Computer Science – Performance
Scientific paper
Mar 2012
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012aps..apr.d8002n&link_type=abstract
American Physical Society, APS April Meeting 2012, March 31-Apr 3, 2012, abstract #D8.002
Computer Science
Performance
Scientific paper
Within this decade, gravitational waves will become new astrophysical messengers with which we can learn about our universe. Gravitational wave emission from the coalescence of massive bodies is projected to be a promising source for the next generation of gravitational wave detectors: advanced LIGO and advanced Virgo. We describe a method for the detection of binary black hole coalescences using a chirplet template bank, Chirplet Omega. By appropriately clustering the linearly variant frequency sin-Gaussian pixels the algorithm uses to decompose the data, the signal to noise ratio SNR of events extended in time can be significantly increased. We present such a clustering method and discuss its impacts on performance and detectability of binary black hole coalescences in ground based gravitational wave interferometers.
Cadonati Laura
Chassande-Mottin Eric
Mohapatra Satyanarayan R. P.
Nemtzow Zachary
No associations
LandOfFree
Chirplet Clustering Algorithm for Black Hole Coalescence Signatures in Gravitational Wave Detectors does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Chirplet Clustering Algorithm for Black Hole Coalescence Signatures in Gravitational Wave Detectors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Chirplet Clustering Algorithm for Black Hole Coalescence Signatures in Gravitational Wave Detectors will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1365645