Quantifying the impact of baryon-CDM perturbations on halo clustering and baryon fraction

Khoraminezhad, Hasti; Lazeyras, Titouan; Angulo, Raúl E.; Hahn, Oliver; Viel, Matteo

doi:10.1088/1475-7516/2021/03/023

Cited by 13 publications

(40 citation statements)

References 60 publications

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“…However, baryon-dark matter differences could be imprinted in halo formation, as expected on theoretical grounds. This question was indeed investigated by using simulations with adaptive softening (Khoraminezhad et al 2021) and by using an extension of the separate universe approach (Barreira et al 2020a), which does not suffer from the numerical inaccuracies described above. These authors showed that halo formation is actually sensitive to baryon-dark matter fluctuations, in agreement with analytic arguments (Chen et al 2019;Schmidt 2016).…”

Section: Baryonsmentioning

confidence: 99%

Large-scale dark matter simulations

Angulo

Hahn

2022

Living Rev Comput Astrophys

Self Cite

111

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We review the field of collisionless numerical simulations for the large-scale structure of the Universe. We start by providing the main set of equations solved by these simulations and their connection with General Relativity. We then recap the relevant numerical approaches: discretization of the phase-space distribution (focusing on N-body but including alternatives, e.g., Lagrangian submanifold and Schrödinger–Poisson) and the respective techniques for their time evolution and force calculation (direct summation, mesh techniques, and hierarchical tree methods). We pay attention to the creation of initial conditions and the connection with Lagrangian Perturbation Theory. We then discuss the possible alternatives in terms of the micro-physical properties of dark matter (e.g., neutralinos, warm dark matter, QCD axions, Bose–Einstein condensates, and primordial black holes), and extensions to account for multiple fluids (baryons and neutrinos), primordial non-Gaussianity and modified gravity. We continue by discussing challenges involved in achieving highly accurate predictions. A key aspect of cosmological simulations is the connection to cosmological observables, we discuss various techniques in this regard: structure finding, galaxy formation and baryonic modelling, the creation of emulators and light-cones, and the role of machine learning. We finalise with a recount of state-of-the-art large-scale simulations and conclude with an outlook for the next decade.

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Section: Baryonsmentioning

confidence: 99%

Large-scale dark matter simulations

Angulo

Hahn

2022

Living Rev Comput Astrophys

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111

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“…(2.3) below). Other types of perturbations involve higher-than-second-order derivatives of the gravitational potential, for example O = ∇ 2 δ m (x, z) [19][20][21]; primordial gravitational potential perturbations O = φ(x) in case of primordial non-Gaussianity [22][23][24][25][26][27]; relative baryon-CDM density and velocity perturbations [28][29][30][31]; and perturbations of the ionizing radiation field in the Universe [32,33]. The vast majority of bias studies are done using gravity-only simulations and focus on the bias of dark matter halos.…”

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confidence: 99%

Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Barreira,

Lazeyras,

Schmidt

2021

Preprint

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We use field-level forward models of galaxy clustering and the EFT likelihood formalism to study, for the first time for self-consistently simulated galaxies, the relations between the linear b 1 and second-order bias parameters b 2 and b K 2 . The forward models utilize all of the information available in the galaxy distribution up to a given order in perturbation theory, which allows us to infer these bias parameters with high signal-to-noise, even from relatively small volumes (L box = 205Mpc/h). We consider galaxies from the IllustrisTNG simulations, and our main result is that the b 2 (b 1 ) and b K 2 (b 1 ) relations obtained from gravity-only simulations for total mass selected objects are broadly preserved for simulated galaxies selected by stellar mass, star formation rate, color and black hole accretion rate. This consistency under different galaxy selection criteria suggests that theoretical priors on these bias relations may be used to improve cosmological constraints based on observed galaxy samples. We do identify some small differences between the bias relations in the hydrodynamical and gravity-only simulations, which we show can be linked to the environmental dependence of the relation between galaxy properties and mass. We also show that the EFT likelihood recovers the value of σ 8 to percent-level from various galaxy samples (including splits by color and star formation rate) and after marginalizing over 8 bias parameters. This demonstration using simulated galaxies adds to previous works based on halos as tracers, and strengthens further the potential of forward models to infer cosmology from galaxy data.

show abstract

Section: Baryonsmentioning

confidence: 99%

Large-scale dark matter simulations

Angulo,

Hahn

2021

Preprint

Self Cite

View full text Add to dashboard Cite

We review the field of collisionless numerical simulations for the large-scale structure of the Universe. We start by providing the main set of equations solved by these simulations and their connection with General Relativity. We then recap the relevant numerical approaches: discretization of the phase-space distribution (focusing on N -body but including alternatives, e.g., Lagrangian submanifold and Schrödinger-Poisson) and the respective techniques for their time evolution and force calculation (Direct summation, mesh techniques, and hierarchical tree methods). We pay attention to the creation of initial conditions and the connection with Lagrangian Perturbation Theory. We then discuss the possible alternatives in terms of the micro-physical properties of dark matter (e.g., neutralinos, warm dark matter, QCD axions, Bose-Einstein condensates, and primordial black holes), and extensions to account for multiple fluids (baryons and neutrinos), primordial non-Gaussianity and modified gravity. We continue by discussing challenges involved in achieving highly accurate predictions. A key aspect of cosmological simulations is the connection to cosmological observables, we discuss various techniques in this regard: structure finding, galaxy formation and baryonic modelling, the creation of emulators and light-cones, and the role of machine learning. We finalise with a recount of state-of-the-art large-scale simulations and conclude with an outlook for the next decade.

show abstract

Quantifying the impact of baryon-CDM perturbations on halo clustering and baryon fraction

Cited by 13 publications

References 60 publications

Large-scale dark matter simulations

Large-scale dark matter simulations

Galaxy bias from forward models: linear and second-order bias of IllustrisTNG galaxies

Large-scale dark matter simulations

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