论文标题

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

论文作者

Rose, Caitlin A., Valsan, Vinaya, Brady, Patrick R., Walsh, Sinead, Pankow, Chris

论文摘要

在多理智的天体物理学时代,重力波信号的低延迟参数估计对于电磁随访观测至关重要。在本文中,我们提出了一种新版本的紧凑型二进制文件的贝叶斯参数估计方案,称为Rapid PE。快速PE通过将固有参数(例如二进制的质量和旋转)固定到围绕搜索识别的固有点上的网格并通过Monte Carlo采样在外部参数上整合到网格上,从而使参数估计平行。 Rapid PE的原始版本计算了有效的Fisher矩阵,以将固有参数固定到椭圆形网格上。在这里,我们在内在空间中使用直线网格。直线固有网格的使用提供了更容易的选择的选项,并允许自适应网格改进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后部。我们证明,此参数估计方法可为来自二进制中子星星合并的模拟重力波信号产生可靠的结果。

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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