Title :
Classification of gravitational waves from supernova core collapses using affinity propagation
Author :
Hayama, Kazuhiro
Author_Institution :
Univ. of Texas at Brownsville, Brownsville, TX
Abstract :
Numerical relativistic simulations of a supernova core collapse indicate that a gravitational waveform from the supernova core collapse has several types. The gravitational waveform is strongly related to the stellar structure such as a rotation of the supernova core and an equation of state. Knowing the distribution of the types of the gravitational waveforms is an probe to elucidate the story of evolution of the supernova. In this paper, we propose a clustering method to determine the distribution. We performed Monte Carlo simulations of classification of simulated gravitational waves from supernovae using the affinity propagation and showed the efficiency of the method. We found that the classification by the affinity propagation worked well if a supernova core collapse occurs in our Galaxy.
Keywords :
Monte Carlo methods; gravitational waves; pattern classification; pattern clustering; stellar structure; supernovae; Monte Carlo simulations; affinity propagation; clustering method; galaxy; gravitational waveform; numerical relativistic simulations; simulated gravitational waves classification; stellar structure; supernova core collapses; supernova evolution; supernovae; Clustering algorithms; Clustering methods; Detectors; Equations; Kinetic energy; Machine learning; Numerical simulation; Optimization methods; Physics; Probes;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697695