Itamar J. Allali, Mark P. Hertzberg, Fabrizio Rompineve

We develop a new phenomenological model that addresses current tensions between observations of the early and late Universe. Our scenario features: (i) a decaying dark energy fluid, which undergoes a transition at $z \sim 5,000$, to raise today's value of the Hubble parameter -- addressing the $H_0$ tension, and (ii) an ultra-light axion, which starts oscillating at $z\sim 16,000$, to suppress the matter power spectrum -- addressing the $S_8$ tension. Our Markov Chain Monte Carlo analyses show that such a Dark Sector model fits a combination of early time datasets slightly better than the $\Lambda$CDM model, while reducing both the $H_0$ and $S_8$ tensions to $\lesssim 3\sigma$ level. Combined with measurements from cosmic shear surveys, we find that the discrepancy on $S_8$ is reduced to the $1.4\sigma$ level, and the value of $H_0$ is further raised. Adding local supernovae measurements, we find that the $H_0$ and $S_8$ tensions are reduced to the $1.5\sigma$ and $1.1\sigma$ level respectively, with a significant improvement $\Delta\chi^2\simeq -17$ compared to the $\Lambda$CDM model. We discuss a possible particle physics realization of this model, with a dark confining gauge sector and its associated axion, although embedding the full details within microphysics remains an urgent open question. Our scenario will be decisively probed with future CMB surveys.

Giovanni Aricò, Raul E. Angulo, Matteo Zennaro

The linear matter power spectrum is an essential ingredient in all theoretical models for interpreting large-scale-structure observables. Although Boltzmann codes such as CLASS or CAMB are very efficient at computing the linear spectrum, the analysis of data usually requires $10^4$-$10^6$ evaluations, which means this task can be the most computationally expensive aspect of data analysis. Here, we address this problem by building a neural network emulator that provides the linear theory matter power spectrum in about one millisecond with 0.3% accuracy over $10^{-3} \le k [h\,{\rm Mpc}^{-1}] < 30$. We train this emulator with more than 150,000 measurements, spanning a broad cosmological parameter space that includes massive neutrinos and dynamical dark energy. We show that the parameter range and accuracy of our emulator is enough to get unbiased cosmological constraints in the analysis of a Euclid-like weak lensing survey. Complementing this emulator, we train 15 other emulators for the cross-spectra of various linear fields in Eulerian space, as predicted by 2nd-order Lagrangian Perturbation theory, which can be used to accelerate perturbative bias descriptions of galaxy clustering. Our emulators are especially designed to be used in combination with emulators for the nonlinear matter power spectrum and for baryonic effects, all of which are publicly available at this http URL