arXiv subjects

Scott E. Field

Publications and source records attributed to Scott E. Field.

At least 37 records · Page 2Linked to original sources

arXiv2025

Modeling the BMS transformation induced by a binary black hole merger

Understanding the characteristics of the remnant black hole formed in a binary black hole merger is crucial for conducting gravitational wave astronomy. Typically, models of remnant black holes provide information about their mass, spin, and kick velocity. However, other information related to the supertranslation symmetries of the BMS group, such as the memory effect, is also important for characterizing the final state of the system. In this work, we build a model of the BMS transformation that maps a binary black hole's inspiral frame to the remnant black hole's canonical rest frame. Training data for this model are created using high-precision numerical relativity simulations of quasi-circular systems with mass ratios $q \le 8$ and spins parallel to the orbital angular momentum with magnitudes $χ_{1}, χ_{2} \le 0.8$. We use Gaussian Process Regression to model the BMS transformations over the three-dimensional parameter space $\left(q, χ_{1}^{z}, χ_{2}^{z}\right)$. The physics captured by this model is strictly non-perturbative and cannot be obtained from post-Newtonian approximations alone, as it requires knowledge of the strong nonlinear effects that are sourced during the merger. Apart from providing the first model of the supertranslation induced by a binary black hole merger, we also find that the kick velocities predicted using Cauchy-characteristic evolution waveforms are, on average, $\sim5\%$ larger than the ones obtained from extrapolated waveforms. Our work has broad implications for improving gravitational wave models and studying the large-scale impact of memory, such as on the cosmological background. The fits produced in this work are available through the Python package $\texttt{surfinBH}$ under the name $\texttt{NRSur3dq8BMSRemnant}$.

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arXiv2024

A fully precessing higher-mode surrogate model of effective-one-body waveforms

We present a surrogate model of \texttt{SEOBNRv4PHM}, a fully precessing time-domain effective-one-body waveform model including subdominant modes. We follow an approach similar to that used to build recent numerical relativity surrogate models. Our surrogate is 5000M in duration, covers mass-ratios up to 1:20 and dimensionless spin magnitudes up to 0.8. Validating the surrogate against an independent test set we find that the bulk of the surrogate errors is less than $\sim 1\%$ in mismatch, which is similar to the modelling error of \texttt{SEOBNRv4PHM} itself. At high total mass a few percent of configurations can exceed this threshold if they are highly precessing and they exceed a mass-ratio of 1:4. This surrogate is nearly two orders of magnitude faster than the underlying time-domain \texttt{SEOBNRv4PHM} model and can be evaluated in $\sim 50$ ms. Bayesian inference analyses with \texttt{SEOBNRv4PHM} are typically very computationally demanding and can take from weeks to months to complete. The two order of magnitude speedup attained by our surrogate model enables practical parameter estimation analyses with this waveform family. This is \emph{crucial} because Bayesian inference allows us to recover the masses and spins of binary black hole mergers given a model of the emitted gravitational waveform along with a description of the noise.

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arXiv2024

Toward exponentially-convergent simulations of extreme-mass-ratio inspirals: A time-domain solver for the scalar Teukolsky equation with singular source terms

Gravitational wave signals from extreme mass ratio inspirals are a key target for space-based gravitational wave detectors. These systems are typically modeled as a distributionally-forced Teukolsky equation, where the smaller black hole is treated as a Dirac delta distribution. Time-domain solvers often use regularization approaches that approximate the Dirac distribution that often introduce small length scales and are a source of systematic error, especially near the smaller black hole. We describe a multi-domain discontinuous Galerkin method for solving the distributionally-forced Teukolsky equation that describes scalar fields evolving on a Kerr spacetime. To handle the Dirac delta, we expand the solution in spherical harmonics and recast the sourced Teukolsky equation as a first-order, one-dimensional symmetric hyperbolic system. This allows us to derive the method's numerical flux to correctly account for the Dirac delta. As a result, our method achieves global spectral accuracy even at the source's location. To connect the near field to future null infinity, we use the hyperboloidal layer method, allowing us to supply outer boundary conditions and providing direct access to the far-field waveform. We document several numerical experiments where we test our method, including convergence tests against exact solutions, energy luminosities for circular orbits, the scheme's superconvergence properties at future null infinity, and the late-time tail behavior of the scalar field. We also compare two systems that arise from different choices of the first-order reduction variables, finding that certain choices are numerically problematic in practice. The methods developed here may be beneficial when computing gravitational self-force effects, where the regularization procedure has been developed for the spherical harmonic modes and high accuracy is needed at the Dirac delta's location.

