Predictions for local PNG bias in the galaxy power spectrum and bispectrum and the consequences for f NL constraints

Barreira, Alexandre (2022): Predictions for local PNG bias in the galaxy power spectrum and bispectrum and the consequences for f NL constraints. In: Journal of Cosmology and Astroparticle Physics, Bd. 2022, Nr. 01, 033

Abstract

We use hydrodynamical separate universe simulations with the IllustrisTNG model to predict the local primordial non-Gaussianity (PNG) bias parameters bϕ and bϕδ, which enter at leading order in the galaxy power spectrum and bispectrum. This is the first time that bϕδ is measured from either gravity-only or galaxy formation simulations. For dark matter halos, the popular assumption of universality overpredicts the bϕδ(b1) relation in the range 1 ≲ b1 ≲ 3 by up to Δ bϕδ ∼ 3 (b1 is the linear density bias). The adequacy of the universality relation is worse for the simulated galaxies, with the relations bϕ(b1) and bϕδ(b1) being generically redshift-dependent and very sensitive to how galaxies are selected (we test total, stellar and black hole mass, black hole mass accretion rate and color). The uncertainties on bϕ and bϕδ have a direct, often overlooked impact on the constraints of the local PNG parameter fNL, which we study and discuss. For a survey with V = 100 Gpc3/h3 at z=1, uncertainties Δ bϕ ≲ 1 and Δ bϕδ ≲ 5 around values close to the fiducial can yield relatively unbiased constraints on fNL using power spectrum and bispectrum data. We also show why priors on galaxy bias are useful even in analyses that fit for products fNLbϕ and fNLbϕδ. The strategies we discuss to deal with galaxy bias uncertainties can be straightforwardly implemented in existing fNL constraint analyses (we provide fits for some of the bias relations). Our results motivate more works with galaxy formation simulations to refine our understanding of bϕ and bϕδ towards improved constraints on fNL.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Physik
• Themengebiete: 500 Naturwissenschaften und Mathematik > 530 Physik
• ISSN: 1475-7516
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 491502892