论文标题
加速重力波的参数性测试对一般相对性的参数化测试，使用了多个可能性分解
Accelerating gravitational-wave parameterized tests of General Relativity using a multiband decomposition of likelihood
论文作者
论文摘要
从紧凑型二元合并（CBC）中检测重力波，使我们能够探测一般相对论（GR）的强场动力学。在Ligo-Virgo-Kagra协作进行的各种测试中，是参数化测试，其中引入并限制对GR波形的参数化修改。该分析通常需要生成数百万个计算昂贵的波形。对于更长的信号，计算成本较高，并且当前的分析需要数周的年度才能完成二进制中子星（BNS）信号。在这项工作中，我们提出了一种技术，可以使用一位可能性的多次分解来加速参数化测试，该分解最初是为了加速CBC信号的参数估计分析，假设其中一位作者是GR的。我们表明，对于低频截止，我们的技术会加快1.4 MSUN-1.4 MSUN BNS信号的参数化测试的速度（10）。我们还使用模拟信号和真实数据验证方法的准确性。
The detection of gravitational waves from compact binary coalescence (CBC) has allowed us to probe the strong-field dynamics of General Relativity (GR). Among various tests performed by the LIGO-Virgo-KAGRA collaboration are parameterized tests, where parameterized modifications to GR waveforms are introduced and constrained. This analysis typically requires the generation of more than millions of computationally expensive waveforms. The computational cost is higher for a longer signal, and current analyses take weeks-years to complete for a binary neutron star (BNS) signal. In this work, we present a technique to accelerate the parameterized tests using a multiband decomposition of likelihood, which was originally proposed to accelerate parameter estimation analyses of CBC signals assuming GR by one of the authors. We show that our technique speeds up the parameterized tests of a 1.4 Msun-1.4 Msun BNS signal by a factor of O(10) for a low-frequency cutoff of 20 Hz. We also verify the accuracy of our method using simulated signals and real data.
