Baryon Acoustic Oscillations estimation from galaxies surveys: spectroscopic vs. photometric redshifts

Abstract

Baryon Acoustic Oscillations (BAO) are one of the Large-Scale Structure probes to constrain cosmological information. For that, one requires observation of the Cosmic Microwave Background (CMB) or galaxy surveys. In this study, we focused on estimating BAO using two types of surveys, one spectroscopic and the other photometric. With a spectroscopic survey, more precise than the photometric, we studied the implications of a model-independent approach for the transverse BAO scale using the SDSS BOSS and eBOSS samples. Particularly, we focused on comparing a covariance matrix from mock catalogs and from the data sample. Another approach for spectroscopic samples was to study how assuming the redshift as a field is sensitive enough to find the BAO signal, this method is called Angular Redshift Fluctuations (ARF), and this analysis was restricted to Fisher forecasts future spectroscopic surveys: Euclid and DESI. For the photometric analysis, we constructed redshift catalogs using different algorithms and analysed their precision without any assumption to the number density distribution using the DES Y3 BAO Sample. Furthermore, we tested choosing the best galaxies with the least noisy Prob ability Density Function (PDF). From those catalogs, we compared the BAO estimation for a model that uses each galaxy’s real PDFs without any assumption of gaussianity of these distributions. We compared the BAO feature from the algorithms and their subsamples. Our investigation revealed that employing a sample covariance achieves results akin to using mock simulations, though the latter seem to push the result towards the assumed cosmological model. ARF stands out as a promising observable for upcoming surveys targeting the BAO signal, particularly when used in tandem with ADF and by crossing various redshift shells. Moreover, our examination of photometric catalogs led us to determine that selecting a PDF aligns with colour comparisons from the training spectroscopic sample, thereby influencing the inference of cosmological parameters through the two-point correlation function.