A data compression and optimal galaxy weights scheme for Dark Energy Spectroscopic Instrument and weak lensing datasets

TL;DR

This paper introduces a novel data compression and galaxy weighting scheme for combining spectroscopic and imaging datasets, enhancing the extraction of cosmological information for dark energy studies.

Contribution

It presents a new optimal data compression method and galaxy weighting scheme that preserve cosmological information in combined spectroscopic and imaging surveys.

Findings

The compression scheme retains all information on structure growth.

Galaxy weights derived are near-optimal for cosmological parameter estimation.

The method improves data combination efficiency for upcoming dark energy experiments.

Abstract

Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. The galaxy redshift sample from the Dark Energy Spectroscopic Instrument (DESI) will have a significant overlap with major ongoing imaging surveys specifically designed for weak lensing measurements: the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES) and the Hyper Suprime-Cam (HSC) survey. In this work we analyse simulated redshift and lensing catalogues to establish a new strategy for combining high-quality cosmological imaging and spectroscopic data, in view of the first-year data assembly analysis of DESI. In a test case fitting for a reduced parameter set, we employ an optimal data compression scheme able to identify those aspects of the data that are most sensitive to the cosmological information, and amplify them with respect to other aspects of the data. We find this optimal compression approach is able to preserve all the information related to the growth of structure; we also extend this scheme to derive weights to be applied to individual galaxies, and show that these produce near-optimal results.