Initial Data and Eccentricity Reduction Toolkit for Binary Black Hole Numerical Relativity Waveforms
Sarah Habib, Antoni Ramos-Buades, E. A. Huerta, Sascha Husa, Roland, Haas, Zachariah Etienne

TL;DR
This paper introduces an open source toolkit for generating high-quality initial data and reducing eccentricity in binary black hole numerical relativity waveforms, facilitating broader community access and use.
Contribution
It provides the first open source, comprehensive set of tools and tutorials for initial data creation and eccentricity reduction in binary black hole simulations.
Findings
Open source parameter files for spinning black hole binaries
Python tools for initial data generation and eccentricity reduction
Integration with Einstein Toolkit for community use
Abstract
The production of numerical relativity waveforms that describe quasicircular binary black hole mergers requires high-quality initial data, and an algorithm to iteratively reduce residual eccentricity. To date, these tools remain closed source, or in commercial software that prevents their use in high performance computing platforms. To address these limitations, and to ensure that the broader numerical relativity community has access to these tools, herein we provide all the required elements to produce high-quality numerical relativity simulations in supercomputer platforms, namely: open source parameter files to numerical simulate spinning black hole binaries with asymmetric mass-ratios; open source tools to produce high-quality initial data for numerical relativity simulations of spinning black hole binaries on quasi-circular orbits; open source …
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