Efficient parameter estimation is critical for Gravitational-Wave astronomy. In the case of compact binary coalescence, the high dimensional parameter space demands efficient sampling techniques - such as Markov chain Monte Carlo (MCMC). A number of degeneracies effectively reduce the dimensionality of the parameter space and, when known, can render sampling algorithms more efficient with problem-specific improvements. We present in this paper an analytical description of a degeneracy involving the extrinsic parameters of a compact binary coalescence gravitational-wave signal, when data from a three detector network (such as Advanced LIGO/Virgo) is available. We use this new formula to construct a jump proposal, a framework for a generic sampler to take advantage of the degeneracy. We show the gain in efficiency for a MCMC sampler in the analysis of the gravitational-wave signal from a compact binary coalescence.
pespace: A new tool of GPU-accelerated and auto-differentiable response generation and likelihood evaluation for space-borne gravitational wave detectors
University of Science and Technology of China（中国科学技术大学）；Guizhou University（贵州大学）
Beyond Gaussian Assumptions: A new robust statistical framework for gravitational-wave data analysis
University of Minnesota（明尼苏达大学）；NSF Institute on Accelerated AI Algorithms for Data-Driven Discovery (A3D3), MIT（美国国家科学基金会加速AI算法驱动发现研究所（A3D3），麻省理工学院）；Aristotle University of Thessaloniki（塞萨洛尼基亚里士多德大学）；University of California（加州大学）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）
A thorough investigation of cross-correlation estimators for stochastic gravitational-wave background searches in ground-based detector data
University of Minnesota（明尼苏达大学）；University of Texas Rio Grande Valley（德克萨斯大学里奥格兰德河谷分校）；Inter-University Centre for Astronomy and Astrophysics（大学间天体物理中心）；ETH Zurich（苏黎世联邦理工学院）
Probabilistic kilonova prediction from gravitational wave inferred binary neutron star parameters
University of Glasgow（格拉斯哥大学）；Liverpool John Moores University（利物浦约翰摩尔大学）；University of Cambridge（剑桥大学）；University of Leicester（莱斯特大学）；Utrecht University（乌得勒支大学）
