Accurate models of gravitational waves from merging black holes are necessary for detectors to observe as many events as possible while extracting the maximum science. Near the time of merger, the gravitational waves from merging black holes can be computed only using numerical relativity. In this paper, we present a major update of the Simulating eXtreme Spacetimes (SXS) Collaboration catalog of numerical simulations for merging black holes. The catalog contains 2018 distinct configurations (a factor of 11 increase compared to the 2013 SXS catalog), including 1426 spin-precessing configurations, with mass ratios between 1 and 10, and spin magnitudes up to 0.998. The median length of a waveform in the catalog is 39 cycles of the dominant = m = 2 gravitational-wave mode, with the shortest waveform containing 7.0 cycles and the longest 351.3 cycles. We discuss improvements such as correcting for moving centers of mass and extended coverage of the parameter space. We also present a thorough analysis of numerical errors, finding typical truncation errors corresponding to a waveform mismatch of ∼ 10 −4 . The simulations provide remnant masses and spins with uncertainties of 0.03% and 0.1% (90 th percentile), about an order of magnitude better than analytical models for remnant properties. The full catalog is publicly available at https://www.black-holes.org/waveforms . black holes and of the surrounding spacetime [31,32]. Simulations have also been used for visualizations of curved spacetime [33][34][35][36][37][38][39][40], investigations of spin quantities [41], and the relaxation of spacetime to the Kerr solution following merger [42][43][44]. The motion of the black hole horizons and horizon curvature quantities have been used to explore eccentric dynamics [45][46][47][48], spin precession [49][50][51][52], and the first law of binary black hole mechanics [53][54][55][56][57]. These in turn have been compared to analytic post-Newtonian and self-force approximations (see also [58][59][60]), mapping out the bounds of validity of these approximations.A key application of BBH simulations is the accurate modeling of gravitational waves emitted by these systems during their late inspiral, merger, and final ringdown. Waveforms extracted from BBH simulations are essential for analyzing observed gravitational-wave signals from black hole binaries. Indeed, all BBH observations by LIGO and Virgo were analyzed using waveform families that rely on numerical relativity for their construction, most notably effective-one-body waveform models [61-65] and phenomenological waveform models [66][67][68]. Numerical simulations are also central in validating such waveform models [69][70][71][72][73][74][75][76], and were used to validate GW searches [77][78][79]. Waveforms from numerical relativity are also used directly in parameter estimation [80,81], to construct template banks [82], and to construct waveform families without intermediate analytical models, using methods such as reduced order modeling [83][84][85][86]. Today's simula...

Only numerical relativity simulations can capture the full complexities of binary black hole mergers. These simulations, however, are prohibitively expensive for direct data analysis applications such as parameter estimation. We present two new fast and accurate surrogate models for the outputs of these simulations: the first model, NRSur7dq4, predicts the gravitational waveform and the second model, NRSur7dq4Remnant, predicts the properties of the remnant black hole. These models extend previous 7-dimensional, non-eccentric precessing models to higher mass ratios, and have been trained against 1528 simulations with mass ratios q ≤ 4 and spin magnitudes χ1, χ2 ≤ 0.8, with generic spin directions. The waveform model, NRSur7dq4, which begins about 20 orbits before merger, includes all ≤ 4 spin-weighted spherical harmonic modes, as well as the precession frame dynamics and spin evolution of the black holes. The final black hole model, NRSur7dq4Remnant, models the mass, spin, and recoil kick velocity of the remnant black hole. In their training parameter range, both models are shown to be more accurate than existing models by at least an order of magnitude, with errors comparable to the estimated errors in the numerical relativity simulations. We also show that the surrogate models work well even when extrapolated outside their training parameter space range, up to mass ratios q = 6.

We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced order model in both parameter and physical dimensions that can be used as a surrogate for the true or fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant that is built for the fiducial waveform family. Third, a fit in the parameter dimension is performed for the waveform's value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order OðmL þ mc fit Þ online operations, where c fit denotes the fitting function operation count and, typically, m ≪ L. The result is a compact, computationally efficient, and accurate surrogate model that retains the original physics of the fiducial waveform family while also being fast to evaluate. We generate accurate surrogate models for effective-one-body waveforms of nonspinning binary black hole coalescences with durations as long as 10 5 M, mass ratios from 1 to 10, and for multiple spherical harmonic modes. We find that these surrogates are more than 3 orders of magnitude faster to evaluate as compared to the cost of generating effective-one-body waveforms in standard ways. Surrogate model building for other waveform families and models follows the same steps and has the same low computational online scaling cost. For expensive numerical simulations of binary black hole coalescences, we thus anticipate extremely large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy.