Probing primordial features with the stochastic gravitational wave background

被引:70
|
作者
Braglia, Matteo [1 ,2 ,3 ]
Chen, Xingang [4 ]
Hazra, Dhiraj Kumar [2 ,5 ]
机构
[1] Univ Bologna, Alma Mater Studiorum, Dipartimento Fis & Astron, DIFA, Via Gobetti 93-2, I-40129 Bologna, Italy
[2] INAF OAS Bologna, Osservatorio Astrofis & Sci Spazio, Area Ric CNR INAF, Via Gobetti 101, I-40129 Bologna, Italy
[3] Ist Nazl Fis Nucl, Sez Bologna, Via Irnerio 46, I-40126 Bologna, Italy
[4] Harvard Smithsonian Ctr Astrophys, Inst Theory & Computat, 60 Garden St, Cambridge, MA 02138 USA
[5] HBNI, Inst Math Sci, CIT Campus, Chennai 600113, Tamil Nadu, India
关键词
inflation; primordial gravitational waves (theory); PERTURBATIONS; RADIATION; SPECTRUM; UNIVERSE;
D O I
10.1088/1475-7516/2021/03/005
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
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. In some cases the scalar power spectrum can significantly exceed the n(s) = 5 limit in single-field inflation and grow as fast as n(s) = 9.1. 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 construct 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.
引用
收藏
页数:36
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