Ultra-large-scale approximations and galaxy clustering: debiasing constraints on cosmological parameters

TL;DR

This paper addresses the challenges of analyzing ultra-large-scale galaxy clustering data by quantifying biases from approximations, and proposes a debiasing method to efficiently recover accurate cosmological parameters.

Contribution

It introduces a simple debiasing technique that corrects parameter estimates without requiring computationally expensive exact calculations.

Findings

Neglecting relativistic effects biases cosmological parameters.

Approximate methods can lead to false detections of new physics.

The proposed debiasing method effectively recovers true cosmologies.

Abstract

Upcoming galaxy surveys will allow us to probe the growth of the cosmic large-scale structure with improved sensitivity compared to current missions, and will also map larger areas of the sky. This means that in addition to the increased precision in observations, future surveys will also access the ultra-large-scale regime, where commonly neglected effects such as lensing, redshift-space distortions and relativistic corrections become important for calculating correlation functions of galaxy positions. At the same time, several approximations usually made in these calculations, such as the Limber approximation, break down at those scales. The need to abandon these approximations and simplifying assumptions at large scales creates severe issues for parameter estimation methods. On the one hand, exact calculations of theoretical angular power spectra become computationally expensive, and the need to perform them thousands of times to reconstruct posterior probability distributions for cosmological parameters makes the approach unfeasible. On the other hand, neglecting relativistic effects and relying on approximations may significantly bias the estimates of cosmological parameters. In this work, we quantify this bias and investigate how an incomplete modelling of various effects on ultra-large scales could lead to false detections of new physics beyond the standard $\Lambda$CDM model. Furthermore, we propose a simple debiasing method that allows us to recover true cosmologies without running the full parameter estimation pipeline with exact theoretical calculations. This method can therefore provide a fast way of obtaining accurate values of cosmological parameters and estimates of exact posterior probability distributions from ultra-large-scale observations.