A fully Lagrangian, non-parametric bias model for dark-matter halos

Abstract

We present a non-parametric Lagrangian biasing model and fit the ratio of the halo and mass densities at the field level using the mass-weighted halo field in the AbacusSummit simulations at $z=0.5$. Unlike the perturbative halo bias model widely used in interpreting the observed large-scale structure traced by galaxies, we find a non-negative halo-to-mass ratio that increases monotonically with the linear overdensity ${\delta }_1$ in the initial Lagrangian space. The bias expansion, however, does not guarantee non-negativity of the halo counts, and may give rising halo number counts at negative overdensities. The shape of the halo-to-mass ratio is unlikely to be described by a polynomial of ${\delta }_1$ and other quantities. Especially for massive halos with $6\times 10^{12}{h}^{-1}{M}_{\odot }$, the halo-to-mass ratio starts soaring up at ${\delta }_1>0$, substantially different from the predictions of the bias expansion. We show that for the halo masses we consider ($M>3\times 10^{11}{h}^{-1}{M}_{\odot }$) a non-parametric halo-to-mass ratio as a function of ${\delta }_1$ and its local derivative ${\nabla }^2{\delta }_1$ can recover the halo power spectra to sub-percent level for wavenumbers $k=0.01-0.1h{\mathrm{Mpc}}^{-1}$ given a proper smoothing scale to filter the initial density field, even though we do not fit the power spectrum directly. However, there is mild dependence of the recovery of the halo power spectrum on the smoothing scale and other input parameters. At $k<0.01h{\mathrm{Mpc}}^{-1}$ and for massive halos with $M>6\times 10^{12}{h}^{-1}{M}_{\odot }$, our non-parametric model leads to a few percent overestimation of the halo power spectrum, indicating the need for larger or multiple smoothing scales. The halo-to-mass ratios obtained qualitatively agree with intuitions from extended Press-Schechter theory. We compare our framework to the bias expansion and discuss possible extensions.

JCAP accepted

References in corpus (16)

• The EAGLE project: Simulating the evolution and assembly of galaxies and their environments
• Introducing the Illustris Project: Simulating the coevolution of dark and visible matter in the Universe
• Simulating galaxy formation with black hole driven thermal and kinetic feedback
• The DESI Experiment Part I: Science,Targeting, and Survey Design
• Clustering of dark matter tracers: generalizing bias for the coming era of precision LSS
• Gravity and Large-Scale Non-local Bias
• AbacusSummit: A Massive Set of High-Accuracy, High-Resolution $N$-Body Simulations
• Understanding higher-order nonlocal halo bias at large scales by combining the power spectrum with the bispectrum
• Modeling scale-dependent bias on the baryonic acoustic scale with the statistics of peaks of Gaussian random fields
• How to suppress the shot noise in galaxy surveys
• The $\text{Abacus}$ Cosmological $N$-body Code
• The Gaussian streaming model and Lagrangian effective field theory
• Simulations and symmetries
• Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies
• Excursion set peaks: the role of shear
• Assembly bias in quadratic bias parameters of dark matter halos from forward modeling

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