Model-agnostic cosmological constraints from the baryon acoustic oscillation feature in redshift space.

We develop a framework for self-consistently extracting cosmological information from the clustering of tracers in redshift space, without relying on model-dependent templates to describe the baryon acoustic oscillation (BAO) feature. Our approach uses the recently proposed Laguerre reconstruction technique for the BAO feature and its linear point r LP, and substantially extends it to simultaneously model the multipoles ℓ = 0, 2, 4 of the anisotropic galaxy 2-point correlation function (2pcf). The approach is 'model-agnostic': it assumes that the nonlinear growth of structure smears the BAO feature by an approximately Gaussian kernel with a smearing scale σv, but does not assume any fiducial cosmology for describing the shape of the feature itself. Using mock observations for two realistic survey configurations assuming Λ cold dark matter (ΛCDM), combined with Bayesian parameter inference, we show that the linear point r LP and smearing scale σv can be accurately recovered by our method in both existing and upcoming surveys. The precision of the recovery of r LP is always better than |$1{{\ \rm per\ cent}}$|⁠ , while σv can be recovered with |$\lesssim 10{{\ \rm per\ cent}}$| uncertainty provided the linear galaxy bias b is separately constrained, e.g. using weak lensing observations. Our method is also sensitive to the linear growth rate f , albeit with larger uncertainties and systematic errors, especially for upcoming surveys such as DESI. We discuss how our model can be modified to improve the recovery of f , such that the resulting constraints on { f , σv, r LP} can potentially be used as a test of cosmological models including and beyond ΛCDM. [ABSTRACT FROM AUTHOR]