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arXiv 2302.07043astro-ph.GA
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LISA螺旋粒子群极值质量比随机背景的计算

Computation of stochastic background from extreme mass ratio inspiral populations for LISA

Federico Pozzoli, Stanislav Babak, Alberto Sesana, Matteo Bonetti, Nikolaos Karnesis

摘要:

极端质量比吸气(EMRI)是激光干涉仪空间天线(LISA)的主要目标之一。这些系统的极端质量比导致相对较弱的GW信号,只能单独解决宇宙学附近的源(高达$z\approx2$)。由未分辨EMRI发射的信号的不相干堆积产生混淆噪声,其可以形式上被视为随机GW背景(GWB)。在本文中,我们估计这个背景的水平,考虑收集天体物理学动机的EMRI模型,跨越影响EMRI形成的不确定性的范围。为此,我们采用了创新的增强分析Kludge波形,并使用了完整的LISA响应函数。对于每个模型,我们计算GWB SNR和可分辨源的数量。从文献中的EMRI信号的简化计算相比,我们发现,对于一个给定的模型的GWB SNR是低的$\approx 2$的一个因素,而可分辨的源的数量下降了一个因素3-5。尽管如此,绝大多数模型导致潜在可检测的GWB,这也可以显着有助于在1-10 mHz频率范围内的整体LISA噪声预算。

英文摘要:

Extreme mass ratio inspirals (EMRIs) are among the primary targets for the Laser Interferometer Space Antenna (LISA). The extreme mass ratios of these systems result in relatively weak GW signals, that can be individually resolved only for cosmologically nearby sources (up to $z\approx2$). The incoherent piling up of the signal emitted by unresolved EMRIs generate a confusion noise, that can be formally treated as a stochastic GW background (GWB). In this paper, we estimate the level of this background considering a collection of astrophysically motivated EMRI models, spanning the range of uncertainties affecting EMRI formation. To this end, we employed the innovative Augmented Analytic Kludge waveforms and used the full LISA response function. For each model, we compute the GWB SNR and the number of resolvable sources. Compared to simplified computations of the EMRI signals from the literature, we find that for a given model the GWB SNR is lower by a factor of $\approx 2$ whereas the number of resolvable sources drops by a factor 3-to-5. Nonetheless, the vast majority of the models result in potentially detectable GWB which can also significantly contribute to the overall LISA noise budget in the 1-10 mHz frequency range.

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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