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arXiv2024

High-Precision Ringdown Surrogate Model for Non-Precessing Binary Black Holes

Highly precise and robust waveform models are required as improvements in detector sensitivity enable us to test general relativity with more precision than ever before. In this work, we introduce a spin-aligned surrogate ringdown model. This ringdown surrogate, NRSur3dq8_RD, is built with numerical waveforms produced using Cauchy-characteristic evolution. In addition, these waveforms are in the superrest frame of the remnant black hole allowing us to do a correct analysis of the ringdown spectrum. The novel prediction of our surrogate model is complex-valued quasinormal mode (QNM) amplitudes, with median relative errors of $10^{-2}-10^{-3}$ over the parameter space. Like previous remnant surrogates, we also predict the remnant black hole's mass and spin. The QNM mode amplitude errors translate into median errors on ringdown waveforms of $10^{-4}$. The high accuracy and QNM mode content provided by our surrogate will enable high-precision ringdown analyses such as tests of general relativity. Our ringdown model is publicly available through the python package surfinBH.

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arXiv2024

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.

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arXiv2023

Numerical relativity surrogate model with memory effects and post-Newtonian hybridization

Numerical relativity simulations provide the most precise templates for the gravitational waves produced by binary black hole mergers. However, many of these simulations use an incomplete waveform extraction technique -- extrapolation -- that fails to capture important physics, such as gravitational memory effects. Cauchy-characteristic evolution (CCE), by contrast, is a much more physically accurate extraction procedure that fully evolves Einstein's equations to future null infinity and accurately captures the expected physics. In this work, we present a new surrogate model, NRHybSur3dq8$\_$CCE, built from CCE waveforms that have been mapped to the post-Newtonian (PN) BMS frame and then hybridized with PN and effective one-body (EOB) waveforms. This model is trained on 102 waveforms with mass ratios $q\leq8$ and aligned spins $χ_{1z}, \, χ_{2z} \in \left[-0.8, 0.8\right]$. The model spans the entire LIGO-Virgo-KAGRA (LVK) frequency band (with $f_{\text{low}}=20\text{Hz}$) for total masses $M\gtrsim2.25M_{\odot}$ and includes the $\ell\leq4$ and $(\ell,m)=(5,5)$ spin-weight $-2$ spherical harmonic modes, but not the $(3,1)$, $(4,2)$ or $(4,1)$ modes. We find that NRHybSur3dq8$\_$CCE can accurately reproduce the training waveforms with mismatches $\lesssim2\times10^{-4}$ for total masses $2.25M_{\odot}\leq M\leq300M_{\odot}$ and can, for a modest degree of extrapolation, capably model outside of its training region. Most importantly, unlike previous waveform models, the new surrogate model successfully captures memory effects.

