Constraining the neutron star equation of state with gravitational wave signals from coalescing binary neutron stars

被引:165
作者
Agathos, M. [1 ]
Meidam, J. [1 ]
Del Pozzo, W. [2 ]
Li, T. G. F. [1 ,3 ]
Tompitak, M. [4 ]
Veitch, J. [2 ]
Vitale, S. [5 ]
Van Den Broeck, C. [1 ]
机构
[1] Nikhef Natl Inst Subat Phys, NL-1098 XG Amsterdam, Netherlands
[2] Univ Birmingham, Sch Phys & Astron, Birmingham B15 2TT, W Midlands, England
[3] CALTECH, LIGO Lab, Pasadena, CA 91125 USA
[4] Leiden Univ, Leiden Inst Phys, NL-2333 CA Leiden, Netherlands
[5] MIT, LIGO Lab, Cambridge, MA 02139 USA
来源
PHYSICAL REVIEW D | 2015年 / 92卷 / 02期
基金
美国国家科学基金会; 英国科学技术设施理事会;
关键词
D O I
10.1103/PhysRevD.92.023012
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Recently exploratory studies were performed on the possibility of constraining the neutron star equation of state (EOS) using signals from coalescing binary neutron stars, or neutron star-black hole systems, as they will be seen in upcoming advanced gravitational wave detectors such as Advanced LIGO and Advanced Virgo. In particular, it was estimated to what extent the combined information from multiple detections would enable one to distinguish between different equations of state through hypothesis ranking or parameter estimation. Under the assumption of zero neutron star spins both in signals and in template waveforms and considering tidal effects to 1 post-Newtonian (1PN) order, it was found that O(20) sources would suffice to distinguish between a stiff, moderate, and soft equation of state. Here we revisit these results, this time including neutron star tidal effects to the highest order currently known, termination of gravitational waveforms at the contact frequency, neutron star spins, and the resulting quadrupole-monopole interaction. We also take the masses of neutron stars in simulated sources to be distributed according to a relatively strongly peaked Gaussian, as hinted at by observations, but without assuming that the data analyst will necessarily have accurate knowledge of this distribution for use as a mass prior. We find that especially the effect of the latter is dramatic, necessitating many more detections to distinguish between different EOSs and causing systematic biases in parameter estimation, on top of biases due to imperfect understanding of the signal model pointed out in earlier work. This would get mitigated if reliable prior information about the mass distribution could be folded into the analyses.
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页数:17
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