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Register a new userThe BACCO Simulation Project: Exploiting the full power of large-scale structure for cosmology
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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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We present a neural-network emulator for baryonic effects in the non-linear matter power spectrum. We calibrate this emulator using more than 50,000 measurements in a 15-dimensional parameters space, varying cosmology and baryonic physics. Baryonic physics is described through a baryonification algorithm, that has been shown to accurately capture the relevant effects on the power spectrum and bispectrum in state-of-the-art hydrodynamical simulations. Cosmological parameters are sampled using a cosmology-rescaling approach including massive neutrinos and dynamical dark energy. The specific quantity we emulate is the ratio between matter power spectrum with baryons and gravity-only, and we estimate the overall precision of the emulator to be 1-2%, at all scales 0.01 < k < 5 h/Mpc, and redshifts 0 < z < 1.5. We also obtain an accuracy of 1-2%, when testing the emulator against a collection of 74 different cosmological hydrodynamical simulations and their respective gravity-only counterparts. We show also that only one baryonic parameter, namely Mc, which set the gas fraction retained per halo mass, is enough to have accurate and realistic predictions of the baryonic feedback at a given epoch. Our emulator will become publicly available in http://www.dipc.org/bacco.
We present an emulator for the two-point clustering of biased tracers in real space. We construct this emulator using neural networks calibrated with more than $400$ cosmological models in a 8-dimensional cosmological parameter space that includes massive neutrinos an dynamical dark energy. The properties of biased tracers are described via a Lagrangian perturbative bias expansion which is advected to Eulerian space using the displacement field of numerical simulations. The cosmology-dependence is captured thanks to a cosmology-rescaling algorithm. We show that our emulator is capable of describing the power spectrum of galaxy formation simulations for a sample mimicking that of a typical Emission-Line survey at $z sim 1$ with an accuracy of $1-2%$ up to nonlinear scales $k sim 0.7 h mathrm{Mpc}^{-1}$.
Recent analyses of the cosmic microwave background (CMB) and the Lyman-alpha forest indicate a mild preference for a deviation from a power law primordial matter power spectrum (a so-called negative `running). We use an extension to the BAHAMAS suite of cosmological hydrodynamic simulations to explore the effects that a running scalar spectral index has on large-scale structure (LSS), using Planck CMB constraints to initialize the simulations. We focus on 5 key statistics: i) the non-linear matter power spectrum ii) the halo mass function; iii) the halo two-point auto correlation function; iv) total mass halo density profiles; and v) the halo concentration-mass relation. In terms of the matter power spectrum, we find that a running scalar spectral index affects all k-scales examined in this study, with a negative (positive) running leading to an amplification (suppression) of power. These effects should be easily detectable with upcoming surveys such as LSST and Euclid. In the mass range sampled, a positive running leads to an increase in the mass of galaxy groups and clusters, with the favoured negative running leading to a decrease in mass of lower-mass (M <~ 10^13 M_solar) halos, but an increase for the most massive (M >~ 10^13 M_solar) halos. Changes in the mass are generally confined to 5-10% which, while not insignificant, cannot by itself reconcile the claimed tension between the primary CMB and cluster number counts. We find that running does not significantly affect the shapes of density profiles of matched halos, changing only their amplitude. Finally, we demonstrate that the observed effects on LSS due to a running scalar spectral index are separable from those of baryonic effects to typically a few percent precision.
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.
Published galaxy power spectra from the 2dFGRS and SDSS are not in good agreement. We revisit this issue by analyzing both the 2dFGRS and SDSS DR5 catalogues using essentially identical techniques. We confirm that the 2dFGRS exhibits relatively more large scale power than the SDSS, or, equivalently, SDSS has more small scale power. We demonstrate that this difference is due to the r-band selected SDSS catalogue being dominated by more strongly clustered red galaxies, which have a stronger scale dependent bias. The power spectra of galaxies of the same rest frame colours from the two surveys match well. If not accounted for, the difference between the SDSS and 2dFGRS power spectra causes a bias in the obtained constraints on cosmological parameters which is larger than the uncertainty with which they are determined. We also found that the correction developed by Cole et al.(2005) to model the distortion in the shape of the power spectrum due to non-linear evolution and scale dependent bias is not able to reconcile the constraints obtained from the 2dFGRS and SDSS power spectra. Intriguingly, the model is able to describe the differences between the 2dFGRS and the much more strongly clustered LRG sample, which exhibits greater nonlinearities. This shows that more work is needed to understand the relation between the galaxy power spectrum and the linear perturbation theory prediction for the power spectrum of matter fluctuations. It is therefore important to accurately model these effects to get precise estimates of cosmological parameters from these power spectra and from future galaxy surveys like Pan-STARRS, or the Dark Energy Survey, which will use selection criteria similar to the one of SDSS.
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