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Register a new userModelling the large scale structure of the Universe as a function of cosmology and baryonic physics
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We present and test a framework that models the three-dimensional distribution of mass in the Universe as a function of cosmological and astrophysical parameters. Our approach combines two different techniques: a rescaling algorithm that modifies the cosmology of gravity-only N-body simulations, and a baryonification algorithm which mimics the effects of astrophysical processes induced by baryons, such as star formation and AGN feedback. We show how this approach can accurately reproduce the effects of baryons on the matter power spectrum of various state-of-the-art hydro-dynamical simulations (EAGLE, Illustris, Illustris-TNG, Horizon-AGN, and OWLS,Cosmo-OWLS and BAHAMAS), to percent level from very large down to small, highly nonlinear scales, k= 5 h/Mpc, and from z=0 up to z=2. We highlight that, thanks to the heavy optimisation of the algorithms, we can obtain these predictions for arbitrary baryonic models and cosmology (including massive neutrinos and dynamical dark energy models) with an almost negligible CPU cost. Therefore, this approach is efficient enough for cosmological data analyses. With these tools in hand we explore the degeneracies between cosmological and astrophysical parameters in the nonlinear mass power spectrum. Our findings suggest that after marginalising over baryonic physics, cosmological constraints inferred from weak gravitational lensing should be moderately degraded.
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Observational cosmology in the next decade will rely on probes of the distribution of matter in the redshift range between $0<z<3$ to elucidate the nature of dark matter and dark energy. In this redshift range, galaxy formation is known to have a significant impact on observables such as two-point correlations of galaxy shapes and positions, altering their amplitude and scale dependence beyond the expected statistical uncertainty of upcoming experiments at separations under 10 Mpc. Successful extraction of information in such a regime thus requires, at the very least, unbiased models for the impact of galaxy formation on the matter distribution, and can benefit from complementary observational priors. This work reviews the current state of the art in the modelling of baryons for cosmology, from numerical methods to approximate analytical prescriptions, and makes recommendations for studies in the next decade, including a discussion of potential probe combinations that can help constrain the role of baryons in cosmological studies. We focus, in particular, on the modelling of the matter power spectrum, $P(k,z)$, as a function of scale and redshift, and of the observables derived from this quantity. This work is the result of a workshop held at the University of Oxford in November of 2018.
We present a new method to identify large scale filaments and apply it to a cosmological simulation. Using positions of haloes above a given mass as node tracers, we look for filaments between them using the positions and masses of all the remaining dark-matter haloes. In order to detect a filament, the first step consists in the construction of a backbone linking two nodes, which is given by a skeleton-like path connecting the highest local dark matter (DM) density traced by non-node haloes. The filament quality is defined by a density and gap parameters characterising its skeleton, and filament members are selected by their binding energy in the plane perpendicular to the filament. This membership condition is associated to characteristic orbital times; however if one assumes a fixed orbital timescale for all the filaments, the resulting filament properties show only marginal changes, indicating that the use of dynamical information is not critical for the method. We test the method in the simulation using massive haloes($M>10^{14}$h$^{-1}M_{odot}$) as filament nodes. The main properties of the resulting high-quality filaments (which corresponds to $simeq33%$ of the detected filaments) are, i) their lengths cover a wide range of values of up to $150 $h$^{-1}$Mpc, but are mostly concentrated below 50h$^{-1}$Mpc; ii) their distribution of thickness peaks at $d=3.0$h$^{-1}$Mpc and increases slightly with the filament length; iii) their nodes are connected on average to $1.87pm0.18$ filaments for $simeq 10^{14.1}M_{odot}$ nodes; this number increases with the node mass to $simeq 2.49pm0.28$ filaments for $simeq 10^{14.9}M_{odot}$ nodes.
A short overview is given on the development of our present paradigm of the large scale structure of the Universe with emphasis on the role of Ya. B. Zeldovich. Next we use the Sloan Digital Sky Survey data and show that the distribution of phases of density waves of various scale in the present-day Universe are correlated. Using numerical simulations of structure evolution we show that the skeleton of the cosmic web was present already in an early stage of the evolution of structure. The positions of maxima and minima of density waves (their phases) are the more stable, the larger is the wavelength. The birth of the first generation of stars occured most probably in the central regions of rich proto-superclusters where the density was highest in the early Universe.
In order to infer the impact of the small-scale physics to the large-scale properties of the universe, we use a series of cosmological $N$-body simulations of self-gravitating matter inhomogeneities to measure, for the first time, the response function of such a system defined as a functional derivative of the nonlinear power spectrum with respect to its linear counterpart. Its measured shape and amplitude are found to be in good agreement with perturbation theory predictions except for the coupling from small to large-scale perturbations. The latter is found to be significantly damped, following a Lorentzian form. These results shed light on validity regime of perturbation theory calculations giving a useful guideline for regularization of small scale effects in analytical modeling. Most importantly our result indicates that the statistical properties of the large-scale structure of the universe are remarkably insensitive to the details of the small-scale physics, astrophysical or gravitational, paving the way for the derivation of robust estimates of theoretical uncertainties on the determination of cosmological parameters from large-scale survey observations.
We present the BACCO project, a simulation framework specially designed to provide highly-accurate predictions for the distribution of mass, galaxies, and gas as a function of cosmological parameters. In this paper, we describe our main suite of simulations (L $sim2$ Gpc and $4320^3$ particles) and present various validation tests. Using a cosmology-rescaling technique, we predict the nonlinear mass power spectrum over the redshift range $0<z<1.5$ and over scales $10^{-2} < k/(h Mpc^{-1} ) < 5$ for 800 points in an 8-dimensional cosmological parameter space. For an efficient interpolation of the results, we build an emulator and compare its predictions against several widely-used methods. Over the whole range of scales considered, we expect our predictions to be accurate at the 2% level for parameters in the minimal $Lambda$ CDM model and to 3% when extended to dynamical dark energy and massive neutrinos. We make our emulator publicly available under http://www.dipc.org/bacco
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