Understanding the non-linear clustering of high-redshift galaxies

Jose, C.; Baugh, C.M.; Lacey, C.G.; Subramanian, K.

Abstract

We incorporate the non-linear clustering of dark matter haloes, as modelled by Jose et al. into the halo model to better understand the clustering of Lyman break galaxies (LBGs) in the redshift range z = 3–5. We find that, with this change, the predicted LBG clustering increases significantly on quasi-linear scales (0.1 ≤ r / h−1 Mpc ≤ 10) compared to that in the linear halo bias model. This, in turn, results in an increase in the clustering of LBGs by an order of magnitude on angular scales 5 ≤ θ ≤ 100 arcsec. Remarkably, the predictions of our new model on the whole remove the systematic discrepancy between the linear halo bias predictions and the observations. The correlation length and large-scale galaxy bias of LBGs are found to be significantly higher in the non-linear halo bias model than in the linear halo bias model. The resulting two-point correlation function retains an approximate power-law form in contrast with that computed using the linear halo bias theory. We also find that the non-linear clustering of LBGs increases with increasing luminosity and redshift. Our work emphasizes the importance of using non-linear halo bias in order to model the clustering of high-z galaxies to probe the physics of galaxy formation and extract cosmological parameters reliably.

Citation

Jose, C., Baugh, C., Lacey, C., & Subramanian, K. (2017). Understanding the non-linear clustering of high-redshift galaxies. Monthly Notices of the Royal Astronomical Society, 469(4), 4428-4436. https://doi.org/10.1093/mnras/stx1014

• Journal Article Type: Article
• Acceptance Date: Apr 25, 2017
• Online Publication Date: Apr 27, 2017
• Publication Date: Apr 27, 2017
• Deposit Date: Jul 18, 2017
• Publicly Available Date: Jul 18, 2017
• Journal: Monthly Notices of the Royal Astronomical Society
• Print ISSN: 0035-8711
• Electronic ISSN: 1365-2966
• Publisher: Royal Astronomical Society
• Peer Reviewed: Peer Reviewed
• Volume: 469
• Issue: 4
• Pages: 4428-4436
• DOI: https://doi.org/10.1093/mnras/stx1014
• Public URL: https://durham-repository.worktribe.com/output/1373810