Documents de présentation
We present GPE, a GPU-accelerated parameter estimation package for gravitational waves from compact binary coalescence sources. This stand-alone program is adapted from the nested sampling flavor of LALInference. Two main parallelization methods are implemented: (1) the frequency-domain waveform and likelihood calculations, (2) and the prior sampling portion in the nested sampling algorithm....
A major activity of the LIGO-Virgo-KAGRA collaboration is to build algorithms able to infer from the detected gravitational wave signals the posterior distributions of the parameters defining their sources: angles in the sky, distance from us, masses etc. Current algorithms like MCMC and Nested Sampling have already demonstrated with success their ability to do so during the first three runs...
Current gravitational-wave data analysis of merging binary black holes accounts for two precessing spins, allowing inference of the six spin degrees of freedom. Nonetheless, it is convenient to use effective parameters to interpret detections; the effective aligned spin
With LISA mission, the detection of galactic binaries as sources of gravitational waves promises an unprecedented wealth of information about these systems, but also raises several challenges in signal processing. In particular, the variety of sources and the presence of both planned and unplanned gaps call for the development of robust methods. We describe here an original non-parametric...
LISA is a future space-based gravitational wave detector that will a new window into the gravitational universe in the mHz range. Among LISA targets, coalescences of massive black hole binaries (MBHB) will be detected with unprecedented signal-to-noise ratios, and might enable multimessenger observations with instruments such as Athena, LSST and SKA. Modelling LISA's ability to locate these...
Continuous gravitational waves (CWs) from asymmetric spinning neutron stars are among the most interesting, although still undetected, targets of the Advanced LIGO-Virgo detectors. The search for this class of signals is difficult due to their expected weakness, and can be very computationally expensive when the source parameters are not known.
The stochastic group uses fast and consolidated...
