Resolving the problem of galaxy clustering on small scales: any new physics needed?

• Published in: Monthly notices of the Royal Astronomical Society 2014-02, Vol.437 (4), p.3385-3395
• Main Author: Kang, X.
• Format: Article
• Language: English
• Subjects: Astrophysics; Comparative analysis; Dark matter; Star & galaxy formation; Supernovae
• ISSN: 0035-8711; 1365-2966
• DOI: 10.1093/mnras/stt2132

Galaxy clustering sets strong constraints on the physics governing galaxy formation and evolution. However, most current models fail to reproduce the clustering of low-mass galaxies on small scales (r < 1 Mpc h −1). In this paper, we study the galaxy clusterings predicted from a few semi-analytical models. We first compare two Munich versions, Guo et al. and De Lucia & Blaizot. The Guo11 model well reproduces the galaxy stellar mass function, but overpredicts the clustering of low-mass galaxies on small scales. The DLB07 model provides a better fit to the clustering on small scales, but overpredicts the stellar mass function. These seem to be puzzling. The clustering on small scales is dominated by galaxies in the same dark matter halo, and there is slightly more fraction of satellite galaxies residing in massive haloes in the Guo11 model, which is the dominant contribution to the clustering discrepancy between the two models. However, both models still overpredict the clustering at 0.1 < r < 10 Mpc h −1 for low-mass galaxies. This is because both models overpredict the number of satellites by 30 per cent in massive haloes than the data. We show that the Guo11 model could be slightly modified to simultaneously fit the stellar mass function and clusterings, but that cannot be easily achieved in the DLB07 model. The better agreement of DLB07 model with the data actually comes as a coincidence as it predicts too many low-mass central galaxies which are less clustered and thus brings down the total clustering. Finally, we show the predictions from the semi-analytical models of Kang et al. We find that this model can simultaneously fit the stellar mass function and galaxy clustering if the supernova feedback in satellite galaxies is stronger. We conclude that semi-analytical models are now able to solve the small-scales clustering problem, without invoking of any other new physics or changing the dark matter properties, such as the recent favoured warm dark matter.