Primordial power spectrum from a matter-ekpyrotic scenario in loop quantum cosmology
Primordial power spectrum from a matter-ekpyrotic scenario in loop quantum cosmology
复制标题
环量子宇宙学中物质火场景的原始功率谱
DOI:
10.1142/9789811269776_0348
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Singh, Parampreet
中科院分区:
文献类型:
--
作者:
Li, Bao-Fei;Saini, Sahil;Singh, Parampreet
The general matter bounce scenario, including an Ekpyrotic field to avoid anisotropic instabilities, is studied in a loop quantized isotropic and homogeneous FLRW setting. The matter bounce scenario provides a convenient way to include quantum corrections from the bounce in the perturbations originating in the far past, which also produce a scale invariant power spectrum. LQC provides the right setting for studying quantum corrections in a matter bounce scenario as the bounce in LQC occurs entirely due to quantum geometrical effects without needing any exotic matter fields to avoid the singularity. A detailed exploration of this general matter-Ekpyrotic scenario in spatially flat FLRW spacetime in LQC filled with minimally coupled dust and Ekpyrotic scalar field is studied with the help of numerical simulations. Various features of the background dynamics are shown to be robust under variations in initial conditions and choice of parameters. We use the dressed metric approach for the perturbations and obtain a scale invariant power spectrum for modes exiting the horizon in the dust dominated contracting phase. In contrast to previous studies considering a constant equation of state for the Ekpyrotic field, we found that the magnitude of the power spectrum changes during the evolution. The scale invariant section of the power spectrum also undergoes a rapid increase in its magnitude in the bounce regime, while its scale invariance is unaffected. We argue that apart from increasing the magnitude, the bounce regime may only substantially affect the modes outside the scale invariant regime. However, the spectral index is found to be too close to unity, thus inconsistent with the observational constraints, necessitating further modifications of the model.