Rights statement: Copyright 2019 American Institute of Physics. The following article appeared in Physical Review D, 91, 2015 and may be found at https://doi.org/10.1103/PhysRevD.91.042003 This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library
AU - Veitch, J.
AU - Raymond, V.
AU - Farr, B.
AU - Farr, W.
AU - Graff, P.
AU - Vitale, S.
AU - Aylott, B.
AU - Blackburn, K.
AU - Christensen, N.
AU - Coughlin, M.
AU - Del Pozzo, W.
AU - Feroz, F.
AU - Gair, J.
AU - Haster, C.-J.
AU - Kalogera, V.
AU - Littenberg, T.
AU - Mandel, I.
AU - O'Shaughnessy, R.
AU - Pitkin, M.
AU - Rodriguez, C.
AU - Röver, C.
AU - Sidery, T.
AU - Smith, R.
AU - Van Der Sluys, M.
AU - Vecchio, A.
AU - Vousden, W.
AU - Wade, L.
N1 - Copyright 2019 American Institute of Physics. The following article appeared in Physical Review D, 91, 2015 and may be found at https://doi.org/10.1103/PhysRevD.91.042003 This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics.
PY - 2015/2/1
Y1 - 2015/2/1
N2 - 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, a neutron star–black hole binary and a binary black hole, where we show a cross comparison of results obtained using three independent sampling algorithms. These systems were analyzed with nonspinning, 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 analyzing 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 parameter space.
AB - 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, a neutron star–black hole binary and a binary black hole, where we show a cross comparison of results obtained using three independent sampling algorithms. These systems were analyzed with nonspinning, 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 analyzing 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 parameter space.
KW - Inference methods
KW - Gravitational waves: theory
KW - Gravitational radiation magnetic fields and other observations
U2 - 10.1103/PhysRevD.91.042003
DO - 10.1103/PhysRevD.91.042003
M3 - Journal article
VL - 91
JO - Physical Review D
JF - Physical Review D
SN - 1550-7998
IS - 4
M1 - 042003
ER -