescence of massive black-hole (BH) binaries with signal-to-noise ratios (SNRs) reaching thousands. Crucially, it will detect some of these binaries with high SNR in both the inspiral and the merger-ringdown stages. Such signals are ideal for tests of general relativity (GR) using information from the whole waveform. Here, we consider astrophysically motivated binary systems at the high-mass end of the population observable by LISA and simulate their signals using the newly developed multipolar effective-one-body model: pSEOBNRv5HM. The merger-ringdown signal in this model depends on the binary properties (masses and spins) and also on parameters that describe fractional deviations from the GR quasinormal mode (complex) frequencies of the remnant BH. Performing full Bayesian analyses, we assess to which accuracy LISA will be able to constrain deviations from GR in the ringdown signal when using information from the whole signal. We find that these deviations can typically be constrained to within 10% and in the best cases to within 1%. We also show that with this model we can measure the binary masses and spins with great accuracy even for very massive BH systems with low SNR in the inspiral. In particular, individual source-frame masses can typically be constrained to within 10% and as precisely as 1%, and individual spins can typically be constrained to within 0.1 and, in the best cases, to within 0.001. We also probe the accuracy of the SEOBNRv5HM waveform family by performing synthetic injections of GR numerical-relativity waveforms. Using a novel method that we develop here to quantify the impact of systematic errors, we show that, already for sources with SNR O(100), we would measure erroneous deviations from GR due to waveform model inaccuracies. One of the main sources of error is the mismodeling of the relative alignment between harmonics. These results confirm the need for improving waveform models to perform tests of GR with binary BHs observed at high SNR by LISA. Published by the American Physical Society 2024

New and robust gravitational-waveform model for high-mass-ratio binary neutron star systems with dynamical tidal effects

For the analysis of gravitational-wave signals, fast and accurate gravitational-waveform models are required. These enable us to obtain information on the system properties from compact binary mergers. In this article, we introduce the model, which contains a closed-form expression that describes tidal effects, focusing on the description of binary neutron star systems. The model improves upon previous versions by employing a larger set of numerical-relativity data for its calibration, by including high-mass ratio systems covering also a wider range of equations of state. It also takes into account dynamical tidal effects and the known post-Newtonian mass-ratio dependence of individual calibration parameters. We implemented the model in the publicly available uite software library by augmenting different binary black hole waveform models (, , and ). We test the validity of by comparing it with numerical-relativity waveforms, as well as other tidal models. Finally, we perform parameter estimation for GW170817 and GW190425 with the new tidal approximant and find overall consistent results with respect to previous studies. Published by the American Physical Society 2024

Comparing Numerical Relativity and Perturbation Theory Waveforms for a Non-Spinning Equal-Mass Binary

Past studies have empirically demonstrated a surprising agreement between gravitational waveforms computed using adiabatic–driven–inspiral point–particle black hole perturbation theory (ppBHPT) and numerical relativity (NR) following a straightforward calibration step, sometimes referred to as α-β scaling. Specifically focusing on the quadrupole mode, this calibration technique necessitates only two time-independent parameters to scale the overall amplitude and time coordinate. In this article, part of a Special Issue, we investigate this scaling for non-spinning binaries at the equal-mass limit. Even without calibration, NR and ppBHPT waveforms exhibit an unexpected degree of similarity after accounting for different mass scale definitions. Post-calibration, good agreement between ppBHPT and NR waveforms extends nearly up to the point of the merger. We also assess the breakdown of the time-independent assumption of the scaling parameters, shedding light on current limitations and suggesting potential generalizations for the α-β scaling technique.

Accuracy of numerical relativity waveforms with respect to space-based gravitational wave detectors

As with the laser interferometer gravitational-wave observatory (LIGO), the matched filtering technique will be critical to the data analysis of gravitational wave detection by space-based detectors, including LISA, Taiji and Tianqin. Waveform templates are the basis for such matched filtering techniques. To construct ready-to-use waveform templates, numerical relativity waveforms are a starting point. Therefore, the accuracy issue of numerical relativity waveforms is critically important. There are many investigations regarding this issue with respect to LIGO. But unfortunately there are few results on this issue with respect to space-based detectors. The current paper investigates this problem. Our results indicate that the existing numerical relativity waveforms are as accurate as 99% with respect to space-based detectors, including LISA, Taiji and Tianqin. Such an accuracy level is comparable to that with respect to LIGO.

