Breaking baryon-cosmology degeneracy with the electron density power spectrum

TL;DR

This paper explores the electron density auto-power spectrum as a robust cosmological probe that can improve constraints on matter density and baryon fraction, while being less affected by galaxy feedback uncertainties.

Contribution

It demonstrates that the electron density auto-power spectrum provides strong, feedback-insensitive constraints on key cosmological parameters using simulations and idealized analysis.

Findings

Electron density auto-correlation constrains $\

_{ m bar}$ and $_{ m bar}$ with robustness to feedback models.

Constraints are obtainable via kSZ observations or FRB dispersion measures.

Abstract

Uncertain feedback processes in galaxies affect the distribution of matter, currently limiting the power of weak lensing surveys. If we can identify cosmological statistics that are robust against these uncertainties, or constrain these effects by other means, then we can enhance the power of current and upcoming observations from weak lensing surveys such as DES, Euclid, the Rubin Observatory, and the Roman Space Telescope. In this work, we investigate the potential of the electron density auto-power spectrum as a robust probe of cosmology and baryonic feedback. We use a suite of (magneto-)hydrodynamic simulations from the CAMELS project and perform an idealized analysis to forecast statistical uncertainties on a limited set of cosmological and physically-motivated astrophysical parameters. We find that the electron number density auto-correlation, measurable through either kinematic Sunyaev-Zel'dovich observations or through Fast Radio Burst dispersion measures, provides tight constraints on $\Omega_{m}$ and the mean baryon fraction in intermediate-mass halos, $\bar{f}_{\mathrm{bar}}$. By obtaining an empirical measure for the associated systematic uncertainties, we find these constraints to be largely robust to differences in baryonic feedback models implemented in hydrodynamic simulations. We further discuss the main caveats associated with our analysis, and point out possible directions for future work.