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arXiv2023

Survey of gravitational wave memory in intermediate mass ratio binaries

The non-linear gravitational wave (GW) memory effect is a distinct prediction in general relativity. While the effect has been well studied for comparable mass binaries, it has mostly been overlooked for intermediate mass ratio inspirals (IMRIs). We offer a comprehensive analysis of the phenomenology and detectability of memory effects, including contributions from subdominant harmonic modes, in heavy IMRIs consisting of a stellar mass black hole and an intermediate mass black hole. When formed through hierarchical mergers, for example when a GW190521-like remnant captures a stellar mass black hole, IMRI systems have a large total mass, large spin on the primary, and possibly residual eccentricity; features that potentially raise the prospect for memory detection. We compute both the displacement and spin non-linear GW memory from the $m \neq 0$ gravitational waveforms computed within a black hole perturbation theory framework that is partially calibrated to numerical relativity waveforms. We probe the dependence of memory effects on mass ratio, spin, and eccentricity and consider the detectability of a memory signal from IMRIs using current and future GW detectors. We find that (i) while eccentricity introduces additional features in both displacement and spin memory, it does not appreciatively change the prospects of detectability, (ii) including higher modes into the memory computation can increase singal-to-noise (SNR) values by about 7\% in some cases, (iii) the SNR from displacement memory dramatically increases as the spin approaches large, positive values, (iv) spin memory from heavy IMRIs would, however, be difficult to detect with future generation detectors even from highly spinning systems. Our results suggest that hierarchical binary black hole mergers may be a promising source for detecting memory and could favorably impact memory forecasts.

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arXiv2023

Discontinuous Galerkin method for linear wave equations involving derivatives of the Dirac delta distribution

Linear wave equations sourced by a Dirac delta distribution $δ(x)$ and its derivative(s) can serve as a model for many different phenomena. We describe a discontinuous Galerkin (DG) method to numerically solve such equations with source terms proportional to $\partial^n δ/\partial x^n$. Despite the presence of singular source terms, which imply discontinuous or potentially singular solutions, our DG method achieves global spectral accuracy even at the source's location. Our DG method is developed for the wave equation written in fully first-order form. The first-order reduction is carried out using a distributional auxiliary variable that removes some of the source term's singular behavior. While this is helpful numerically, it gives rise to a distributional constraint. We show that a time-independent spurious solution can develop if the initial constraint violation is proportional to $δ(x)$. Numerical experiments verify this behavior and our scheme's convergence properties by comparing against exact solutions.

math.NA↗

arXiv2023

Fast evaluation of far-field signals for time-domain wave propagation

Time-domain simulation of wave phenomena on a finite computational domain often requires a fictitious outer boundary. An important practical issue is the specification of appropriate boundary conditions on this boundary, often conditions of complete transparency. Attention to this issue has been paid elsewhere, and here we consider a different, although related, issue: far-field signal recovery. Namely, from smooth data recorded on the outer boundary we wish to recover the far-field signal which would reach arbitrarily large distances. These signals encode information about interior scatterers and often correspond to actual measurements. This article expresses far-field signal recovery in terms of time-domain convolutions, each between a solution multipole moment recorded at the boundary and a sum-of-exponentials kernel. Each exponential corresponds to a pole term in the Laplace transform of the kernel, a finite sum of simple poles. Greengard, Hagstrom, and Jiang have derived the large-$\ell$ (spherical-harmonic index) asymptotic expansion for the pole residues, and their analysis shows that, when expressed in terms of the exact sum-of-exponentials, large-$\ell$ signal recovery is plagued by cancellation errors. Nevertheless, through an alternative integral representation of the kernel and its subsequent approximation by a {\em smaller} number of exponential terms (kernel compression), we are able to alleviate these errors and achieve accurate signal recovery. We empirically examine scaling relations between the parameters which determine a compressed kernel, and perform numerical tests of signal "teleportation" from one radial value $r_1$ to another $r_2$, including the case $r_2=\infty$. We conclude with a brief discussion on application to other hyperbolic equations posed on non-flat geometries where waves undergo backscatter.

math.NA↗

arXiv2023

Remnant black hole properties from numerical-relativity-informed perturbation theory and implications for waveform modelling

