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Institut d'Astrophysique et
de Géophysique (Bât. B5c)
Quartier Agora
Allée du 6 août, 19C
B-4000 Liège 1 (Sart-Tilman)
Belgique
Tel.: 04.366.9779
Fax: 04.366.9729
de Géophysique (Bât. B5c)
Quartier Agora
Allée du 6 août, 19C
B-4000 Liège 1 (Sart-Tilman)
Belgique
Tel.: 04.366.9779
Fax: 04.366.9729
Séminaires : Documents
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1er séminaire : Jeudi 21 janvier, 16h00
Stochastic GWSearch for a Stochastic Gravitational Waves Background using a Network of Detectors
Anirban Ain (INFN, Pisa)
The direct detection of Gravitational Waves (GW) by LIGO and Virgo is one of the most significant discoveries of modern times. The network of operational GW detectors is expected to observe a stochastic gravitational waves background (SGWB) in the near future. This all-sky source is made up of unresolved astrophysical sources and remnant GW from cosmological phenomena. Detection of the SGWB can be challenging because the signal is much smaller than the detector noise and being a stochastic signal there is no optimized filter to match-filter the data. Instead, an aperture synthesis technique is used to search for SGWB where data from different detectors are correlated to find signals and long stretches of data is added to build up significance. I have been working on the improvement of SGWB search pipelines. In recent years we implemented data folding and some new techniques to make the pipeline a few thousand times faster. I will be discussing SGWB mapping techniques and how they are optimized.
Anirban Ain (INFN, Pisa)
The direct detection of Gravitational Waves (GW) by LIGO and Virgo is one of the most significant discoveries of modern times. The network of operational GW detectors is expected to observe a stochastic gravitational waves background (SGWB) in the near future. This all-sky source is made up of unresolved astrophysical sources and remnant GW from cosmological phenomena. Detection of the SGWB can be challenging because the signal is much smaller than the detector noise and being a stochastic signal there is no optimized filter to match-filter the data. Instead, an aperture synthesis technique is used to search for SGWB where data from different detectors are correlated to find signals and long stretches of data is added to build up significance. I have been working on the improvement of SGWB search pipelines. In recent years we implemented data folding and some new techniques to make the pipeline a few thousand times faster. I will be discussing SGWB mapping techniques and how they are optimized.
