Surrogate models for precessing binary black hole simulations with unequal masses
Surrogate models for precessing binary black hole simulations with unequal masses
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DOI：
10.1103/physrevresearch.1.033015
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发表时间：
2019-05
影响因子：
4.2
通讯作者：
V. Varma;Scott E. Field;M. Scheel;J. Blackman;D. Gerosa;L. Stein;Lawrence E. Kidder;H. Pfeiffer
中科院分区：
文献类型：
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作者：
V. Varma;Scott E. Field;M. Scheel;J. Blackman;D. Gerosa;L. Stein;Lawrence E. Kidder;H. Pfeiffer
只有数值相对论模拟才能捕获双黑洞合并的全部复杂性。然而，这些模拟对于参数估计等直接数据分析应用来说过于昂贵。我们为这些模拟的输出提出了两个新的快速且准确的替代模型：第一个模型 NRSur7dq4 预测引力波形，第二个模型 \RemnantModel 预测残余黑洞的属性。这些模型将以前的 7 维非偏心进动模型扩展到更高的质量比，并针对质量比 $q\leq4$ 和自旋幅度 $\chi_1,\chi_2 \leq 0.8$ 以及通用自旋方向的 1528 个模拟进行了训练。波形模型 NRSur7dq4 在合并前开始大约 20 个轨道，包括所有 $\ell \leq 4$ 自旋加权球谐模，以及黑洞的进动框架动力学和自旋演化。最终的黑洞模型 \RemnantModel 对残余黑洞的质量、自旋和反冲速度进行建模。在训练参数范围内，这两个模型都比现有模型准确至少一个数量级，误差与数值相对论模拟中的估计误差相当。我们还表明，即使在训练参数空间范围之外（最高质量比 $q=6$）外推，代理模型也能很好地工作。
Only numerical relativity simulations can capture the full complexities of binary black hole mergers. These simulations, however, are prohibitively expensive for direct data analysis applications such as parameter estimation. We present two new fast and accurate surrogate models for the outputs of these simulations: the first model, NRSur7dq4, predicts the gravitational waveform and the second model, \RemnantModel, predicts the properties of the remnant black hole. These models extend previous 7-dimensional, non-eccentric precessing models to higher mass ratios, and have been trained against 1528 simulations with mass ratios $q\leq4$ and spin magnitudes $\chi_1,\chi_2 \leq 0.8$, with generic spin directions. The waveform model, NRSur7dq4, which begins about 20 orbits before merger, includes all $\ell \leq 4$ spin-weighted spherical harmonic modes, as well as the precession frame dynamics and spin evolution of the black holes. The final black hole model, \RemnantModel, models the mass, spin, and recoil kick velocity of the remnant black hole. In their training parameter range, both models are shown to be more accurate than existing models by at least an order of magnitude, with errors comparable to the estimated errors in the numerical relativity simulations. We also show that the surrogate models work well even when extrapolated outside their training parameter space range, up to mass ratios $q=6$.