Neutral hydrogen in galaxy clusters: impact of AGN feedback and implications for intensity mapping

Abstract

By means of zoom-in hydrodynamic simulations we quantify the amount of neutral hydrogen (HI) hosted by groups and clusters of galaxies. Our simulations, which are based on an improved formulation of smoothed particle hydrodynamics (SPH), include radiative cooling, star formation, metal enrichment and supernova feedback, and can be split in two different groups, depending on whether feedback from active galactic nuclei (AGN) is turned on or off. Simulations are analyzed to account for HI self-shielding and the presence of molecular hydrogen. We find that the mass in neutral hydrogen of dark matter halos monotonically increases with the halo mass and can be well described by a power-law of the form M HI (M, z) ∝ M 3/4 . Our results point out that AGN feedback reduces both the total halo mass and its HI mass, although it is more efficient in removing HI. We conclude that AGN feedback reduces the neutral hydrogen mass of a given halo by ∼ 50%, with a weak dependence on halo mass and redshift. The spatial distribution of neutral hydrogen within halos is also affected by AGN feedback, whose effect is to decrease the fraction of HI that resides in the halo inner regions. By extrapolating our results to halos not resolved in our simulations we derive astrophysical implications from the measurements of Ω HI (z): halos with circular velocities larger than ∼ 25 km/s are needed to host HI in order to reproduce observations. We find that only the model with AGN feedback is capable of reproducing the value of Ω HI b HI derived from available 21cm intensity mapping observations.

The spatial distribution of neutral hydrogen as traced by low H i mass galaxies

“…The predicted H I (z) from the Kim15 model agrees well with observations up to z ∼ 2 without any assumption about the relationship between H I mass and dark matter halo mass as was assumed in Bagla et al (2010, see Kim et al 2015and Rhee et al 2016. The predicted H I mass increases monotonically with the halo mass above 10 12 h −1 M and can be well described by a power law which is consistent with the zoom-in hydrodynamic simulation predictions in Villaescusa-Navarro et al (2016). Villaescusa-Navarro et al (2016) only show this relation above M halo > 10 13 M because of the volume limit in their simulation.…”

“…The predicted H I mass increases monotonically with the halo mass above 10 12 h −1 M and can be well described by a power law which is consistent with the zoom-in hydrodynamic simulation predictions in Villaescusa-Navarro et al (2016). Villaescusa-Navarro et al (2016) only show this relation above M halo > 10 13 M because of the volume limit in their simulation. Equivalently, we can predict the intensity mapping signal using the power spectrum of the H I mass of galaxies which gives us information about the H I mass distribution from the model, with no assumptions about linear bias relative to the underlying dark matter distribution, P H I (k, z), Fig.…”

“…Each model includes a prescription for the relation between H I and dark matter halo masses. This results in the implicit assumption that the H I traces the underlying matter distribution with a linear bias (Bagla, Khandai & Datta 2010;Guha Sarkar et al 2012;Padmanabhan, Choudhury & Refregier 2015;Villaescusa-Navarro et al 2016). For example, Bagla et al (2010) propose phenomenological functions for this relation based on the observation that haloes much more massive than a few times 10 11 M do not host significant amounts of H I (Catinella et al 2013;Dénes, Kilborn & Koribalski 2014).…”

A scale-dependent bias on linear scales: the case for H i intensity mapping at z = 1

“…Even though it is widely accepted that HI is within galaxies at z < 5, today a simple relation between dark matter halo and HI masses (MHIMh) is used, with a certain gas profile when necessary (which is not for the bias). The MHIMh relation is measured in hydrodynamical simulations often assuming a simple power law (Davé et al 2013;Kim et al 2016;Villaescusa-Navarro et al 2016), inspired from observations (Bagla et al 2010) or parametrised and fitted on data (Barnes & Haehnelt 2010, 2014Padmanabhan et al 2016;. Lately, Padmanabhan & Kulkarni (2017) derived the MHIMh relation using the abundance matching technique where the halo mass function is matched to the HI mass function.…”

H i and cosmological constraints from intensity mapping, optical and CMB surveys

“…It is important to note that these measurements are key in order to discriminate between models of how to assign HI to the dark matter haloes MHI(M ). For example, the simulations of Villaescusa-Navarro et al (2016) show that AGN feedback reduces MHI and hence suppresses the whole curve, while (Padmanabhan & Refregier 2016) suggest a slope effect on the high mass end of the HI-halo mass relation. Repeating the above procedure for BINGO (one redshift bin with 0.12 < z < 0.48) we find δΩ HI Ω HI 0.02.…”