3D-Radial galaxy correlation function
Francesco Spezzati, Alvise Raccanelli

TL;DR
This paper evaluates biases in galaxy correlation function modeling for cosmological parameter estimation and introduces a new 3D radial model that reduces these biases, improving accuracy for upcoming galaxy surveys.
Contribution
The paper proposes a novel 3D radial model that effectively minimizes biases in galaxy correlation function analysis, enhancing modeling accuracy for future surveys.
Findings
Neglecting radial and angular separation causes significant parameter biases.
Integrating over redshift reduces but does not eliminate biases.
The 3D radial model significantly decreases parameter estimation biases.
Abstract
Tests of cosmological models via measurements of galaxy correlations will require increasing modeling accuracy, given the high precision of measurements promised by forthcoming galaxy surveys. In this work we investigate the biases introduced in parameter estimation when using different approximations in the modeling of the galaxy two point correlation function. We study this for two example surveys, with different binning strategies, for measurements of the Primordial non-Gaussianity parameter and the growth rate of structures . We then investigate the same issue for the nDGP model, to see if results will change for a different cosmological model. Our results show that failing to properly account for radial and angular separation between galaxies will induce a considerable shift in parameters best fit estimates, the bias being larger for thicker redshift bins.…
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Taxonomy
TopicsScientific Research and Discoveries · Astronomy and Astrophysical Research
