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タイトルParameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference
本文(外部サイト)http://hdl.handle.net/2060/20150007912
著者(英)Farr, W.; Graff, P.; Raymond, V.; Blackburn, K.; Christensen, N.; Vitale, S.; Coughlin, M.; Aylott, B.; Farr, B.; Veitch, J.
著者所属(英)NASA Goddard Space Flight Center
発行日2015-02-17
言語eng
内容記述The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.
NASA分類Computer Programming and Software; Statistics and Probability; Astrophysics
レポートNOGSFC-E-DAA-TN22707
権利Copyright, Distribution under U.S. Government purpose rights


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