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Improved effective-one-body model of spinning, nonprecessing binary black holes for the era of gravitational-wave astrophysics with advanced detectors

机译:重力波天体物理学时代具有先进探测器的改进的有效无旋体二元黑洞有效一人模型

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摘要

We improve the accuracy of the effective-one-body (EOB) waveforms that were employed during the first observing run of Advanced LIGO for binaries of spinning, nonprecessing black holes by calibrating them to a set of 141 numerical-relativity (NR) waveforms. The NR simulations expand the domain of calibration toward larger mass ratios and spins, as compared to the previous EOBNR model. Merger-ringdown waveforms computed in black-hole perturbation theory for Kerr spins close to extremal provide additional inputs to the calibration. For the inspiral-plunge phase, we use a Markov-chain Monte Carlo algorithm to efficiently explore the calibration space. For the merger-ringdown phase, we fit the NR signals with phenomenological formulae. After extrapolation of the calibrated model to arbitrary mass ratios and spins, the (dominant-mode) EOBNR waveforms have faithfulness—at design Advanced-LIGO sensitivity—above 99% against all the NR waveforms, including 16 additional waveforms used for validation, when maximizing only on initial phase and time. This implies a negligible loss in event rate due to modeling for these binary configurations. We find that future NR simulations at mass ratios ≳4 and double spin ≳0.8 will be crucial to resolving discrepancies between different ways of extrapolating waveform models. We also find that some of the NR simulations that already exist in such region of parameter space are too short to constrain the low-frequency portion of the models. Finally, we build a reduced-order version of the EOBNR model to speed up waveform generation by orders of magnitude, thus enabling intensive data-analysis applications during the upcoming observation runs of Advanced LIGO.
机译:我们通过将先进的LIGO进行第一次观测运行,将其校准为一组141个数值相关性(NR)波形,从而提高了旋转,无进动黑洞的二进制速度时在高级LIGO首次运行过程中采用的有效一体(EOB)波形的准确性。与以前的EOBNR模型相比,NR模拟将校准范围扩大到更大的质量比和旋转。在黑洞扰动理论中为接近极值的Kerr自旋计算的归并衰减波形为校准提供了额外的输入。对于吸气下降阶段,我们使用马尔可夫链蒙特卡罗算法来有效地探索校准空间。对于合并终止阶段,我们用现象学公式拟合NR信号。将校准模型外推至任意质量比和自旋后,(主导模式)EONBR波形(在设计时为高级LIGO灵敏度)对所有NR波形具有超过99%的忠实度,包括16个用于验证的其他波形(最大化时)仅在初始阶段和时间。这意味着由于对这些二进制配置进行了建模,因此事件发生率的损失可以忽略不计。我们发现,将来以质量比≳4和双自旋≳0.8进行的NR模拟对于解决波形模型外推方法之间的差异至关重要。我们还发现,在参数空间的这种区域中已经存在的一些NR模拟太短而无法约束模型的低频部分。最后,我们构建了EOBNR模型的降阶版本,以将波形生成速度提高了几个数量级,从而在即将进行的Advanced LIGO观测运行期间启用了密集的数据分析应用程序。

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