Fast extreme-mass-ratio-inspiral waveforms: New tools for millihertz gravitational-wave data analysis
Fast extreme-mass-ratio-inspiral waveforms: New tools for millihertz gravitational-wave data analysis
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DOI：
10.1103/physrevd.104.064047
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发表时间：
2021-04
影响因子：
5
通讯作者：
Michael L. Katz;A. J. Chua;L. Speri;Niels Warburton;S. Hughes
中科院分区：
文献类型：
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作者：
Michael L. Katz;A. J. Chua;L. Speri;Niels Warburton;S. Hughes
我们推出了 FastEMRIWaveforms (FEW) 软件包，这是一个用于构建和分析极端质量比螺旋 (EMRI) 波形的工具集合。在这里，我们对《物理评论快报》进行了扩展，该快报介绍了第一个快速、准确的完全相对论 EMRI 波形模板模型。我们讨论总体框架的构建；组成模块；以及用于加速 EMRI 波形的一般方法。由于完全相对论 FEW 模型波形目前仅限于史瓦西时空中的偏心轨道，因此我们还引入了一种改进的增强分析 Kludge (AAK) 模型，该模型描述了通用克尔螺旋。两种波形模型都可以使用图形处理单元 (GPU) 硬件进行加速。有了 GPU 加速波形，就可以进行各种研究，包括 EMRI 模式内容分析、模板不匹配以及完全基于贝叶斯马尔可夫链蒙特卡罗的 EMRI 参数估计。我们发现相对论 EMRI 波形模板可以使用较少的谐波模式 ($\sim10-100$) 生成，而无需偏置信号提取。然而，我们首次证明，提取具有半相对论振幅的相对论注入可能会导致参数空间某些区域的后验分布出现强烈偏差和异常结构。
We present the FastEMRIWaveforms (FEW) package, a collection of tools to build and analyze extreme mass ratio inspiral (EMRI) waveforms. Here, we expand on the Physical Review Letter that introduced the first fast and accurate fully-relativistic EMRI waveform template model. We discuss the construction of the overall framework; constituent modules; and the general methods used to accelerate EMRI waveforms. Because the fully relativistic FEW model waveforms are for now limited to eccentric orbits in the Schwarzschild spacetime, we also introduce an improved Augmented Analytic Kludge (AAK) model that describes generic Kerr inspirals. Both waveform models can be accelerated using graphics processing unit (GPU) hardware. With the GPU-accelerated waveforms in hand, a variety of studies are performed including an analysis of EMRI mode content, template mismatch, and fully Bayesian Markov Chain Monte Carlo-based EMRI parameter estimation. We find relativistic EMRI waveform templates can be generated with fewer harmonic modes ($\sim10-100$) without biasing signal extraction. However, we show for the first time that extraction of a relativistic injection with semi-relativistic amplitudes can lead to strong bias and anomalous structure in the posterior distribution for certain regions of parameter space.