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arXiv 1602.00620gr-qcastro-ph.HEastro-ph.IM
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用于EMRI数据分析的增广组装波形和高斯过程回归

Augmented kludge waveforms and Gaussian process regression for EMRI data analysis

Alvin J. K. Chua

摘要:

极端质量比螺旋线(EMRI)将是未来天基引力波探测器的一种重要天体物理源。在这些探测器的数据分析中,需要对EMRI波形模板的准确性和计算速度进行权衡。我们讨论了如何使用更快的模板所产生的系统误差可以减少与改进的模型,如增强组装波形,并与统计技术,如高斯过程回归边缘化。

英文摘要:

Extreme-mass-ratio inspirals (EMRIs) will be an important type of astrophysical source for future space-based gravitational-wave detectors. There is a trade-off between accuracy and computational speed for the EMRI waveform templates required in the analysis of data from these detectors. We discuss how the systematic error incurred by using faster templates may be reduced with improved models such as augmented kludge waveforms, and marginalised over with statistical techniques such as Gaussian process regression.

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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