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arxiv: 2103.13618 · v1 · pith:PUIKGVOAnew · submitted 2021-03-25 · 🌌 astro-ph.CO

Constraints on ΛCDM Extensions from the SPT-3G 2018 EE and TE Power Spectra

classification 🌌 astro-ph.CO
keywords constraintsextensionsspt-3gcombineddataspectraplancktextit
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We present constraints on extensions to the $\Lambda$CDM cosmological model from measurements of the $E$-mode polarization auto-power spectrum and the temperature-$E$-mode cross-power spectrum of the cosmic microwave background (CMB) made using 2018 SPT-3G data. The extensions considered vary the primordial helium abundance, the effective number of relativistic degrees of freedom, the sum of neutrino masses, the relativistic energy density and mass of a sterile neutrino, and the mean spatial curvature. We do not find clear evidence for any of these extensions, from either the SPT-3G 2018 dataset alone or in combination with baryon acoustic oscillation and \textit{Planck} data. None of these model extensions significantly relax the tension between Hubble-constant, $H_0$, constraints from the CMB and from distance-ladder measurements using Cepheids and supernovae. The addition of the SPT-3G 2018 data to \textit{Planck} reduces the square-root of the determinants of the parameter covariance matrices by factors of $1.3 - 2.0$ across these models, signaling a substantial reduction in the allowed parameter volume. We also explore CMB-based constraints on $H_0$ from combined SPT, \textit{Planck}, and ACT DR4 datasets. While individual experiments see some indications of different $H_0$ values between the $TT$, $TE$, and $EE$ spectra, the combined $H_0$ constraints are consistent between the three spectra. For the full combined datasets, we report $H_0 = 67.49 \pm 0.53\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$, which is the tightest constraint on $H_0$ from CMB power spectra to date and in $4.1\,\sigma$ tension with the most precise distance-ladder-based measurement of $H_0$. The SPT-3G survey is planned to continue through at least 2023, with existing maps of combined 2019 and 2020 data already having $\sim3.5\times$ lower noise than the maps used in this analysis.

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