第三代探测器中长时引力波信号的快速贝叶斯推断
Fast Bayesian Inference for Long-Duration Gravitational-Wave Signals in 3G detectors
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中文总结 AI 辅助
针对3G引力波探测器观测长时信号的计算瓶颈，采用JKS分解与相对分箱技术，实现21.3小时信号似然评估加速10^4倍，使长时信号贝叶斯推断成为现实。
中文摘要 AI 辅助
第三代（3G）引力波探测器将观测双中子星并合近一天，因此地球自转成为信号的一部分而非可忽略的修正项。这破坏了内禀与外禀参数的常规分离，成为贝叶斯推断的主要计算瓶颈。我们证明，精确的五阶谐波Jaranowski-Krolak-Schutz（JKS）分解可恢复旋转天线振幅响应与计算开销大的内禀波形计算的分离。通过在内禀波形由其相位曲率确定的频率网格上采样，再应用误差可控的相对分箱，21.3小时信号的似然评估加速了10^4量级，使长达一天的3G信号推断成为可能。
英文摘要
Third-generation (3G) gravitational-wave detectors will observe binary-neutron-star inspirals for nearly a day, so Earth's rotation becomes part of the signal rather than a negligible correction. This destroys the usual separation between intrinsic and extrinsic parameters and creates a major computational bottleneck for Bayesian inference. We show that the exact five-harmonic Jaranowski-Krolak-Schutz (JKS) decomposition restores the separation of the rotating antenna amplitude response from the computationally expensive intrinsic waveform calculations. By sampling the intrinsic waveform on a frequency grid set by its phase curvature and then applying error-controlled relative binning, likelihood evaluations for a 21.3-h signal are accelerated by O(10^4), making day-long 3G signal inference practical.
发表机构
- Indian Institute of Technology Gandhinagar（印度理工学院甘德纳格尔分校）
机构由 AI 辅助整理，请以论文原文为准。
