On priors and scale cuts in EFT-based full-shape analyses

TL;DR

This paper investigates how priors and scale cuts in EFT-based full-shape galaxy survey analyses can introduce systematic biases, especially due to two-loop corrections, affecting the accuracy of cosmological parameter estimation.

Contribution

It extends previous studies by analyzing the impact of analysis choices, particularly scale cuts, on parameter biases using high-fidelity simulation data, highlighting the importance of careful analysis design.

Findings

Scale cuts can bias parameters, overestimating σ8 by over 5%.

Different analysis codes (PyBird vs. CLASS-PT) show varying bias levels.

Two-loop corrections cause systematic biases that do not diminish with better priors.

Abstract

Parameter estimation from galaxy survey data from the full-shape method depends on scale cuts and priors on EFT parameters. The effects of priors, including the so-called ''prior volume'' phenomenon have been originally studied in Ivanov et al. (2019) and subsequent works. In this note, we repeat and extend these tests and also apply them to other priors used in the literature. We point out that in addition to the ''prior volume'' effect there is a more dangerous effect that is largely overlooked: a systematic bias on cosmological parameters due to overoptimistic scale cuts. Unlike the ''prior volume'' effect, this is a genuine systematic bias due to two-loop corrections that does not vanish with better priors or with larger data volumes. Our study is based on the high fidelity BOSS-like PT Challenge simulation data which offer many advantages over analyses based on synthetic data generated with fitting pipelines. We show that some analysis choices associated with the PyBird code, especially the scale cuts, significantly bias parameter recovery, overestimating $\sigma_8$ by over $5\%$ (equivalent to $1\sigma$). The bias on measured EFT parameters is even more significant. In contrast, the analysis choices associated with the CLASS-PT code lead to much smaller ($\lesssim 1\%$) shifts in cosmological parameters based on their best-fit values.