Agnostic black hole spectroscopy: Quasinormal mode content of numerical relativity waveforms and limits of validity of linear perturbation theory

Agnostic black hole spectroscopy: Quasinormal mode content of numerical relativity waveforms and limits of validity of linear perturbation theory

Morphology-independent characterization method of postmerger gravitational wave emission from binary neutron star coalescences

Gravitational waves (GWs) emitted during the coalescence of binary neutron star (BNS) systems carry information about the equation of state (EoS) describing the extremely dense matter inside neutron stars (NSs). In particular, the EoS determines the fate of the binary after the merger: a prompt collapse to black hole (BH), or the formation of a NS remnant that is either stable or survives up to a few seconds before collapsing to a BH. Determining the evolution of a BNS system will therefore place strong constraints on the EoS. We present a morphology-independent method, developed in the framework of the coherentWaveBurst analysis of signals from ground-based interferometric detectors of GWs. The method characterizes the time-frequency postmerger GW emission from a BNS system, and determines whether, after the merger, it formed a remnant NS or promptly collapsed to a BH. We measure the following quantities to characterize the postmerger emission: ratio of signal energies and match of luminosity profile in different frequency bands, weighted central frequency and bandwidth. From these quantities, based on the study of signals simulated through injections of numerical relativity waveforms, we build a statistics to discriminate between the different scenarios after the merger. Finally, we test our method on a set of signals simulated with new models, to estimate its efficiency as a function of the source distance.

Unraveling information about supranuclear-dense matter from the complete binary neutron star coalescence process using future gravitational-wave detector networks

Gravitational waves provide us with an extraordinary tool to study the matter inside neutron stars. In particular, the postmerger signal probes an extreme temperature and density regime and will help reveal information about the equation of state of supranuclear-dense matter. Although current detectors are most sensitive to the signal emitted by binary neutron stars before the merger, the upgrades of existing detectors and the construction of the next generation of detectors will make postmerger detections feasible. For this purpose, we present a new analytical, frequency-domain model for the inspiral-merger-postmerger signal emitted by binary neutron star systems. The inspiral and merger parts of the signals are modeled with IMRPhenomD_NRTidalv2, and we describe the main emission peak of the postmerger with a three-parameter Lorentzian, using two different approaches: one in which the Lorentzian parameters are kept free, and one in which we model them via quasiuniversal relations. We test the performance of our new complete waveform model in parameter estimation analyses, studying simulated signals obtained both from our developed model and by injecting numerical relativity waveforms. We investigate the performance of different detector networks to determine the improvement that future detectors will bring to our analysis. We consider Advanced $\mathrm{LIGO}+$ and Advanced $\mathrm{Virgo}+$, KAGRA, and LIGO-India. We also study the possible impact of a detector with high sensitivity in the kilohertz band like NEMO, and finally we compare these results to the ones we obtain with third-generation detectors, the Einstein Telescope and the Cosmic Explorer.

Using rational filters to uncover the first ringdown overtone in GW150914

There have been debates in the literature about the existence of the first overtone in the ringdown of GW150914. We develop a novel Bayesian framework to reanalyze the data of this event, by incorporating a new technique, the ``rational filter'' that can clean particular modes from the ringdown signal. We examine the existence of the first overtone in GW150914 from multiple novel perspectives. First, we confirm that the estimates of the remnant black hole mass and spin are more consistent with those obtained from the full inspiral-merger-ringdown signal when including the first overtone at an early stage of the ringdown (right after the inferred signal peak); such improvement fades away at later times. Second, we formulate a new way to compare the ringdown models with and without the first overtone by calculating the Bayes factor at different times during the ringdown. We obtain a Bayes factor of 600 at the time when the signal amplitude reaches its peak. The Bayes factor decreases sharply when moving away from the peak time and eventually oscillates around a small value when the overtone signal is expected to have decayed. Third, we clean the fundamental mode from the ringdown of GW150914 and estimate the amplitudes of the modes using the filtered data with Markov chain Monte Carlo (MCMC). The inferred amplitude of the fundamental mode is $\ensuremath{\sim}0$ whereas the amplitude of the first overtone remains almost unchanged, implying that the filtered data is consistent with a first-overtone-only template. Similarly, if we remove the first overtone from the GW150914 data, the filtered data are consistent with a fundamental-mode-only template. Finally, after removing the fundamental mode, we use MCMC to infer the remnant black hole mass and spin from the first overtone alone. We find the posteriors are still informative and consistent with those inferred from the fundamental mode. The conclusions are also verified through simulations in Gaussian noise using a GW150914-like numerical relativity waveform.

Study of the intermediate mass ratio black hole binary merger up to 1000:1 with numerical relativity

We explicitly demonstrate that current numerical relativity techniques are able to accurately evolve black hole binaries with mass ratios of the order of 1000:1. This proof of principle is relevant for future third generation gravitational wave detectors and space mission LISA, as by purely numerical methods we would be able to accurately compute gravitational waves from the last stages of black hole mergers, as directly predicted by general relativity. We perform a sequence of simulations in the intermediate to small mass ratio regime, , with the small hole starting from rest at a proper distance . We compare these headon full numerical evolutions with the corresponding semianalytic point particle perturbative results finding an impressive agreement for the total gravitational radiated energy and linear momentum as well as for the waveform spectra. We display numerical convergence of the results and identify the minimal numerical resolutions required to accurately solve for these very low amplitude gravitational waves. This work represents a first step towards the considerable challenge of applying numerical-relativity waveforms to interpreting gravitational-wave observations by LISA and next-generation ground-based gravitational-wave detectors.

