$\text{GWFAST}$: a Fisher information matrix Python code for third-generation gravitational-wave detectors

Abstract

We introduce $\text{GWFAST}$, a Fisher information matrix $\text{Python}$ code that allows easy and efficient estimation of signal-to-noise ratios and parameter measurement errors for large catalogs of resolved sources observed by networks of gravitational-wave detectors. In particular, $\text{GWFAST}$ includes the effects of the Earth's motion during the evolution of the signal, supports parallel computation, and relies on automatic differentiation rather than on finite differences techniques, which allows the computation of derivatives with accuracy close to machine precision. We also release the library $\text{WF4Py}$ implementing state-of-the-art gravitational-wave waveforms in $\text{Python}$. In this paper we provide a documentation of $\text{GWFAST}$ and $\text{WF4Py}$ with practical examples and tests of performance and reliability. In a companion paper we present forecasts for the detection capabilities of the second and third generation of ground-based gravitational-wave detectors, obtained with $\text{GWFAST}$.

18 pages, 6 figures, $\text{GWFAST}$ available at $\text{href}$, $\text{WF4Py}$ available at $\text{href}$. v3 matches the version accepted for publication in ApJS. Title changed in journal

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Cited by in corpus (1)

• Gravitational-wave cosmology with dark sirens: state of the art and perspectives for 3G detectors