Combining effective-one-body accuracy and reduced-order-quadrature speed for binary neutron star merger parameter estimation with machine learning-Reference-Cited by-同舟云学术

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Combining effective-one-body accuracy and reduced-order-quadrature speed for binary neutron star merger parameter estimation with machine learning

Published:2023-04-25 Issue:8 Volume:107 Page:
ISSN:2470-0010
Container-title:Physical Review D
language:en
Short-container-title:Phys. Rev. D

Author:

Tissino Jacopo,Carullo Gregorio,Breschi Matteo,Gamba Rossella,Schmidt Stefano^ORCID,Bernuzzi Sebastiano

Funder

H2020 European Research Council

European Research Council

Deutsche Forschungsgemeinschaft

Horizon 2020 Framework Programme

HORIZON EUROPE Marie Sklodowska-Curie Actions

Villum Fonden

Danmarks Grundforskningsfond

National Science Foundation

Centre National de la Recherche Scientifique

Instituto Nazionale di Fisica Nucleare

Research Training Group

Della Riccia Foundation

Dutch Nikhef

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevD.107.084037/fulltext

Reference90 articles.

1. Parameter estimation for compact binary coalescence signals with the first generation gravitational-wave detector network

2. Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library

3. Comparison of post-Newtonian templates for compact binary inspiral signals in gravitational-wave detectors

4. Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries

5. Bayesian Inference for Gravitational Waves from Binary Neutron Star Mergers in Third Generation Observatories

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