During binary black hole (BBH) mergers, energy and momenta are carried away from the binary system as gravitational radiation. Access to the radiated energy and momenta allows us to predict the properties of the remnant black hole. We develop a Python package gw_remnant to compute the remnant mass, remnant spin, peak luminosity, and the final kick imparted on the remnant black hole from the gravitational radiation. Using this package, we compute the remnant properties of the final black hole in case of non-spinning BBH mergers with mass ratios ranging from q=2.5 to q=1000 using waveform modes generated from BHPTNRSur1dq1e4, a recently developed numerical-relativity-informed surrogate model based on black-hole perturbation theory framework. We validate our results against the remnant properties estimated from numerical relativity (NR) surrogate models in the comparable mass ratio regime and against recently available high-mass-ratio NR simulations at q=[15,32,64]. We find that our remnant property estimates computed from fluxes at future null infinity closely match the estimates obtained from the NR surrogate model of apparent horizon data. Using Gaussian process regression fitting methods, we train a surrogate model, {BHPTNR_Remnant, for the properties of the remnant black hole arising from BBH mergers with mass ratios from q=2.5 to q=1000. Finally, we discuss potential improvements in the BHPTNRSur1dq1e4 waveform model when including remnant information. We make both the gw_remnant and BHPTNR_Remnant packages publicly available.

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arXiv2022

Evidence of large recoil velocity from a black hole merger signal

The final black hole left behind after a binary black hole merger can attain a recoil velocity, or a "kick", reaching values up to 5000 km/s. This phenomenon has important implications for gravitational wave astronomy, black hole formation scenarios, testing general relativity, and galaxy evolution. We consider the gravitational wave signal from the binary black hole merger GW200129_065458 (henceforth referred to as GW200129), which has been shown to exhibit strong evidence of orbital precession. Using numerical relativity surrogate models, we constrain the kick velocity of GW200129 to $v_f \sim 1542^{+747}_{-1098}$ km/s or $v_f \gtrsim 698$ km/s (one-sided limit), at 90\% credibility. This marks the first identification of a large kick velocity for an individual gravitational wave event. Given the kick velocity of GW200129, we estimate that there is a less than $0.48\%$ ($7.7\%$) probability that the remnant black hole after the merger would be retained by globular (nuclear star) clusters. Finally, we show that kick effects are not expected to cause biases in ringdown tests of general relativity for this event, although this may change in the future with improved detectors.

astro-ph.HE↗

arXiv2022

Surrogate model for gravitational wave signals from non-spinning, comparable- to large-mass-ratio black hole binaries built on black hole perturbation theory waveforms calibrated to numerical relativity

We present a reduced-order surrogate model of gravitational waveforms from non-spinning binary black hole systems with comparable to large mass-ratio configurations. This surrogate model, \texttt{BHPTNRSur1dq1e4}, is trained on waveform data generated by point-particle black hole perturbation theory (ppBHPT) with mass ratios varying from 2.5 to 10,000. \texttt{BHPTNRSur1dq1e4} extends an earlier waveform model, \texttt{EMRISur1dq1e4}, by using an updated transition-to-plunge model, covering longer durations up to 30,500 $m_1$ (where $m_1$ is the mass of the primary black hole), includes several more spherical harmonic modes up to $\ell=10$, and calibrates subdominant modes to numerical relativity (NR) data. In the comparable mass-ratio regime, including mass ratios as low as $2.5$, the gravitational waveforms generated through ppBHPT agree surprisingly well with those from NR after this simple calibration step. We also compare our model to recent SXS and RIT NR simulations at mass ratios ranging from $15$ to $32$, and find the dominant quadrupolar modes agree to better than $\approx 10^{-3}$. We expect our model to be useful to study intermediate-mass-ratio binary systems in current and future gravitational-wave detectors.

