# Assessing non-linear models for galaxy clustering III: Theoretical accuracy for Stage IV surveys

## TL;DR

This study compares two models for galaxy clustering in large surveys, finding the TNS model more accurate and robust across various tests, which is crucial for precise cosmological measurements.

## Contribution

The paper provides a comprehensive MCMC comparison of TNS and EFTofLSS models, establishing the TNS model's superior validity range for Stage IV survey analyses.

## Key findings

- TNS model's validity range is broader and more robust.
- EFTofLSS model struggles with highly biased tracers and large volumes.
- Constraints on the growth rate are stronger with the TNS model.

## Abstract

We provide in depth MCMC comparisons of two different models for the halo redshift space power spectrum, namely a variant of the commonly applied Taruya-Nishimichi-Saito (TNS) model and an effective field theory of large scale structure (EFTofLSS) inspired model. Using many simulation realisations and Stage IV survey-like specifications for the covariance matrix, we check each model's range of validity by testing for bias in the recovery of the fiducial growth rate of structure formation. The robustness of the determined range of validity is then tested by performing additional MCMC analyses using higher order multipoles, a larger survey volume and a more highly biased tracer catalogue. We find that under all tests, the TNS model's range of validity remains robust and is found to be much higher than previous estimates. The EFTofLSS model fails to capture the spectra for highly biased tracers as well as becoming biased at higher wavenumbers when considering a very large survey volume. Further, we find that the marginalised constraints on $f$ for all analyses are stronger when using the TNS model.