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Abstract:

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 of the total matter power spectrum from the Horizon cosmological hydrodynamical simulations: a dark matter-only run, one with full baryonic physics, and another lacking Active Galactic Nuclei (AGN) feedback. Baryons cause a suppression of power at $k\simeq 10$ $h/$Mpc of $<15\%$ at $z=0$, and an enhancement of a factor of a few at smaller scales due to the more efficient cooling and star formation. The results are sensitive to the presence of the highest mass haloes in the simulation and the distribution of dark matter is also impacted up to a few percent. The redshift evolution of the effect is non-monotonic throughout $z=0-5$ due to an interplay between AGN feedback and gas pressure, and the growth of structure. We investigate the effectiveness of the "baryonic correction model" proposed by Schneider & Teyssier (2015) in describing our results. We require a different redshift evolution and propose an alternative fitting function with $4$ free parameters that reproduces our results within $5\%$. Compared to other simulations, we find the impact of baryonic processes on the total matter power spectrum to be smaller at $z=0$. Nevertheless, our results also suggest that AGN feedback is not strong enough in the simulation. Total matter power spectra from the Horizon simulations are made publicly available at https://www.horizon-simulation.org/catalogues.html.

Abstract:

Accurate models of radiative cooling are a fundamental ingredient of modern cosmological simulations. Without cooling, accreted baryons will not efficiently dissipate their energy and collapse to the centres of haloes to form stars. It is well established that local variations in the amplitude and shape of the spectral energy distribution of the radiation field can drastically alter the cooling rate. Here we introduce deepCool, deepHeat, and deepMetal: methods for accurately modelling the total cooling rates, total heating rates, and metal-line only cooling rates of irradiated gas using artificial neural networks. We train our algorithm on a high-resolution cosmological radiation hydrodynamics simulation and demonstrate that we can predict the cooling rate, as measured with the photoionisation code CLOUDY, under the influence of a local radiation field, to an accuracy of ~5%. Our method is computationally and memory efficient, making it suitable for deployment in state-of-the-art radiation hydrodynamics simulations. We show that the circumgalactic medium and diffuse gas surrounding the central regions of a galaxy are most affected by the interplay of radiation and gas, and that standard cooling functions that ignore the local radiation field can incorrectly predict the cooling rate by more than an order of magnitude, indicating that the baryon cycle in galaxies is affected by the influence of a local radiation field on the cooling rate.