Quantifying the accuracy of the Alcock-Paczynski scaling of baryon acoustic oscillation measurements

TL;DR

This paper evaluates the accuracy of the Alcock-Paczynski scaling in BAO measurements, introduces an improved method, and tests their effectiveness on mock catalogues, revealing systematic errors that impact cosmological inferences.

Contribution

The paper proposes a new constant AP scaling method that improves upon conventional approaches and assesses its performance across various cosmological models.

Findings

Conventional AP scaling is effective for large-scale metrics but fails with significant metric gradients.

The new AP scaling method maintains accuracy across all tested models.

Systematic errors of about 1% occur when the true cosmology differs substantially from the fiducial model.

Abstract

We investigate - in a generic setting - the regime of applicability of the Alcock-Paczynski (AP) scaling conventionally applied to test different cosmological models, given a fiducial measurement of the baryon acoustic oscillation (BAO) characteristic scale in the galaxy 2-point correlation function. We quantify the error in conventional AP scaling methods, for which our ignorance about the true cosmology is parameterised in terms of two constant AP scaling parameters. We propose a new, and as it turns out, improved version of the constant AP scaling, also consisting of two scaling parameters. The two constant AP scaling methods are almost indistinguishable when the fiducial model used in data reduction and the "true" underlying cosmology are not differing substantially in terms of metric gradients, but are otherwise expected to differ. Our new methods can be applied to existing analyses through a reinterpretation of the results of the conventional AP scaling. This reinterpretation might be important in model universes where curvature gradients above the scale of galaxies are significant. We test our theoretical findings on $\Lambda$CDM mock catalogues. The conventional constant AP scaling methods are surprisingly successful for pairs of large-scale metrics, but eventually break down when toy models allowing for large metric gradients are tested. The new constant AP scaling methods proposed in this paper are efficient for all test models examined. We find systematic errors of ~1% in the recovery of the BAO scale when the true model is distant from the fiducial, which cannot be attributed to any constant AP approximation. The level of systematic uncertainty is robust to the exact fitting method employed. This indicates that caution must be taken with the error budget when extrapolating the BAO acoustic scale measurements obtained in the standard literature.