发表机构
Laboratoire d’étude de l’Univers et des phénomènes eXtrêmes (LUX), Observatoire de Paris, Université PSL, Sorbonne Université, CNRS; Department of Physics, University of Virginia（极端宇宙现象实验室，巴黎天文台，巴黎文理研究大学，索邦大学，法国国家科学研究中心; 弗吉尼亚大学物理系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究构建了非自旋双黑洞引力波记忆信号的唯象频域模型，精度达$10^{-4}-10^{-3}$量级，效率高于时域模型，相关实现已开源。
AI 中文摘要
我们提出了一种针对准圆轨道上非自旋双黑洞并合产生的引力波（GW）记忆信号的唯象频域模型。针对引力波记忆信号的主导球谐模式$(l,m)=(2,0)$，我们分别构建了振幅模型和相位模型。这些模型由基本函数和超越函数的叠加构成，可高效计算。模型的振幅和相位两部分均通过数值相对论代理模型校准，质量比范围为1至8。利用第四观测 run 的先进 LIGO 灵敏度曲线，通过计算与数值相对论模型的失配度来评估模型精度，在 LIGO 覆盖的总质量参数空间内，失配度为$10^{-4}-10^{-3}$量级。所得频域模型比作者此前开发的相关时域模型具有更高的计算效率，且在 Python 包 GWMemoryModel 中提供了时域和频域两种模型的开源实现，可用于非自旋双黑洞的相关分析。
英文摘要
We present a phenomenological frequency-domain model for the gravitational-wave (GW) memory signal from nonspinning binary-black-hole mergers on quasicircular orbits. We develop separate amplitude and phase models for the dominant $(l,m)=(2,0)$ spherical-harmonic mode of the GW memory signal. The amplitude and phase models are built from superpositions of elementary and transcendental functions, which can be evaluated efficiently. Both portions of the model are calibrated against a numerical-relativity surrogate model over mass ratios from one to eight. Their accuracy is assessed by computing their mismatch with the numerical-relativity models using the Advanced LIGO sensitivity curve from the fourth observing run. The mismatches are of the order $10^{-4}\unicode{x2013}10^{-3}$ over the parameter space of total mass covered by LIGO. The resulting frequency-domain model is a more computationally efficient waveform model for the GW memory signal than a related time-domain model earlier produced by the authors. An open-access implementation of both the time-domain and frequency-domain models is provided in the Python package GWMemoryModel, which can be used for relevant analyses of nonspinning binary black holes.
