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arXiv 2008.06071gr-qc
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用于LISA数据分析的完全相对论性极质量比螺旋波形模板的快速生成

Rapid generation of fully relativistic extreme-mass-ratio-inspiral waveform templates for LISA data analysis

Alvin J. K. Chua, Michael L. Katz, Niels Warburton, Scott A. Hughes

摘要:

未来的空间任务LISA将观测大量的毫赫兹频率的引力波源。其中,紧凑物体进入大质量黑洞的极端质量比激励是将强场复杂性的挑战与长寿命信号的挑战相结合的唯一来源。通过在数据分析期间将这些信号与大量精确波形模板进行比较来发现和表征这些信号,但是通过计算完全相对论性波形中的$\sim10^3$ - $10^5$谐波模式来阻碍这些模板的快速生成。我们使用降阶和深度学习技术来获得这些模式的全局拟合,并在具有硬件加速的完整波形框架中实现它。我们的高保真波形可以在$1\,\mathrm{s}$下生成,并实现$\lesssim 5\times 10^{-4}$与参考波形的不匹配,而参考波形的时间要长$\gtrsim 10^4$倍。这标志着第一次,分析长度的波形与完整的谐波内容可以产生的时间尺度上有用的直接实施LISA分析算法。

英文摘要:

The future space mission LISA will observe a wealth of gravitational-wave sources at millihertz frequencies. Of these, the extreme-mass-ratio inspirals of compact objects into massive black holes are the only sources that combine the challenges of strong-field complexity with that of long-lived signals. Such signals are found and characterized by comparing them against a large number of accurate waveform templates during data analysis, but the rapid generation of such templates is hindered by computing the $\sim10^3$-$10^5$ harmonic modes in a fully relativistic waveform. We use order-reduction and deep-learning techniques to derive a global fit for these modes, and implement it in a complete waveform framework with hardware acceleration. Our high-fidelity waveforms can be generated in under $1\,\mathrm{s}$, and achieve a mismatch of $\lesssim 5\times 10^{-4}$ against reference waveforms that take $\gtrsim 10^4$ times longer. This marks the first time that analysis-length waveforms with full harmonic content can be produced on timescales useful for direct implementation in LISA analysis algorithms.

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