Resonant tides in binary neutron star mergers: Analytical-numerical relativity study

Resonant excitations of $f$-modes in binary neutron star coalescences influence the gravitational waves (GWs) emission in both quasicircular and highly eccentric mergers and can deliver information on the star interior. Most models of resonant tides are built using approximate, perturbative approaches and thus require to be carefully validated against numerical relativity (NR) simulations in the high-frequency regime. We perform detailed comparisons between a set of high-resolution NR simulations and the state of the art effective one body (EOB) model ${\tt TEOBResumS}$ with various tidal potentials and including a model for resonant tides. For circular mergers, we find that $f$-mode resonances can improve the agreement between EOB and NR, but there is no clear evidence that the tidal enhancement after contact is due to a resonant mechanism. Tidal models with $f$-mode resonances do not consistently reproduce, at the same time, the NR waveforms and the energetics within the errors, and their performances is comparable to resummed tidal models without resonances. For highly eccentric mergers, we show for the first time that our EOB model reproduces the bursty NR waveform to a high degree of accuracy. However, the considered resonant model does not capture the $f$-mode oscillations excited during the encounters and present in the NR waveform. Finally, we analyze GW170817 with both adiabatic and dynamical tides models and find that the data shows no evidence in favor of models including dynamical tides. This is in agreement with the fact that resonant tides are measured at very high frequencies, which are not available for GW170817 but might be tested with next generation detectors.

Upgraded waveform model of eccentric binary black hole based on effective-one-body-numerical-relativity for spin-aligned binary black holes

Effective one body numerical relativity waveform models for spin-aligned binary black holes (SEOBNR) are based on the effective one body theoretical framework and numerical relativity simulation results. SEOBNR models have evolved through version 1 to version 4. We recently extended SEOBNRv1 model to SEOBNRE (Effective One Body Numerical Relativity waveform models for Spin-aligned binary black holes along Eccentric orbit) model which is also valid for spin-aligned binary black hole coalescence along eccentric orbit. In this paper, we update our previous SEOBNRE model to make it consistent to SEOBNRv4 which is the most widely used SEOBNR waveform model. This upgraded SEOBNRE model improves accuracy compared to previous SEOBNRE model, especially for highly spinning black holes. For spin-aligned binary black holes with mass ratio [Formula: see text], dimensionless spin [Formula: see text] and orbital eccentricity [Formula: see text] at reference frequency [Formula: see text] ([Formula: see text] is the total mass of the binary black hole, [Formula: see text]Hz), the upgraded SEOBNRE model can always fit numerical relativity waveform better than 98.2%. For most cases, the fitting factor can even be better than 99%.

Numerical-relativity surrogate modeling with nearly extremal black-hole spins

Numerical relativity (NR) simulations of binary black hole (BBH) systems provide the most accurate gravitational wave predictions, but at a high computational cost—especially when the black holes have nearly extremal spins (i.e. spins near the theoretical upper limit) or very unequal masses. Recently, the technique of reduced order modeling has enabled the construction of ‘surrogate models’ trained on an existing set of NR waveforms. Surrogate models enable the rapid computation of the gravitational waves emitted by BBHs. Typically these models are used for interpolation to compute gravitational waveforms for BBHs with mass ratios and spins within the bounds of the training set. Because simulations with nearly extremal spins are so technically challenging, surrogate models almost always rely on training sets with only moderate spins. In this paper, we explore how well surrogate models can extrapolate to nearly extremal spins when the training set only includes moderate spins. For simplicity, we focus on one-dimensional surrogate models trained on NR simulations of BBHs with equal masses and equal, aligned spins. We assess the performance of the surrogate models at higher spin magnitudes by calculating the mismatches between extrapolated surrogate model waveforms and NR waveforms, by calculating the differences between extrapolated and NR measurements of the remnant black-hole mass, and by testing how the surrogate model improves as the training set extends to higher spins. We find that while extrapolation in this one-dimensional case is viable for current detector sensitivities, surrogate models for next-generation detectors should use training sets that extend to nearly extremal spins.

