TL;DR
This paper introduces GWJulia, a Julia-based tool for fast Fisher Information Matrix analysis of gravitational-wave signals, aiding in detector layout optimization and parameter estimation for future Einstein Telescope configurations.
Contribution
The paper presents GWJulia, an open-source, high-accuracy Julia code for FIM analysis of GW signals, specifically tailored for Einstein Telescope design comparisons.
Findings
Comparison of ET configurations shows differences in parameter estimation accuracy.
GWJulia enables efficient analysis of GW detection prospects and parameter correlations.
The tool supports guiding posterior sampling with Hamiltonian Monte Carlo.
Abstract
Future gravitational-wave (GW) detectors are expected to detect tens of thousands of compact binary coalescences (CBC) per year, depending also on the final detectors layout. For this reason, it is essential to have a fast, reliable tool for forecasting how different detector layouts will affect parameter estimation for these events. The Fisher Information Matrix (FIM) is a common tool for tackling this problem. In this paper, we present a new open source code GWJulia to perform FIM analysis of CBC parameters, i.e., stellar black-hole binaries (BBH), neutron star binaries (BNS), and neutron star-black hole binaries (NSBH). The code is purely written in Julia, making it fast while maintaining a high level of accuracy. We consider a set of case studies to compare different Einstein Telescope (ET) designs. We compare a 10km triangular configuration with two 15km L-shaped detectors with…
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