Astrophysical model selection in gravitational wave astronomy

被引:49
作者
Adams, Matthew R. [1 ]
Cornish, Neil J. [1 ]
Littenberg, Tyson B. [2 ,3 ]
机构
[1] Montana State Univ, Dept Phys, Bozeman, MT 59717 USA
[2] Univ Maryland, Dept Phys, Maryland Ctr Fundamental Phys, College Pk, MD 20742 USA
[3] NASA Goddard Spaceflight Ctr, Gravitat Astrophys Lab, Greenbelt, MD 20771 USA
来源
PHYSICAL REVIEW D | 2012年 / 86卷 / 12期
关键词
DOUBLE WHITE-DWARFS; POPULATION SYNTHESIS; BINARIES; SYSTEMS; SIGNAL;
D O I
10.1103/PhysRevD.86.124032
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve similar to 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%. DOI: 10.1103/PhysRevD.86.124032
引用
收藏
页数:10
相关论文
共 51 条
[1]   Discriminating between a stochastic gravitational wave background and instrument noise [J].
Adams, Matthew R. ;
Cornish, Neil J. .
PHYSICAL REVIEW D, 2010, 82 (02)
[2]   Low-frequency gravitational-wave science with eLISA/NGO [J].
Amaro-Seoane, Pau ;
Aoudia, Sofiane ;
Babak, Stanislav ;
Binetruy, Pierre ;
Berti, Emanuele ;
Bohe, Alejandro ;
Caprini, Chiara ;
Colpi, Monica ;
Cornish, Neil J. ;
Danzmann, Karsten ;
Dufaux, Jean-Francois ;
Gair, Jonathan ;
Jennrich, Oliver ;
Jetzer, Philippe ;
Klein, Antoine ;
Lang, Ryan N. ;
Lobo, Alberto ;
Littenberg, Tyson ;
McWilliams, Sean T. ;
Nelemans, Gijs ;
Petiteau, Antoine ;
Porter, Edward K. ;
Schutz, Bernard F. ;
Sesana, Alberto ;
Stebbins, Robin ;
Sumner, Tim ;
Vallisneri, Michele ;
Vitale, Stefano ;
Volonteri, Marta ;
Ward, Henry .
CLASSICAL AND QUANTUM GRAVITY, 2012, 29 (12)
[3]   An overview of the second round of the mock LISA data challenges [J].
Arnaud, K. A. ;
Babak, S. ;
Baker, J. G. ;
Benacquista, M. J. ;
Cornish, N. J. ;
Cutler, C. ;
Finn, L. S. ;
Larson, S. L. ;
Littenberg, T. ;
Porter, E. K. ;
Vallisneri, M. ;
Vecchio, A. ;
Vinet, J-Y .
CLASSICAL AND QUANTUM GRAVITY, 2007, 24 (19) :S551-S564
[4]   The Mock LISA Data Challenges: from challenge 3 to challenge 4 [J].
Babak, Stanislav ;
Baker, John G. ;
Benacquista, Matthew J. ;
Cornish, Neil J. ;
Larson, Shane L. ;
Mandel, Ilya ;
McWilliams, Sean T. ;
Petiteau, Antoine ;
Porter, Edward K. ;
Robinson, Emma L. ;
Vallisneri, Michele ;
Vecchio, Alberto ;
Adams, Matt ;
Arnaud, Keith A. ;
Blaut, Arkadiusz ;
Bridges, Michael ;
Cohen, Michael ;
Cutler, Curt ;
Feroz, Farhan ;
Gair, Jonathan R. ;
Graff, Philip ;
Hobson, Mike ;
Key, Joey Shapiro ;
Krolak, Andrzej ;
Lasenby, Anthony ;
Prix, Reinhard ;
Shang, Yu ;
Trias, Miquel ;
Veitch, John ;
Whelan, John T. .
CLASSICAL AND QUANTUM GRAVITY, 2010, 27 (08)
[5]   LISA capture sources: Approximate waveforms, signal-to-noise ratios, and parameter estimation accuracy [J].
Barack, L ;
Cutler, C .
PHYSICAL REVIEW D, 2004, 69 (08) :24
[6]   Mock LISA data challenge for the Galactic white dwarf binaries [J].
Blaut, Arkadiusz ;
Babak, Stanislav ;
Krolak, Andrzej .
PHYSICAL REVIEW D, 2010, 81 (06)
[7]  
Carlin BP, 2000, C&H TEXT STAT SCI
[8]   AN INTRODUCTION TO EMPIRICAL BAYES DATA-ANALYSIS [J].
CASELLA, G .
AMERICAN STATISTICIAN, 1985, 39 (02) :83-87
[9]   Tests of Bayesian model selection techniques for gravitational wave astronomy [J].
Cornish, Neil J. ;
Littenberg, Tyson B. .
PHYSICAL REVIEW D, 2007, 76 (08)
[10]   LISA data analysis: Source identification and subtraction [J].
Cornish, NJ ;
Larson, SL .
PHYSICAL REVIEW D, 2003, 67 (10)