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引力波从天体源的引力透镜效应:理论、探测与应用

Gravitational Lensing of Gravitational Waves from Astrophysical Sources: Theory, Detection, and Applications

National Astronomical Observatories, Chinese Academy of Sciences(中国科学院国家天文台);School of Astronomy and Space Sciences, University of Chinese Academy of Sciences(中国科学院大学天文学与空间科学学院)

Zhiwei Chen, Youjun Lu

AI总结:

本文探讨引力波透镜效应的理论、探测方法及应用,分析其在宇宙学和基础物理中的潜力。

摘要:

来自遥远源的引力波,如 inspiralling 和 merging 的恒星级致密双星、中等质量和超大质量双黑洞,可通过 intervening 物体(如恒星、原始黑洞、星系和团块)发生引力透镜效应。根据引力波波长与透镜尺度的关系,透镜效应分为几何光学和波光学两种模式:几何光学产生多个成像和时间延迟与放大,波光学导致频率依赖的波形调制。通过事件对参数重叠或特征频率依赖调制识别透镜信号。探测率取决于源和透镜的红移和质量分布,未来观测站有前景。一旦确认,透镜引力波将成为探索基本物理和宇宙学的强大工具:可约束暗物质、透镜结构、哈勃常数和其他宇宙学参数。本文综述了引力波透镜的理论框架、预测探测率、搜索策略和应用,并总结了观测和利用透镜天体引力波事件的前景和未来方向。

英文摘要:

Gravitational waves (GWs) from distant sources such as inspiralling and merging stellar-mass compact binaries, intermediate-mass and supermassive-binary-black-hole can be gravitationally lensed by intervening objects, ranging from stars and primordial black holes to galaxies and clusters. Depending on the GW wavelength relative to the lens scale, lensing occurs in two regimes: geometric optics, producing multiple images with time delays and magnifications, and wave optics, resulting in frequency-dependent waveform modulations. Lensed signals are identified via parameter overlap between event pairs or characteristic frequency-dependent modulations that distinguish them from unlensed signals. Detection rates depend on the redshift and mass distributions of sources and lenses, with promising prospects for future observatories. Once confirmed, lensed GWs will be powerful probes of fundamental physics and cosmology: they can constrain dark matter, lensing structures, the Hubble constant, and other cosmological parameters. In this review, we provide a concise overview of GW lensing, covering the theoretical framework, predicted detection rates, search strategies, and applications. We conclude with prospects and future directions for observing and exploiting lensed astrophysical GW events.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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