Priors on Lagrangian bias parameters from galaxy formation modelling

Author:

Zennaro Matteo1ORCID,Angulo Raul E12ORCID,Contreras Sergio1ORCID,Pellejero-Ibáñez Marcos1,Maion Francisco13ORCID

Affiliation:

1. Donostia International Physics Center (DIPC) , Paseo Manuel de Lardizabal, 4, E-20018 Donostia-San Sebastián, Guipuzkoa, Spain

2. IKERBASQUE, Basque Foundation for Science , E-48013 Bilbao, Spain

3. Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo , Rua do Matão 1371, CEP 05508-090, São Paulo, Brazil

Abstract

ABSTRACT We study the relations among the parameters of the hybrid Lagrangian bias expansion model, fitting biased auto and cross power spectra up to $k_{\rm max} = 0.7 \, h \, \mathrm{Mpc}^{-1}$. We consider ∼8000 halo and galaxy samples, with different halo masses, redshifts, galaxy number densities, and varying the parameters of the galaxy formation model. Galaxy samples are obtained through state-of-the-art extended subhalo abundance matching techniques and include both stellar mass and star formation rate selected galaxies. All of these synthetic galaxy samples are publicly available. We find that the hybrid Lagrangian bias model provides accurate fits to all of our halo and galaxy samples. The coevolution relations between galaxy bias parameters, although roughly compatible with those obtained for haloes, show systematic shifts and larger scatter. We explore possible sources of this difference in terms of dependence on halo occupation and assembly bias of each sample. The bias parameter relations displayed in this work can be used as a prior for future Bayesian analyses employing the hybrid Lagrangian bias expansion model.

Funder

ERC

FAPESP

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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2. Hybrid bias and displacement emulators for field-level modelling of galaxy clustering in real and redshift space;Monthly Notices of the Royal Astronomical Society;2024-02-16

3. Galaxy bias in the era of LSST: perturbative bias expansions;Journal of Cosmology and Astroparticle Physics;2024-02-01

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