论文标题
探测具有随机重力波背景的原始特征
Probing Primordial Features with the Stochastic Gravitational Wave Background
论文作者
论文摘要
随机重力波背景(SGWB)提供了一个新的机会,可以观察到通货膨胀模型中原始特征的信号。我们通过未来的基于空间的重力波实验研究它们的可检测性,将分析重点放在丽莎任务的频率范围上。我们通过探索能够生成不同类别的特征类别的两场膨胀模型的参数空间来计算重力波谱。这些信号落入观测窗口中,尺度和振幅进行微调是必要的。一旦出现,可以区分不同基础通货膨胀物理学的特征的几类频率依赖性振荡信号,并且SGWB提供了独立于宇宙微波背景和大规模结构的原始宇宙动力学的窗口。为了与未来的实验数据联系,我们讨论了如何将结果应用于数据分析的两种方法。首先,我们讨论使用LISA重建信号的可能性,Lisa需要高信噪比。第二个更敏感的方法是应用代表光谱作为估计器的模板。出于后一个目的,我们得出可以准确捕获几类特征信号的光谱特征并将其与其他物理机制生成的SGWB进行比较的模板。
The stochastic gravitational wave background (SGWB) offers a new opportunity to observe signals of primordial features from inflationary models. We study their detectability with future space-based gravitational waves experiments, focusing our analysis on the frequency range of the LISA mission. We compute gravitational wave spectra from primordial features by exploring the parameter space of a two-field inflation model capable of generating different classes of features. Fine-tuning in scales and amplitudes is necessary for these signals to fall in the observational windows. Once they show up, several classes of frequency-dependent oscillatory signals, characteristic of different underlying inflationary physics, may be distinguished and the SGWB provides a window on dynamics of the primordial universe independent of cosmic microwave background and large-scale structure. To connect with future experimental data, we discuss two approaches of how the results may be applied to data analyses. First, we discuss the possibility of reconstructing the signal with LISA, which requires a high signal-to-noise ratio. The second more sensitive approach is to apply templates representing the spectra as estimators. For the latter purpose, we derive templates that can accurately capture the spectral features of several classes of feature signals and compare them with the SGWB produced by other physical mechanisms.