Computer Science – Performance
Scientific paper
Jan 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21347710c&link_type=abstract
American Astronomical Society, AAS Meeting #213, #477.10; Bulletin of the American Astronomical Society, Vol. 41, p.444
Computer Science
Performance
Scientific paper
The low frequency gravitational waves that will be detected by the LISA observatory contain a wealth of information that can inform us about early structure formation, galaxy evolution and the near horizon geometry of black holes. The difficulty is that all the sources are "talking" at the same time. With tens of thousands of sources visible in the LISA band, we need to find a way to listen to multiple, simultaneous conversations. A series of Mock LISA Data Challenges have been conducted to help address this issue, and a variety of semi-stochastic search algorithms - part Markov Chain Monte Carlo and part Genetic - have shown great promise. The implementation and performance of these techniques will be reviewed.
Cornish Neil J.
Montana Gravitational Wave Astronomy Group
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