Sparse data inpainting for the recovery of Galactic-binary gravitational wave signals from gapped data
Autor: | Hervé Moutarde, Jérôme Bobin, Aurore Blelly |
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Přispěvatelé: | Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay |
Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Gravitational-wave observatory
Inpainting FOS: Physical sciences Binary number General Relativity and Quantum Cosmology (gr-qc) 01 natural sciences General Relativity and Quantum Cosmology 0103 physical sciences [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det] Instrumentation and Methods for Astrophysics (astro-ph.IM) 010303 astronomy & astrophysics Astrophysics::Galaxy Astrophysics Sparse matrix High Energy Astrophysical Phenomena (astro-ph.HE) Physics Signal processing methods: statistical 010308 nuclear & particles physics Gravitational wave Noise (signal processing) Astronomy and Astrophysics Sparse approximation methods: data analysis gravitational waves Space and Planetary Science [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc] [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph] Astrophysics - High Energy Astrophysical Phenomena Astrophysics - Instrumentation and Methods for Astrophysics Algorithm |
Zdroj: | Mon.Not.Roy.Astron.Soc. Mon.Not.Roy.Astron.Soc., 2021, 509 (4), pp.5902-5917. ⟨10.1093/mnras/stab3314⟩ Monthly Notices of the Royal Astronomical Society Monthly Notices of the Royal Astronomical Society, 2021, 509 (4), pp.5902-5917. ⟨10.1093/mnras/stab3314⟩ |
ISSN: | 0035-8711 1365-2966 |
DOI: | 10.1093/mnras/stab3314⟩ |
Popis: | The forthcoming space-based gravitational wave observatory LISA will open a new window for the measurement of Galactic binaries, which will deliver unprecedented information about these systems. However, the detection of Galactic binary gravitational wave signals is challenged by the presence of gaps in the data. Whether being planned or not, gapped data reduce our ability to detect faint signals and increase the risk of misdetection. Inspired by advances in signal processing, we introduce a non-parametric inpainting algorithm based on the sparse representation of the Galactic binary signal in the Fourier domain. In contrast to traditional inpainting approaches, noise statistics are known theoretically on ungapped measurements only. This calls for the joint recovery of both the ungapped noise and the Galactic binary signal. We thoroughly show that sparse inpainting yields an accurate estimation of the gravitational imprint of the Galactic binaries. Additionally, we highlight that the proposed algorithm produces a statistically consistent ungapped noise estimate. We further evaluate the performances of the proposed inpainting methods to recover the gravitational wave signal on a simple example involving verification Galactic binaries recently proposed in LISA data challenges. |
Databáze: | OpenAIRE |
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