用自适应网格补充快速贝叶斯参数估计方案
Supplementing rapid Bayesian parameter estimation schemes with adaptive grids
摘要：
在多信使天体物理学时代，引力波信号的低延迟参数估计对于电磁跟踪观测至关重要。在本文中，我们提出了一个新的版本的贝叶斯参数估计方案紧凑的二进制称为快速PE。快速PE通过将内在参数（例如二进制的质量和自旋）固定到搜索识别的内在点周围的网格以及通过Monte Carlo采样对外在参数进行积分来并行化参数估计。Rapid PE的原始版本计算了一个有效的Fisher矩阵，以将内部参数固定到椭球网格。这里我们在固有空间中使用直线网格。直线固有网格的使用提供了更容易包括自旋的选项，并允许自适应网格细化以减轻搜索偏差，并在不牺牲采样效率的情况下更完整地绘制出后验。我们证明，这种参数估计方法产生可靠的结果模拟引力波信号从二进制中子星合并。
英文摘要：
In the age of multi-messenger astrophysics, low-latency parameter estimation of gravitational-wave signals is essential for electromagnetic follow-up observations. In this paper, we present a new edition of the Bayesian parameter estimation scheme for compact binaries known as Rapid PE. Rapid PE parallelizes parameter estimation by fixing the intrinsic parameters (such as the masses and spins of the binary) to a grid around a search-identified intrinsic point and by integrating over the extrinsic parameters via Monte Carlo sampling. The original version of Rapid PE calculated an effective Fisher matrix to fix the intrinsic parameters to an ellipsoidal grid. Here we use rectilinear gridding in intrinsic space. The use of rectilinear intrinsic grids provides the option to more easily include spin and allows for adaptive grid refinements to mitigate search biases and map out the posterior more completely without sacrificing sampling efficiency. We demonstrate that this parameter estimation method produces reliable results for simulated gravitational-wave signals from binary neutron star mergers.
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