Perturbation theory for modeling galaxy bias: Validation with simulations of the Dark Energy Survey

Abstract

We describe perturbation theory (PT) models of galaxy bias for applications to photometric galaxy surveys. We model the galaxy-galaxy and galaxy-matter correlation functions in configuration space and validate against measurements from mock catalogs designed for the Dark Energy Survey (DES). We find that an effective PT model with five galaxy bias parameters provides a good description of the 3D correlation functions above scales of 4 Mpc=h and z < 1. Our tests show that at the projected precision of the DES Year 3 analysis, two of the nonlinear bias parameters can be fixed to their coevolution values, and a third (the k 2 term for higher derivative bias) set to zero. The agreement is typically at the 2% level over scales of interest, which is the statistical uncertainty of our simulation measurements. To achieve this level of agreement, our fiducial model requires using the full nonlinear matter power spectrum (rather than the one-loop PT one). We also measure the relationship between the nonlinear and linear bias parameters and compare them to their expected coevolution values. We use these tests to motivate the galaxy bias model and scale cuts for the cosmological analysis of the Dark Energy Survey; our conclusions are generally applicable to all photometric surveys.

Perturbation theory models for LSST-era galaxy clustering: tests with sub-percent mock catalog measurements in Fourier and configuration space

“…Our results differ from those of Pandey et al [24] who found that the 2-parameter was sufficient to describe the 3D correlation function ratios ξ gg /ξ mm and ξ gm /ξ mm in DES-like mock galaxy catalogs from the MICE [57][58][59] simulation. The insufficiency of the 2-parameter model in our analysis is likely a result of the increased statistical precision of our correlation function measurements.…”

“…Furthermore, letting all five bias parameters vary freely yields significant improvements in our ability to model all galaxy samples. Our findings differ from those of [24] who found that the 2-parameter model provides sufficient precision for DES analysis. This discrepancy is likeley a result of the increased precision of the measurements in this analysis.…”

“…Whereas the DES analysis was focused on 2% precision, our measurements had error bars on the order of 0.1%. Nevertheless, Pandey et al [24] was performed in configuration space so we present a more detailed comparison in §III B.…”

“…In this paper, we validate the perturbative bias model used in the DES Y3 [9,22,24,25] analysis (both for the sample of red galaxies and the sample of bright magnitude limited galaxies) against a deep, magnitude lim-ited LSST-like galaxy sample from the CosmoDC2 simulation, the largest synthetic photometric dataset to date. The less-biased galaxies included in our faint samples are likely to be easier to model than the bright galaxies residing in the centers of the most massive halos, which tend to come from overdense regions of the Universe subject to stronger non-linear gravitational processes.…”

The mass and galaxy distribution around SZ-selected clusters

“…6 The second order bias parameter for clusters (b (2) c ) is estimated using the relation calibrated from N-body simulations as described in Lazeyras et al (2016). For the galaxies, we approximate the second order bias using the calibration described in Pandey et al (2020) which used DES mocks.…”