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arXiv2021

Learning orbital dynamics of binary black hole systems from gravitational wave measurements

We introduce a gravitational waveform inversion strategy that discovers mechanical models of binary black hole (BBH) systems. We show that only a single time series of (possibly noisy) waveform data is necessary to construct the equations of motion for a BBH system. Starting with a class of universal differential equations parameterized by feed-forward neural networks, our strategy involves the construction of a space of plausible mechanical models and a physics-informed constrained optimization within that space to minimize the waveform error. We apply our method to various BBH systems including extreme and comparable mass ratio systems in eccentric and non-eccentric orbits. We show the resulting differential equations apply to time durations longer than the training interval, and relativistic effects, such as perihelion precession, radiation reaction, and orbital plunge, are automatically accounted for. The methods outlined here provide a new, data-driven approach to studying the dynamics of binary black hole systems.

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arXiv2021

High-precision source characterization of intermediate mass-ratio black hole coalescences with gravitational waves: The importance of higher-order multipoles

Intermediate mass ratio inspiral (IMRI) binaries -- containing stellar-mass black holes coalescing into intermediate-mass black holes ($M>100M_{\odot}$) -- are a highly anticipated source of gravitational waves (GWs) for Advanced LIGO/Virgo. Their detection and source characterization would provide a unique probe of strong-field gravity and stellar evolution. Due to the asymmetric component masses and the large primary, these systems generically excite subdominant modes while reducing the importance of the dominant quadrupole mode. Including higher order harmonics can also result in a $10\%-25\%$ increase in signal-to-noise ratio for IMRIs, which may help to detect these systems. We show that by including subdominant GW modes into the analysis we can achieve a precise characterization of IMRI source properties. For example, we find that the source properties for IMRIs can be measured to within $2\%-15\%$ accuracy at a fiducial signal-to-noise ratio of 25 if subdominant modes are included. When subdominant modes are neglected, the accuracy degrades to $9\%-44\%$ and significant biases are seen in chirp mass, mass ratio, primary spin and luminosity distances. We further demonstrate that including subdominant modes in the waveform model can enable an informative measurement of both individual spin components and improve the source localization by a factor of $\sim$10. We discuss some important astrophysical implications of high-precision source characterization enabled by subdominant modes such as constraining the mass gap and probing formation channels.

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arXiv2021

Genetic-algorithm-optimized neural networks for gravitational wave classification

Gravitational-wave detection strategies are based on a signal analysis technique known as matched filtering. Despite the success of matched filtering, due to its computational cost, there has been recent interest in developing deep convolutional neural networks (CNNs) for signal detection. Designing these networks remains a challenge as most procedures adopt a trial and error strategy to set the hyperparameter values. We propose a new method for hyperparameter optimization based on genetic algorithms (GAs). We compare six different GA variants and explore different choices for the GA-optimized fitness score. We show that the GA can discover high-quality architectures when the initial hyperparameter seed values are far from a good solution as well as refining already good networks. For example, when starting from the architecture proposed by George and Huerta, the network optimized over the 20-dimensional hyperparameter space has 78% fewer trainable parameters while obtaining an 11% increase in accuracy for our test problem. Using genetic algorithm optimization to refine an existing network should be especially useful if the problem context (e.g. statistical properties of the noise, signal model, etc) changes and one needs to rebuild a network. In all of our experiments, we find the GA discovers significantly less complicated networks as compared to the seed network, suggesting it can be used to prune wasteful network structures. While we have restricted our attention to CNN classifiers, our GA hyperparameter optimization strategy can be applied within other machine learning settings.

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arXiv2021

Improved analysis of GW190412 with a precessing numerical relativity surrogate waveform model

