Fast and accurate waveform models are fundamentally important to modern gravitational wave astrophysics, enabling the study of merging compact objects like black holes and neutron stars. However, generating high-fidelity gravitational waveforms through numerical relativity simulations is computationally intensive, often requiring days to months of computation time on supercomputers. Surrogate models provide a practical solution to dramatically accelerate waveform evaluations (typically tens of milliseconds per evaluation) while retaining the accuracy of computationally expensive simulations. The GWSurrogate Python package provides easy access to these gravitational wave surrogate models through a user-friendly interface. Currently, the package supports 16 surrogate models, each varying in duration, included physical effects (e.g., nonlinear memory, tidal forces, harmonic modes, eccentricity, mass ratio range, precession effects), and underlying solution methods (e.g., Effective One Body, numerical relativity, black hole perturbation theory). GWSurrogate models follow the waveform model conventions used by the LIGO-Virgo-Kagra collaboration, making the package immediately suitable for both theoretical studies and practical gravitational wave data analysis. By enabling rapid and precise waveform generation, GWSurrogate serves as a production-level tool for diverse applications, including parameter estimation, template bank generation, and tests of general relativity.

Advanced LIGO and Advanced Virgo are actively monitoring the sky and collecting gravitational-wave strain data with sufficient sensitivity to detect signals routinely. In this paper we describe the data recorded by these instruments during their first and second observing runs. The main data products are the gravitational-wave strain arrays, released as time series sampled at 16384 Hz. The datasets that include this strain measurement can be freely accessed through the Gravitational Wave Open Science Center at http://gw-openscience.org, together with data-quality information essential for the analysis of LIGO and Virgo data, documentation, tutorials, and supporting software.

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 l = 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 similar to 10(-4). The simulations provide remnant masses and spins with uncertainties of 0.03% and 0.1% (90th percentile), about an order of magnitude better than analytical models for remnant properties. The full catalog is publicly available at www.blackholes.org/waveforms.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

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, \RemnantModel, 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 $q\leq4$ and spin magnitudes $\chi_1,\chi_2 \leq 0.8$, with generic spin directions. The waveform model, NRSur7dq4, which begins about 20 orbits before merger, includes all $\ell \leq 4$ spin-weighted spherical harmonic modes, as well as the precession frame dynamics and spin evolution of the black holes. The final black hole model, \RemnantModel, 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 $q=6$.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.

Simulation of a black-hole binary system evolved by the SpEC code.