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

Pandey, S.; Krause, E.; Jain, B.; MacCrann, N.; Blazek, J.; Crocce, M.; DeRose, J.; Fang, X.; Ferrero, I.; Friedrich, O.; Aguena, M.; Allam, S.; Annis, J.; Avila, S.; Bernstein, G. M.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Costanzi, M.; da Costa, L. N.; De Vicente, J.; Desai, S.; Elvin-Poole, J.; Everett, S.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Honscheid, K.; Kuehn, K.; Kuropatkin, N.; Maia, M. A. G.; Marshall, J. L.; Menanteau, F.; Miquel, R.; Palmese, A.; Paz-Chinchón, F.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Serrano, S.; Sevilla-Noarbe, I.; Smith, M.; Soares-Santos, M.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Weller, J.; DES Collaboration
Bibliographical reference

Physical Review D

Advertised on:
12
2020
Number of authors
56
IAC number of authors
2
Citations
31
Refereed citations
25
Description
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 k2 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.
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