UC Riverside

The Legacy Survey of Space and Time (LSST) carried out by the Vera C. Rubin Observatory is one of the most ambitious optical surveys planned in the near future. It will generate $\sim 20$~TB of data every night during its 10 year survey duration. Simulated data sets (``Data Challenges'') have been generated by the LSST Dark Energy Science Collaboration (DESC) to allow development of efficient analysis algorithms, evaluation of their performance and scaling capabilities, and to study the impact of systematic uncertainties. In this work we focus on the analysis of Large Scale Structure using galaxies selected from the DESC Data Challenge 2 (DC2) corresponding to a survey area of 300 square degrees. We develop and perform an end-to-end analysis of the galaxy Large Scale Structure with the DC2 data, validating the extraction of galaxy power spectra and galaxy bias in the presence of complex systematics. We provide a range of strong consistency checks of both the simulated data and the analysis techniques.

Based on matching selected galaxies with the DC2 truth catalog, we optimize selection to obtain a clean sample of galaxies. After generating and applying survey masks, we produce galaxy density maps binned in redshift, with six bins from $z = 0.2 - 1.4$. We generate the power spectra measurements from the processed data and fit the data using theoretical predictions to estimate the galaxy bias as a function of redshift. Finally, we study the effect of systematic uncertainties on estimation of the galaxy bias.

We find that the relative uncertainty $\sigma_\ell / C_\ell$ in the measured angular power spectra is smaller than 10\% in most cases, and smaller than 4\% at multipoles above 1500.% Changes in the angular power spectra due to systematic uncertainties are found to be on average of order 0.5\%, i.e. $\Delta C_\ell / C_\ell \approx 0.5\%$, with a maximum deviation of 1.5\%. % Systematic effects are small compared to the statistical uncertainty of the measured angular power spectra: $\Delta C_\ell \sim 0.1 \sigma_\ell$ on average with a maximum of $0.25 \sigma_\ell$.