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  Towards the routine use of subdominant harmonics in gravitational-wave inference: re-analysis of GW190412 with generation X waveform models

Colleoni, M., Mateu-Lucena, M., Estellés, H., García-Quirós, C., Keitel, D., Pratten, G., et al. (in preparation). Towards the routine use of subdominant harmonics in gravitational-wave inference: re-analysis of GW190412 with generation X waveform models.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0007-5FF3-D Version Permalink: http://hdl.handle.net/21.11116/0000-0007-5FFF-1
Genre: Paper

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2010.05830.pdf (Preprint), 5MB
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 Creators:
Colleoni, Marta, Author
Mateu-Lucena, Maite, Author
Estellés, Héctor, Author
García-Quirós, Cecilio, Author
Keitel, David, Author
Pratten, Geraint, Author
Ramos Buades, Antoni1, Author              
Husa, Sascha, Author
Affiliations:
1Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society, ou_1933290              

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Free keywords: General Relativity and Quantum Cosmology, gr-qc, Astrophysics, High Energy Astrophysical Phenomena, astro-ph.HE
 Abstract: We re-analyse the gravitational-wave event GW190412 with state-of-the-art phenomenological waveform models. This event, which has been associated with a black hole merger, is interesting due to the significant contribution from subdominant harmonics. We use both frequency-domain and time-domain waveform models. The PhenomX waveform models constitute the fourth generation of frequency-domain phenomenological waveforms for black hole binary coalescence; they have more recently been complemented by the time-domain PhenomT models, which open up new strategies to model precession and eccentricity, and to perform tests of general relativity with the phenomenological waveforms approach. Both PhenomX and PhenomT have been constructed with similar techniques and accuracy goals, and due to their computational efficiency this "generation X" model family allows the routine use of subdominant spherical harmonics in Bayesian inference. We show the good agreement between these and other state-of-the-art waveform models for GW190412, and discuss the improvements over the previous generation of phenomenological waveform models. We also discuss practical aspects of Bayesian inference such as run convergence, variations of sampling parameters, and computational cost.

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 Dates: 2020-10-122020-10-13
 Publication Status: Not specified
 Pages: 25 pages, 18 figures. Data release: https://doi.org/10.5281/zenodo.4079188
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: arXiv: 2010.05830
 Degree: -

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