Gravitational wave inference on a numerical-relativity simulation of a black hole merger beyond general relativity

We apply common gravitational wave inference procedures on binary black hole merger waveforms beyond general relativity. We consider dynamical Chern-Simons gravity, a modified theory of gravity with origins in string theory and loop quantum gravity. This theory introduces an additional parameter $\ell$, corresponding to the length-scale below which beyond-general-relativity effects become important. We simulate data based on numerical relativity waveforms produced under an approximation to this theory, which differ from those of general relativity in the strongly nonlinear merger regime. We consider a system with parameters similar to GW150914 with different values of $\ell$ and signal-to-noise ratios. We perform two analyses of the simulated data. The first is a template-based analysis that uses waveforms derived under general relativity and allows us to identify degeneracies between the two waveform morphologies. The second is a morphology-independent analysis based on BayesWave that does not assume that the signal is consistent with general relativity. The BayesWave analysis faithfully reconstructs the simulated signals. However, waveform models derived under general relativity are unable to fully mimic the simulated modified-gravity signals and such a deviation would be identifiable with existing inference tools. Depending on the magnitude of the deviation, we find that the templated analysis can under perform the morphology-independent analysis in fully recovering simulated beyond-GR waveforms even for achievable signal-to-noise ratios $\gtrsim 20{-}30$.

Quasinormal-mode filters: A new approach to analyze the gravitational-wave ringdown of binary black-hole mergers

We propose two frequency-domain filters to analyze ringdown signals of binary black hole mergers. The first rational filter is constructed based on a set of (arbitrary) quasi-normal modes (QNMs) of the remnant black holes, whereas the second full filter comes from the transmissivity of the remnant black holes. The two filters can remove corresponding QNMs from original time-domain ringdowns, while changing early inspiral signals in a trivial way - merely a time and phase shift. After filtering out dominant QNMs, we can visualize the existence of various subdominant effects. For example, by applying our filters to a GW150914-like numerical relativity (NR) waveform, we find second-order effects in the (l = 4, m = 4), (l = 5, m = 4) and (l = 5, m = 5) harmonics; the spherical-spheroidal mixing mode in the (l = 2,m = 2) harmonic; and a mixing mode in the (l = 2,m = 1) harmonic due to a gravitational recoil. In another NR simulation where two component spins are anti-aligned with the orbital angular momentum, we also find retrograde modes. The filters are sensitive to the remnant properties (i.e., mass and spin) and thus have a potential application to future data analyses and parameter estimations. We also investigate the stability of the full filter. Its connection to the instability of QNM spectra is discussed.

Fixing the BMS frame of numerical relativity waveforms with BMS charges

The Bondi-van der Burg-Metzner-Sachs (BMS) group, which uniquely describes the symmetries of asymptotic infinity and therefore of the gravitational waves that propagate there, has become increasingly important for accurate modeling of waveforms. In particular, waveform models, such as post-Newtonian (PN) expressions, numerical relativity (NR), and black hole perturbation theory, produce results that are in different BMS frames. Consequently, to build a model for the waveforms produced during the merging of compact objects, which ideally would be a hybridization of PN, NR, and black hole perturbation theory, one needs a fast and robust method for fixing the BMS freedoms. In this work, we present the first means of fixing the entire BMS freedom of NR waveforms to match the frame of either PN waveforms or black hole perturbation theory. We achieve this by finding the BMS transformations that change certain charges in a prescribed way -- e.g., finding the center-of-mass transformation that maps the center-of-mass charge to a mean of zero. We find that this new method is 20 times faster, and more correct when mapping to the superrest frame, than previous methods that relied on optimization algorithms. Furthermore, in the course of developing this charge-based frame fixing method, we compute the PN expression for the Moreschi supermomentum to 3PN order without spins and 2PN order with spins. This Moreschi supermomentum is effectively equivalent to the energy flux or the null memory contribution at future null infinity $\mathscr{I}^{+}$. From this PN calculation, we also compute oscillatory ($m\not=0$ modes) and spin-dependent memory terms that have not been identified previously or have been missing from strain expressions in the post-Newtonian literature.

AI and extreme scale computing to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non-precessing black hole mergers

We use artificial intelligence (AI) to learn and infer the physics of higher order gravitational wave modes of quasi-circular, spinning, non precessing binary black hole mergers. We trained AI models using 14 million waveforms, produced with the surrogate model NRHybSur3dq8, that include modes up to ℓ≤4 and (5,5), except for (4,0) and (4,1), that describe binaries with mass-ratios q≤8, individual spins s{1,2}z∈[−0.8,0.8], and inclination angle θ∈[0,π]. Our probabilistic AI surrogates can accurately constrain the mass-ratio, individual spins, effective spin, and inclination angle of numerical relativity waveforms that describe such signal manifold. We compared the predictions of our AI models with Gaussian process regression, random forest, k-nearest neighbors, and linear regression, and with traditional Bayesian inference methods through the PyCBC Inference toolkit, finding that AI outperforms all these approaches in terms of accuracy, and are between three to four orders of magnitude faster than traditional Bayesian inference methods. Our AI surrogates were trained within 3.4 hours using distributed training on 1,536 NVIDIA V100 GPUs in the Summit supercomputer.