The eccentric behavior of inspiralling compact binaries
The eccentric behavior of inspiralling compact binaries
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DOI：
10.1088/1361-6382/aaf2a9
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发表时间：
2018-10
影响因子：
3.5
通讯作者：
N. Loutrel;Samuel Liebersbach;N. Yunes;N. Cornish
中科院分区：
文献类型：
--
作者：
N. Loutrel;Samuel Liebersbach;N. Yunes;N. Cornish
即使没有规范不变的偏心率定义，它也会对观测到的这类系统的引力波信号产生重要影响，在轨道周期的所有可能的谐波中产生能量。我们在这里阐明了用于描述双星系统轨道动力学的不同偏心率参数之间在不同近似下的可能差异，特别是后牛顿近似、自力近似和数值相对论。为此，我们强调了通常使用的在辐射反应下演化双星系统的轨道平均方法与后牛顿理论中解决两体问题的更直接的技术之间的差异。我们从数值和解析两个方面证明了轨道平均法在末期破裂，未能捕捉到开普勒式偏心率参数的长期增长，并产生了相对于两体运动方程直接积分的轨道退相。我们发现，长期增长和退相会影响观测到的引力波信号，这可能会影响我们如何准确地恢复信噪比系统的参数。我们进一步发展了一个频域后绝热波形模型来捕捉这些影响，并通过Fisher信息矩阵分析研究了使用该模型估计参数的精度。
Even if there is no gauge invariant definition of eccentricity, it has an important impact on the observed gravitational wave signal of such systems, generating power in all possible harmonics of the orbital period. We here clarify the possible discrepancies between different eccentricity parameters used to describe the orbital dynamics of binary systems across different approximations, specifically the post-Newtonian approximation, the self-force approximation, and numerical relativity. To this end, we highlight disparities between the typically used orbit averaged method of evolving binary systems under radiation reaction, and more direct techniques of solving the two-body problem in post-Newtonian theory. We show, both numerically and analytically, that the orbit averaged method breaks down in the late inspiral, failing to capture a strong secular growth in the Keplerian eccentricity parameter and producing a orbital de-phasing relative to direct integration of the two-body equations of motion. We show that the secular growth and de-phasing affect the observed gravitational wave signal, which could bias how accurately we may recover parameters for systems with signal-to-noise ratios . We further develop a frequency domain post-adiabatic waveform model to capture these effects, and study the precision to which we may estimate parameters with this model through a Fisher information matrix analysis.