Description
- Compact-Transportable Iodine Stabilized Laser Setup for LISA Mission Grounds Tests Operation
- Spectral separation of the cosmological SGWB for LISA in context of galactic and astrophysical background
- Non parametric representation for MBHB recovery from LISA data
- Neural density estimation for Galactic Binaries with LISA
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Benjamin Pointard (LNE-SYRTE)20/11/2023 10:00
The French activities for LISA (Laser Interferometer Space Antenna) mission include assembly, integration, validation and testing of the payload by a consortium of several partners led by CNES.
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SYRTE has developed for several years a laser activity for the different tests and interferometric measures realized by the consortium. A partnership with eXail led to a major technological step in the... -
Guillaume Boileau (Laboratoire Lagrange UMR 7293, Observatoire de la Côte d'Azur)20/11/2023 10:20
In pursuit of observing a stochastic gravitational wave background (SGWB) with LISA, it is crucial to investigate the spectral separability of cosmological, astrophysical backgrounds, and galactic foreground in order to make accurate estimations.
Our objective is to determine the observability of a cosmological background, considering the predicted astrophysical background and galactic...
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Elie Leroy (DRF-IRFU)20/11/2023 10:40
In the context of the LISA mission, the fast detection and recovery of MBHB (Massive Black Hole Binaries) from the LISA data is key for both the low-latency and global analysis tasks. This is especially paramount when the data are gapped or contaminated with spuritous transients such as glitches. For that purpose, we introduce an hybrid non-parametric representation of MBHBs that combines an...
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Natalia Korsakova (APC)20/11/2023 11:00
The future space gravitational wave detector LISA (Laser Interferometer Space Antenna) will have hundreds of thousands of Galactic Binaries (GBs) constantly present in the data stream. One of the challenging tasks from the data analysis point of view will be to estimate parameters of these GBs while disentangling them from each other and from other signals present in the data. This problem is...
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