Abstract

ABSTRACT We present a framework for characterizing the large-scale movement of baryons relative to dark matter in cosmological simulations, requiring only the initial conditions and final state of the simulation. This is performed using the spread metric that quantifies the distance in the final conditions between initially neighbouring particles, and by analysing the baryonic content of final haloes relative to that of the initial Lagrangian regions (LRs) defined by their dark matter component. Applying this framework to the simba cosmological simulations, we show that 40 per cent (10 per cent) of cosmological baryons have moved $\gt 1\, h^{-1}\, {\rm Mpc}{}$ ($3\, h^{-1}\, {\rm Mpc}{}$) by z = 0, primarily due to entrainment of gas by jets powered by an active galactic nucleus, with baryons moving up to $12\, h^{-1}\, {\rm Mpc}{}$ away in extreme cases. Baryons decouple from the dynamics of the dark matter component due to hydrodynamic forces, radiative cooling, and feedback processes. As a result, only 60 per cent of the gas content in a given halo at z = 0 originates from its LR, roughly independent of halo mass. A typical halo in the mass range Mvir = 1012–1013 M⊙ only retains 20 per cent of the gas originally contained in its LR. We show that up to 20 per cent of the gas content in a typical Milky Way-mass halo may originate in the region defined by the dark matter of another halo. This inter-Lagrangian baryon transfer may have important implications for the origin of gas and metals in the circumgalactic medium of galaxies, as well as for semi-analytic models of galaxy formation and ‘zoom-in’ simulations.

Highlights

  • Cosmological simulations are an important tool to study the evolution of the universe

  • The remainder of this paper is organized as follows: In Section 2, we discuss the SIMBA simulation suite that is used for analysis; in Section 3, we discuss a distance-based metric for the investigation of feedback strength; in Section 4, we discuss halo-level metrics based on Lagrangian regions (LRs) to study inter-Lagrangian transfer; in Section 5, we discuss the convergence of the method; and in Section 6, we conclude and summarize the results

  • We have explored the relative motion of dark matter and baryons using a particle-level metric, showing that AGN jets in the SIMBA cosmological simulations can spread baryons up to 12 h−1 Mpc relative to the neighbouring dark matter

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Summary

INTRODUCTION

It has been recognized that feedback processes from the formation of stars and black holes have an important effect on the resulting observable baryonic component, though they have a small effect on the collisionless dark matter Such feedback often takes the form of large-scale winds that eject substantial amounts of gas from galaxies due to energetic input from young stars, supernovae, and active galactic nuclei (AGNs). This gas can be deposited far out in the intergalactic medium (IGM), remain as halo gas in the circumgalactic medium (CGM), or be re-accreted in ‘wind recycling’ (Oppenheimer et al 2010; Christensen et al 2016; Angles-Alcazar et al 2017b; Christensen et al 2018; Hafen et al 2019b). The remainder of this paper is organized as follows: In Section 2, we discuss the SIMBA simulation suite that is used for analysis; in Section 3, we discuss a distance-based metric for the investigation of feedback strength; in Section 4, we discuss halo-level metrics based on LRs to study inter-Lagrangian transfer; in Section 5, we discuss the convergence of the method; and in Section 6, we conclude and summarize the results

Code and subgrid model
Defining haloes
Defining LRs
QUANTIFYING BARYON REDISTRIBUTION
The spread metric
Baryon spreading in SIMBA
Connecting feedback and the spread of baryons
Redshift evolution of the spread metric
LAGRANGIAN BARYON TRANSFER
The different origins of baryons and dark matter in haloes
Computing transfer between LRs
Transfer in a non-radiative model
Transfer into haloes
Redshift evolution of transfer into haloes
Transfer out of LRs
Filling in holes in LRs
The sizes of LRs
Findings
DISCUSSION AND CONCLUSIONS
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