The recent observation of GW190412, the first high-mass ratio binary black-hole (BBH) merger, by the LIGO-Virgo Collaboration (LVC) provides a unique opportunity to probe the impact of subdominant harmonics and precession effects encoded in a gravitational wave signal. We present refined estimates of source parameters for GW190412 using \texttt{NRSur7dq4}, a recently developed numerical relativity waveform surrogate model that includes all $\ell \leq 4$ spin-weighted spherical harmonic modes as well as the full physical effects of precession. We compare our results with two different variants of phenomenological precessing BBH waveform models, \texttt{IMRPhenomPv3HM} and \texttt{IMRPhenomXPHM}, as well as to the LVC results. Our results are broadly in agreement with \texttt{IMRPhenomXPHM} results and the reported LVC analysis compiled with the \texttt{SEOBNRv4PHM} waveform model, but in tension with \texttt{IMRPhenomPv3HM}. Using the \texttt{NRSur7dq4} model, we provide a tighter constraint on the mass-ratio ($0.26^{+0.08}_{-0.06}$) as compared to the LVC estimate of $0.28^{+0.13}_{-0.07}$ (both reported as median values withs 90\% credible intervals). We also constrain the binary to be more face-on, and find a broader posterior for the spin precession parameter. We further find that even though $\ell=4$ harmonic modes have negligible signal-to-noise ratio, omission of these modes will influence the estimated posterior distribution of several source parameters including chirp mass, effective inspiral spin, luminosity distance, and inclination. We also find that commonly used model approximations, such as neglecting the asymmetric modes (which are generically excited during precession), have negligible impact on parameter recovery for moderate SNR-events similar to GW190412.

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arXiv2021

Eccentric binary black hole surrogate models for the gravitational waveform and remnant properties: comparable mass, nonspinning case

We develop new strategies to build numerical relativity surrogate models for eccentric binary black hole systems, which are expected to play an increasingly important role in current and future gravitational-wave detectors. We introduce a new surrogate waveform model, \texttt{NRSur2dq1Ecc}, using 47 nonspinning, equal-mass waveforms with eccentricities up to $0.2$ when measured at a reference time of $5500M$ before merger. This is the first waveform model that is directly trained on eccentric numerical relativity simulations and does not require that the binary circularizes before merger. The model includes the $(2,2)$, $(3,2)$, and $(4,4)$ spin-weighted spherical harmonic modes. We also build a final black hole model, \texttt{NRSur2dq1EccRemnant}, which models the mass, and spin of the remnant black hole. We show that our waveform model can accurately predict numerical relativity waveforms with mismatches $\approx 10^{-3}$, while the remnant model can recover the final mass and dimensionless spin with absolute errors smaller than $\approx 5 \times 10^{-4}M$ and $\approx 2 \times10^{-3}$ respectively. We demonstrate that the waveform model can also recover subtle effects like mode-mixing in the ringdown signal without any special ad-hoc modeling steps. Finally, we show that despite being trained only on equal-mass binaries, \texttt{NRSur2dq1Ecc} can be reasonably extended up to mass ratio $q\approx3$ with mismatches $\simeq 10^{-2}$ for eccentricities smaller than $\sim 0.05$ as measured at a reference time of $2000M$ before merger. The methods developed here should prove useful in the building of future eccentric surrogate models over larger regions of the parameter space.

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arXiv2020

A GPU-accelerated mixed-precision WENO method for extremal black hole and gravitational wave physics computations

We develop and use a novel mixed-precision weighted essentially non-oscillatory (WENO) method for solving the Teukolsky equation, which arises when modeling perturbations of Kerr black holes. We show that WENO methods outperform higher-order finite-difference methods, standard in the discretization of the Teukolsky equation, due to the need to add dissipation for stability purposes in the latter. In particular, as the WENO scheme uses no additional dissipation it is well-suited for scenarios requiring long-time evolution such as the study of Price tails and gravitational wave emission from extreme mass ratio binaries. In the mixed-precision approach, the expensive computation of the WENO weights is performed in reduced floating-point precision that results in a significant speedup factor of 3.3. In addition, we use state-of-the-art Nvidia general-purpose graphics processing units and cluster parallelism to further accelerate the WENO computations. Our optimized WENO solver can be used to quickly generate accurate results of significance in the field of black hole and gravitational wave physics. We apply our solver to study the behavior of the Aretakis charge -- a conserved quantity, that if detected by a gravitational wave observatory like LIGO/Virgo would prove the existence of extremal black holes.

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