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arXiv 2307.08697gr-qcastro-ph.HE
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迈向数值相对论赋能的动力学捕获黑洞双体有效单体波形

Towards numerical-relativity informed effective-one-body waveforms for dynamical capture black hole binaries

Tomas Andrade, Juan Trenado, Simone Albanesi, Rossella Gamba, Sebastiano Bernuzzi, Alessandro Nagar, Juan Calderon-Bustillo, Nicolas Sanchis-Gual, Jose A. Font,… 展开作者

Tomas Andrade, Juan Trenado, Simone Albanesi, Rossella Gamba, Sebastiano Bernuzzi, Alessandro Nagar, Juan Calderon-Bustillo, Nicolas Sanchis-Gual, Jose A. Font, William Cook, Boris Daszuta, Francesco Zappa, David Radice

AI总结:

本文利用14项新数值相对论模拟赋能TEOBResumS-Dali的并合-铃宕模型,显著提升动力学捕获黑洞双体波形的匹配度与相位精度。

摘要:

黑洞的动力学捕获可能发生在致密恒星介质中,原因是近距离交会期间引力辐射的发射。探测此类事件需要精细建模,因为其现象学与准圆形双体存在定性差异。能够提供此类波形的模型极少,而且没有任何模型纳入来自非准圆形并合的数值相对论(NR)模拟信息。在本研究中,我们迈出了构建完全由NR赋能的动力学捕获有效单体(EOB)模型的第一步。我们完成了14项新的单次和双次交会并合模拟,并用这些数据为TEOBResumS-Dali近似器的并合-铃宕模型提供信息。我们将初始能量近似保持为双体质量固定值,并使经质量重标度的无量纲角动量在$(0.6,1.1)$范围内变化,质量比在$(1,2.15)$范围内变化,同向排列的无量纲自旋在$(-0.5,0.5)$范围内变化。我们发现,该模型无需修改基线模板即可将NR匹配度提升至97%,改进了以往性能。在对模型进行NR赋能后,除一个对应直接坠入的异常值外,匹配度提升至99%。未赋能模型在并合时的最大EOBNR相位差为0.15弧度,引入NR信息后降至0.1弧度。我们概述了迈向完全赋能的动力学捕获EOB模型的步骤,并讨论了未来改进方向。

英文摘要:

Dynamical captures of black holes may take place in dense stellar media due to the emission of gravitational radiation during a close passage. Detection of such events requires detailed modelling, since their phenomenology qualitatively differs from that of quasi-circular binaries. Very few models can deliver such waveforms, and none includes information from Numerical Relativity (NR) simulations of non quasi-circular coalescences. In this study we present a first step towards a fully NR-informed Effective One Body (EOB) model of dynamical captures. We perform 14 new simulations of single and double encounter mergers, and use this data to inform the merger-ringdown model of the TEOBResumS-Dali approximant. We keep the initial energy approximately fixed to the binary mass, and vary the mass-rescaled, dimensionless angular momentum in the range $(0.6, 1.1)$, the mass ratio in $(1, 2.15)$ and aligned dimensionless spins in $(-0.5, 0.5)$. We find that the model is able to match NR to $97%$, improving previous performances, without the need of modifying the base-line template. Upon NR informing the model, this improves to $99%$ with the exception of one outlier corresponding to a direct plunge. The maximum EOBNR phase difference at merger for the uninformed model is of $0.15$ radians, which is reduced to $0.1$ radians after the NR information is introduced. We outline the steps towards a fully informed EOB model of dynamical captures, and discuss future improvements.

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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