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arXiv 2403.03487gr-qc

利用数值相对论与旋近-并合-铃宕模型研究偏心双黑洞并合

Study of eccentric binary black hole mergers using numerical relativity and an inspiral-merger-ringdown model

Tousif Islam

AI总结:

本研究实现并验证了偏心双黑洞波形模型\texttt{EccentricIMR},确认其在一定偏心率与质量比范围内与数值相对论数据匹配良好,还用于交叉比对不同星表数据、检验圆轨道并合模型及探究平近点角的作用。

摘要:

我们借助数值相对论(NR)波形与参考文献[Hinder:2017sxy](Hinder、Kidder与Pfeiffer,arXiv:1709.02007)中提出的\texttt{EccentricIMR}波形模型,研究无自旋偏心双黑洞(BBH)并合的现象学特征。该模型通过将偏心旋近阶段(源自后牛顿(PN)近似,包含对双黑洞动力学的3PN保守项与2PN耗散项贡献)与圆轨道并合模型相结合构建而成。\texttt{EccentricIMR}的一个显著特点是采用偏心率和平近点角这两个参数来表征偏心波形。我们在\texttt{Python}中实现了\texttt{EccentricIMR}模型,以便于常规使用。随后,我们利用来自SXS和RIT两个数值相对论星表的35个偏心NR波形对该模型进行验证。结果发现,在无量纲参考频率$x=0.07$下偏心率最高达$0.16$、质量比最高达$q=4$的范围内,\texttt{EccentricIMR}模型与NR数据匹配效果良好。此外,我们将该模型用作工具,对SXS与RIT星表中的偏心NR数据进行交叉比对。我们还结合NR数据与\texttt{EccentricIMR}模型,探究了偏心双黑洞并合建模中常用的圆轨道并合模型的有效性。最后,我们利用该模型研究了平近点角在偏心双黑洞并合中的作用。

英文摘要:

We study the phenomenology of non-spinning eccentric binary black hole (BBH) mergers using numerical relativity (NR) waveforms and \texttt{EccentricIMR} waveform model, as presented in Ref. \cite{Hinder:2017sxy} (Hinder, Kidder, and Pfeiffer, arXiv:1709.02007). This model is formulated by combining an eccentric inspiral, derived from a post-Newtonian (PN) approximation including 3PN conservative and 2PN reactive contributions to the BBH dynamics, with a circular merger model. A distinctive feature of \texttt{EccentricIMR} is its two-parameter treatment, utilizing eccentricity and mean anomaly, to characterize eccentric waveforms. We implement the \texttt{EccentricIMR} model in \texttt{Python} to facilitate routine use. We then validate the model against 35 eccentric NR waveforms obtained from both the SXS and RIT NR catalogs. We find that \texttt{EccentricIMR} model reasonably match NR data for eccentricities up to $0.16$, specified at a dimensionless reference frequency of $x=0.07$, and mass ratios up to $q=4$. Additionally, we use this model as a tool for cross-comparing eccentric NR data obtained from the SXS and RIT catalogs. Furthermore, we explore the validity of a circular merger model often used in eccentric BBH merger modelling using both the NR data and \texttt{EccentricIMR} model. Finally, we use this model to explore the effect of mean anomaly in eccentric BBH mergers.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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