Aging haloes: implications of the magnitude gap on conditional statistics of stellar and gas properties of massive haloes

Abstract

Cold dark matter model predicts that the large-scale structure grows hierarchically. Small dark matter halos form first. Then, they grow gradually via continuous merger and accretion. These halos host the majority of baryonic matter in the Universe in the form of hot gas and cold stellar phase. Determining how baryons are partitioned into these phases requires detailed modeling of galaxy formation and their assembly history. It is speculated that formation time of the same mass halos might be correlated with their baryonic content. To evaluate this hypothesis, we employ halos of mass above 10 14 M realized by TNG300 solution of the IllustrisTNG project. Formation time is not directly observable. Hence, we rely on the magnitude gap between the brightest and the fourth brightest halo galaxy member, which is shown that traces formation time of the host halo. We compute the conditional statistics of the stellar and gas content of halos conditioned on their total mass and magnitude gap. We find a strong correlation between magnitude gap and gas mass, BCG stellar mass, and satellite galaxies stellar mass, but not the total stellar mass of halo. Conditioning on the magnitude gap can reduce the scatter about halo property-halo mass relation and has a significant impact on the conditional covariance. Reduction in the scatter can be as significant as 30%, which implies more accurate halo mass prediction. Incorporating the magnitude gap has a potential to improve cosmological constraints using halo abundance and allows us to gain insight into the baryon evolution within these systems.

HSC-XXL : Baryon budget of the 136 XXL Groups and Clusters

“…We use the results being as close as possible to our median redshift and consider the redshift dependence of p(Z, z). The gas mass slopes of numerical simulations (Young et al 2011;Planelles et al 2013;Barnes et al 2017b;Wu et al 2015;Truong et al 2018;Farahi et al 2018a;Henden et al 2020;Farahi et al 2020) are higher than predicted by the self-similar model (β = 1). Some simulations are slightly steeper than the self-similar expectation (1 < βg < 1.1) while others have a clear higher slope (βg > ∼ 1.2).…”

“…Recent cosmological hydrodynamic simulations (e.g. Young et al 2011;McCarthy et al 2011;Planelles et al 2013;Martizzi et al 2014;Le Brun et al 2014;Wu et al 2015;Sembolini et al 2016a;McCarthy et al 2017;Barnes et al 2017b;Farahi et al 2018a;Henden et al 2020;Farahi et al 2020) studied stellar mass and gas distributions in clusters and/or groups. The simulations include the effect of cooling, AGN feedback, star formation, and SN feedback and compare them with the results of non-radiative simulations.…”

“…The slopes of some numerical simulations depend on the halo mass. For instance, Farahi et al (2020) showed that the slopes of the gas mass and stellar mass scaling relations at massive clusters (M500 ∼ 10 15 M ) are close to unity and becomes steeper and shallower with decreasing mass, respectively. We therefore estimate the average value and scatter with a weight of the resulting parent population p(Z,z) to fairly compare with their values in our mass range.…”

Do gas-poor galaxy clusters have different galaxy populations? The positive covariance of hot and cold baryons

“…Relying on simulations, richness, formation time and magnitude gap are related to each other. The number of satellite galaxies in a halo, which is closely related to the cluster richness, depending on the formation time (Farahi et al 2020), because satellites in early formed haloes had more time to merge and reduce their number. Moreover, the cannibalism of the central galaxy, grown by major mergers, produces the lack of bright satellite galaxies (Jones et al 2003;Giodini et al 2013) and consequently increases the magnitude gap between the first and the second BCG, which should therefore be indicative of the formation time.…”

“…A larger scatter in such relations produces larger errors in the cosmological parameters estimates (Lima & Hu 2005). The scatter can be due to the measurement errors of the involved quantities, but there is also ★ E-mail: emanuella.puddu@inaf.it an intrinsic component that reflects the variegated properties of the examined clusters sample (Andreon et al 2017); such properties are related to the formation and evolution scenarios (Hartley et al 2008;Fujita et al 2018) and to the underlying physical processes taking place into clusters (Farahi et al 2020). Understanding the nature of the intrinsic component could contribute having a more deep insight into these processes (for example AGN feedback, star formation, mergers, radiative cooling and other non-gravitational effects; e.g.…”