de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

An algorithm for detection of extreme mass ratio inspirals in LISA data

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons20655

Babak,  Stanislav
Astrophysical Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)

0902.4133
(Preprint), 2MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Babak, S., Gair, J. R., & Porter, E. K. (2009). An algorithm for detection of extreme mass ratio inspirals in LISA data. Classical and quantum gravity, 26: 135004. doi:10.1088/0264-9381/26/13/135004.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0012-BC1E-8
Zusammenfassung
The gravitational wave signal from a compact object spiralling toward a massive black hole (MBH) is thought to be one of the most difficult sources to detect in the LISA data stream. Due to the large parameter space of possible signals and many orbital cycles spent in the sensitivity band of LISA, it has been estimated previously that of the order of 10^{35} templates would be required for a fully coherent search with a template grid, which is computationally impossible. Here we describe an algorithm based on a constrained Metropolis-Hastings stochastic search which allows us to find and accurately estimate parameters of isolated EMRI signals buried in Gaussian instrumental noise. We illustrate the effectiveness of the algorithm with results from searches of the Mock LISA Data Challenge round 1B data sets.