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[ascl:2309.016] PEREGRINE: Gravitational wave parameter inference with neural ration estimation

PEREGRINE performs full parameter estimation on gravitational wave signals. Using an internal Truncated Marginal Neural Ratio Estimation (TMNRE) algorithm and building upon the swyft (ascl:2302.016) code to efficiently access marginal posteriors, PEREGRINE conducts a sequential simulation-based inference approach to support the analysis of both transient and continuous gravitational wave sources. The code can fully reconstruct the posterior distributions for all parameters of spinning, precessing compact binary mergers using waveform approximants.

Code site:
https://github.com/PEREGRINE-GW/peregrine
Described in:
https://ui.adsabs.harvard.edu/abs/2023PhRvD.108d2004B
Bibcode:
2023ascl.soft09016B

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ascl:2309.016
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