Full Modeling and Parameter Compression Methods in configuration space for DESI 2024 and beyond

Understand

In the contemporary era of high-precision spectroscopic surveys, led by projects like DESI, there is an increasing demand for optimizing the extraction of cosmological information from clustering data.

• This work conducts a thorough comparison of various methodologies for modeling the full shape of the two-point statistics in configuration space.
• We investigate the performance of both direct fits (Full-Modeling) and the parameter compression approaches (ShapeFit and Standard).
• We utilize the ABACUS-SUMMIT simulations, tailored to exceed DESI's precision requirements.