相关论文: Hybrid analytic and machine-learned baryonic prope…

We train a novel deep learning architecture to perform likelihood-free inference on the value of the cosmological parameters from halo catalogs of the Quijote N-body simulations. Our model takes as input a halo catalog where each halo is…

Baryonic processes such as radiative cooling and feedback from massive stars and active galactic nuclei (AGN) directly redistribute baryons in the Universe but also indirectly redistribute dark matter due to changes in the gravitational…

Cosmological hydrodynamical simulations are studied in order to analyse generic trends for the stellar, baryonic and halo mass assembly of low-mass galaxies (M_* < 3 x 10^10 M_sun) as a function of their present halo mass, in the context of…

Cosmological neutral hydrogen (HI) surveys provide a promising tomographic probe of the post-reionization era and of the standard model of cosmology. Simulations of this signal are crucial for maximizing the utility of these surveys. We…

Hydrodynamical cosmological simulations are increasing their level of realism by considering more physical processes and having greater resolution or larger statistics. However, usually either the statistical power of such simulations or…

Making robust predictions for the phase space distribution of dark matter at the solar neighbourhood is vital for dark matter direct detection experiments. To date, almost all such predictions have been based on simulations that model the…

In this series of papers we present an emulator-based halo model for the non-linear clustering of galaxies in modified gravity cosmologies. In the first paper, we present emulators for the following halo properties: the halo mass function,…

The non-spherical shapes of dark matter and gas distributions introduce systematic uncertainties that affect observable-mass relations and selection functions of galaxy groups and clusters. However, the triaxial gas distributions depend on…

We study the $z=0$ properties of clusters (and large groups) of galaxies within the context of interacting and non-interacting quintessence cosmological models, using a series of adiabatic SPH simulations. Initially, we examine the average…

The advent of large cosmological sky surveys - ushering in the era of precision cosmology - has been accompanied by ever larger cosmological simulations. The analysis of these simulations, which currently encompass tens of billions of…

We have developed a simple yet surprisingly accurate analytic scheme for tracking the dynamical evolution of substructure within larger dark halos. The scheme incorporates the effects of dynamical friction, tidal mass loss and tidal heating…

We extend our super-resolution and emulation framework for cosmological dark matter simulations to include hydrodynamics. We present a two-stage deep learning model to emulate high-resolution (HR-HydroSim) baryonic fields from…

Hydrodynamical simulations are the most accurate way to model structure formation in the universe, but they often involve a large number of astrophysical parameters modeling subgrid physics, in addition to cosmological parameters. This…

The formation of the disk and feedback from supernova winds impacts the distribution of dark matter in galaxies. Recently, Di Cintio et al. (2014b) characterized the halo response from baryonic processes in hydrodynamical simulations via a…

We perform an extensive analysis of nonlinear and stochastic biasing of galaxies and dark halos in spatially flat low-density CDM universe using cosmological hydrodynamic simulations. We compare their biasing properties with the predictions…

We present the results of a series of adiabatic hydrodynamical simulations of several quintessence models (both with a free and an interacting scalar field) in comparison to a standard \LCDM\ cosmology. For each we use $2\times1024^3$…

Accurate cosmology from upcoming weak lensing surveys relies on knowledge of the total matter power spectrum at percent level at scales $k < 10$ $h$/Mpc, for which modelling the impact of baryonic physics is crucial. We compare measurements…

Cosmological surveys aim at answering fundamental questions about our Universe, including the nature of dark matter or the reason of unexpected accelerated expansion of the Universe. In order to answer these questions, two important…

We present two promising applications of training machine learning models inside a differentiable astrophysical (magneto)hydrodynamics simulator. First, we address the problem of slow convergence in hydrodynamical simulations of wind-blown…

Generating pre-initial conditions (or particle loads) is the very first step to set up a cosmological N-body simulation. In this work, we revisit the numerical convergence of pre-initial conditions on dark matter halo properties using a set…