Model-agnostic cosmological inference using the BAO feature

The baryon acoustic oscillation (BAO) feature in the clustering of biased tracers of cosmological matter, such as galaxies, is a key prediction of the Big Bang model of the evolution of the Universe, rooted in well-understood atomic physics. Being a standard ruler, the BAO feature plays a critical role in cosmological inference using large-volume galaxy redshift surveys. Traditional BAO analyses typically build on templates derived from assuming a cosmological model such as standard Lambda-cold dark matter (LCDM). In order to convincingly test LCDM (or any model), however, one requires a model-agnostic description of the BAO feature involving a number of ingredients. Physically, one must describe the impact of cosmological bulk flows which progressively and anisotropically smear out the feature over time. One must also model nonlinear effects such as the scale dependence of tracer bias and the gravitational coupling between short and long scales. All of these can be incorporated using the so-called Zel'dovich approximation, without reference to any particular cosmological model. On the technical front, one needs a robust, complete and cosmology-independent basis of 1-dimensional functions to describe the shape of the BAO feature in linear theory, which can then be propagated to the nonlinearly evolved, measured feature. I will describe how these ingredients -- which have been systematically constructed in recent work -- come together in an accurate framework capable of describing the BAO-scale pairwise measurements of state-of-the-art galaxy surveys, thus enabling model-agnostic cosmological inference.