Selection bias in dynamically-measured supermassive black hole samples: Scaling relations and correlations between residuals in semi-analytic galaxy formation models - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Monthly Notices of the Royal Astronomical Society Année : 2017

Selection bias in dynamically-measured supermassive black hole samples: Scaling relations and correlations between residuals in semi-analytic galaxy formation models

Francesco Shankar
Mariangela Bernardi
  • Fonction : Auteur
Yohan Dubois
Ravi K. Sheth
  • Fonction : Auteur

Résumé

Recent work has confirmed that the scaling relations between the masses of supermassive black holes and host-galaxy properties such as stellar masses and velocity dispersions may be biased high. Much of this may be caused by the requirement that the black hole sphere of influence must be resolved for the black hole mass to be reliably estimated. We revisit this issue with a comprehensive galaxy evolution semi-analytic model. Once tuned to reproduce the (mean) correlation of black hole mass with velocity dispersion, the model cannot account for the correlation with stellar mass. This is independent of the model's parameters, thus suggesting an internal inconsistency in the data. The predicted distributions, especially at the low-mass end, are also much broader than observed. However, if selection effects are included, the model's predictions tend to align with the observations. We also demonstrate that the correlations between the residuals of the scaling relations are more effective than the relations themselves at constraining models for the feedback of active galactic nuclei (AGNs). In fact, we find that our model, while in apparent broad agreement with the scaling relations when accounting for selection biases, yields very weak correlations between their residuals at fixed stellar mass, in stark contrast with observations. This problem persists when changing the AGN feedback strength, and is also present in the hydrodynamic cosmological simulation Horizon-AGN, which includes state-of-the-art treatments of AGN feedback. This suggests that current AGN feedback models are too weak or simply not capturing the effect of the black hole on the stellar velocity dispersion.

Dates et versions

hal-01555149 , version 1 (03-07-2017)

Identifiants

Citer

Enrico Barausse, Francesco Shankar, Mariangela Bernardi, Yohan Dubois, Ravi K. Sheth. Selection bias in dynamically-measured supermassive black hole samples: Scaling relations and correlations between residuals in semi-analytic galaxy formation models. Monthly Notices of the Royal Astronomical Society, 2017, 468 (4), pp.4782-4791. ⟨10.1093/mnras/stx799⟩. ⟨hal-01555149⟩
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