Baryonic effects for weak lensing. Part II. Combination with X-ray data and extended cosmologies

Abstract

An accurate modelling of baryonic feedback effects is required to exploit the full potential of future weak-lensing surveys such as Euclid or LSST. In this second paper in a series of two, we combine Euclid-like mock data of the cosmic shear power spectrum with an eROSITA X-ray mock of the cluster gas fraction to run a combined likelihood analysis including both cosmological and baryonic parameters. Following the first paper of this series, the baryonic effects (based on the baryonic correction model of Ref.[1]) are included in both the tomographic power spectrum and the covariance matrix. However, this time we assume the more realistic case of a ΛCDM cosmology with massive neutrinos and we consider several extensions of the currently favoured cosmological model. For the standard ΛCDM case, we show that including X-ray data reduces the uncertainties on the sum of the neutrino mass by ∼ 30 percent, while there is only a mild improvement on other parameters such as Ω m and σ 8 . As extensions of ΛCDM, we consider the cases of a dynamical dark energy model (wCDM), a f (R) gravity model (fRCDM), and a mixed dark matter model (ΛMDM) with both a cold and a warm/hot dark matter component. We find that combining weak-lensing with X-ray data only leads to a mild improvement of the constraints on the additional parameters of wCDM, while the improvement is more substantial for both fRCDM and ΛMDM. Ignoring baryonic effects in the analysis pipeline leads significant false-detections of either phantom dark energy or a light subdominant dark matter component. Overall we conclude that for all cosmologies considered, a general parametrisation of baryonic effects is both necessary and sufficient to obtain tight constraints on cosmological parameters.

Euclid: Impact of non-linear and baryonic feedback prescriptions on cosmological parameter estimation from weak lensing cosmic shear

“…In the most constraining setting ( max = 5000), for all the three cases we considered, we find significant biases for all the cosmological parameters, except for {ω b,0 , ln (10 10 A s )}, which are actually constrained by the Planck data rather than by cosmic shear. While this work was near to completion, Schneider et al (2020) presented a similar analysis, but their method to account for baryons is very different from the one we have adopted here. They use instead a model for the baryonification of dark matter only simulations to determine the matter power spectrum (Schneider et al 2019).…”

Feedback from Active Galactic Nuclei in Galaxy Groups

“…Systematic effects can be mitigated by excluding the small scales (k 10 −1 h/Mpc) when fitting the measured power spectra, although that comes at the price of greatly increased uncertainties in the resulting cosmological parameters. Constraints on extended cosmologies, such as massive neutrinos, variable dark energy equation of state, or chameleon gravity, require sensitivity on smaller scales, and their effect is strongly degenerate with that of baryonic physics [326,327].…”

“…Calibrating their semi-analytic model on the observed gas fraction and gas density profiles of group-scale halos, Schneider et al [329] provided a range of predictions matching the existing observational constraints. High-precision measurements of the gas density profiles in a representative sample of galaxy groups would allow us to precisely determine the expected shape of the power spectrum [327], thereby providing a key input for upcoming cosmology experiments.…”

On the impact of galaxy bias uncertainties on primordial non-Gaussianity constraints

“…Such an interesting set of studies can involve determining the values of p predicted from current state-of-the-art galaxy formation simulations (as Ref. [65] did recently with IllustrisTNG) and use the mean and scatter of the predictions to inform priors on p. This is akin to the case of baryonic effects on the small-scale total matter power spectrum that is a major source of uncertainty in weak-lensing data analysis, and whose priors are also often informed by hydrodynamical simulations [98][99][100][101][102].…”