Robust parameter estimation for compact binaries with ground-based gravitational-wave observations using the LALInference software library
John Veitch, Vivien Raymond, Benjamin Farr, Will M. Farr, Philip Graff, Salvatore Vitale, Ben Aylott, Kent Blackburn, Nelson Christensen, Michael Coughlin, Walt… 展开作者
John Veitch, Vivien Raymond, Benjamin Farr, Will M. Farr, Philip Graff, Salvatore Vitale, Ben Aylott, Kent Blackburn, Nelson Christensen, Michael Coughlin, Walter Del Pozzo, Farhan Feroz, Jonathan Gair, Carl-Johan Haster, Vicky Kalogera, Tyson Littenberg, Ilya Mandel, Richard O'Shaughnessy, Matthew Pitkin, Carl Rodriguez, Christian Röver, Trevor Sidery, Rory Smith, Marc Van Der Sluys, Alberto Vecchio, Will Vousden, Leslie Wade
The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star, a neutron star black hole binary and a binary black hole, where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence parameter space.
Parameter Estimation of Gravitational Waves from Nonprecessing BH-NS Inspirals with higher harmonics: Comparing MCMC posteriors to an Effective Fisher Matrix
The stepping-stone sampling algorithm for calculating the evidence of gravitational wave models
贝叶斯统计推断对于分析Advanced LIGO和Advanced Virgo引力波探测器的观测结果变得越来越重要。为此，迭代模拟技术，特别是嵌套采样和并行回火，已在软件库LALInference中实现，以从紧凑型二元聚结事件的波形参数的后验分布中采样。嵌套抽样主要用于计算模型的边际似然，但也会产生后验样本。采用热力学积分计算的证据，使用平行回火产生的样品，但已被发现是计算要求。在这里，我们提出了垫脚石采样算法，最初由Xie et al.（2011）在遗传学和路径采样的特殊情况下提出，作为热力学积分的替代方案。垫脚石采样算法也是基于来自并行回火的功率后验的样本，但具有更好的性能，因为温度步长更少，因此需要计算资源来实现相同的精度。我们证明了它的性能和计算成本相比，热力学集成和嵌套采样的模拟研究和计算的边缘可能性的二元黑洞信号模型应用于模拟数据的高级LIGO和高级处女座引力波探测器的案例研究。为了解决目前基于幂后验技术估计证据估计标准误的方法不足的问题，我们提出了一种新的块引导方法，并在我们的模拟研究和LIGO应用中显示了其潜力。
Celephais: efficient spectral initial data code for precessing compact binaries
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Max Planck Institute for Gravitational Physics (Albert Einstein Institute)（马克斯·普朗克引力物理研究所（阿尔伯特·爱因斯坦研究所））
Bayesian inference for compact binary coalescences with BILBY: Validation and application to the first LIGO--Virgo gravitational-wave transient catalogue
