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Parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library

J. VeitchNikhef, Science Park 105, Amsterdam 1098XG, The NetherlandsV. RaymondLIGO, California Institute of Technology, Pasadena, California 91125, USAB. FarrCenter for Interdisciplinary Exploration and Research in Astrophysics (CIERA) and Department of Physics and Astronomy, 2145 Sheridan Road, Evanston, Illinois 60208, USAWill M. FarrSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomP. B. GraffNASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, Maryland 20771, USAS. VitaleMassachusetts Institute of Technology, 185 Albany Street, Cambridge, Massachusetts 02138, USAB. E. AylottSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomK. BlackburnLIGO, California Institute of Technology, Pasadena, California 91125, USAN. ChristensenPhysics and Astronomy, Carleton College, Northfield, Minnesota 55057, USAM. W. CoughlinDepartment of Physics, Harvard University, Cambridge, Massachusetts 02138, USAW. Del PozzoSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomF. FerozAstrophysics Group, Cavendish Laboratory, J.J. Thomson Avenue, Cambridge CB3 0HE, United KingdomJ. GairInstitute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, United KingdomC.‐J. HasterSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomV. KalogeraT. B. LittenbergIlya MandelSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomR. O’ShaughnessyRochester Institute of Technology, Rochester, New York 14623, USAM. PitkinSUPA, School of Physics and Astronomy, University of Glasgow, University Avenue, Glasgow G12 8QQ, United KingdomCarl L. RodriguezChristian RöverDepartment of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, 37073 Göttingen, GermanyT. L. SiderySchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomR. J. E. SmithLIGO, California Institute of Technology, Pasadena, California 91125, USAMarc van der SluysDepartment of Astrophysics/IMAPP, Radboud University Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The NetherlandsA. VecchioSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomW. D. VousdenSchool of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomL. E. WadeUniversity of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53201, USA

2015en

ABI

Annotatsiya

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.

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Identifikatorlar

DOI: 10.1103/physrevd.91.042003

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