发表机构
Stony Brook University; University of Waterloo; Perimeter Institute for Theoretical Physics; University of Toronto（石溪大学; 滑铁卢大学; 理论物理前沿研究所; 多伦多大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究通过放宽参数空间，发现早期宇宙模型未被排除，并预测未来CMB实验将大幅提升对原初功率谱的约束精度。
AI 中文摘要
原初标量功率谱为早期宇宙物理提供了一个强有力的窗口，涵盖了一大类暴胀场景。这些模型通常预言特征性的标量谱指数$(n_s)$、非零的谱跑动$(\alpha_s)$，或更普遍的偏离纯幂律形式。我们发现，释放轻子遗迹物种数$(N_{\rm eff})$和中微子质量之和$(\sum m_\nu)$会拓宽$n_s$误差轮廓，使得关键的早期宇宙模型不再被排除。特别是，虽然Starobinsky暴胀和双热大爆炸模型在六参数$\Lambda$CDM模型中大约在95%置信水平上被排除，但在九参数$\Lambda{\rm CDM} + \alpha_s + N_{\rm eff} + \sum m_\nu$模型中，来自Planck、ACT和SPT（CMB-PAS）的CMB数据与DESI DR2结合给出$n_s = 0.9758 \pm 0.0064$和$\alpha_s = 0.0080 \pm 0.0064$，与这两个模型均一致。未来的CMB设施将大幅提高对$n_s$、$\alpha_s$以及更普遍的分段原初功率谱$\mathcal{P}(k)$的约束。例如，CMB-PAS将$e^{-2\tau}\mathcal{P}(k = 0.2\\,{\rm Mpc}^{-1})$约束到0.5%，而SO-like和CMB-HD-like巡天将把这一约束收紧到0.1%；CMB-HD还将把这一测量扩展到更小的、此前未探测的尺度，将$e^{-2\tau}\mathcal{P}(k = 30\\,{\rm Mpc}^{-1})$约束在十倍以内。我们发布了我们的预测代码，并更新了公开的CMB-HD似然和Fisher代码以支持CLASS和CAMB。
英文摘要
The primordial scalar power spectrum provides a powerful window onto early-universe physics, including a broad class of inflationary scenarios. These models often predict a characteristic scalar spectral index $(n_s)$, nonzero running $(α_s)$, or more general deviations from a pure power-law form. We find that freeing the number of light relic species $(N_{\rm eff})$ and the sum of the neutrino masses $(\sum m_ν)$ broadens the $n_s$ error contours enough that key early-Universe models are no longer excluded. In particular, while both Starobinsky inflation and the Bi-thermal Big Bang model are ruled out at about the 95% confidence level in the six-parameter $Λ$CDM model, we find that in the nine-parameter $Λ{\rm CDM} + α_s + N_{\rm eff} + \sum m_ν$ model, CMB data from Planck, ACT, and SPT (CMB-PAS) combined with DESI DR2 give $n_s = 0.9758 \pm 0.0064$ and $α_s = 0.0080 \pm 0.0064$, consistent with both models. Future CMB facilities will sharply improve constraints on $n_s$, $α_s$, and, more generally, the binned primordial power spectrum $\mathcal{P}(k)$. For example, CMB-PAS constrains $e^{-2τ}\mathcal{P}(k = 0.2\,{\rm Mpc}^{-1})$ to 0.5%, while SO-like and CMB-HD-like surveys would tighten this to 0.1%; CMB-HD would also extend this measurement to smaller, previously unprobed scales, constraining $e^{-2τ}\mathcal{P}(k = 30\,{\rm Mpc}^{-1})$ to within a factor of ten. We release our forecast code and update the public CMB-HD likelihood and Fisher codes to support CLASS in addition to CAMB.
Comments28 pages, 11 figures, 7 tables. The code used here to generate the current and projected constraints is available at https://github.com/CMB-HD/hdInitPk , and the CMB-HD likelihood and Fisher codes at https://github.com/CMB-HD/hdfisher and https://github.com/CMB-HD/hdlike are updated to support CLASS
