Investigating the galaxy–halo connection of DESI emission-line galaxies with SHAMe-SF

Context. The Dark Energy Spectroscopic Instrument (DESI) survey is mapping the large-scale distribution of millions of emission line galaxies (ELGs) over vast cosmic volumes to measure the growth history of the Universe. However, compared to luminous red galaxies, it is more complex to model the connection of ELGs with the underlying matter field. Aims. We employed a novel theoretical model, SHAMe-SF, to infer the connection between ELGs and their host dark matter haloes and subhaloes. SHAMe-SF is a version of subhalo abundance matching that incorporates prescriptions for multiple processes, including star formation, tidal stripping, environmental correlations, and quenching. Methods. We analysed public measurements of the projected and redshift-space ELG correlation functions at z = 1.0 and z = 1.3 from the DESI One Percent data release (from the Early Data Release), which we fitted over a broad range of scales, r ∈ [0.1, 30]/h−1 Mpc, to within the statistical uncertainties of the data. We also validated the inference pipeline using two mock DESI-ELG catalogues built from hydrodynamic (TNG300) and semi-analytic galaxy formation models (<ns0:monospace>L-Galaxies</ns0:monospace>). Results. SHAMe-SF is able to reproduce the clustering of DESI ELGs and the mock DESI samples within statistical uncertainties. We infer that DESI ELGs typically reside in haloes of ∼ 1011.8 h−1 M⊙ when they are centrals and ∼ 1012.5 h−1 M⊙ when they are satellites, which occurs in ∼30% of cases. In addition, compared to the distribution of dark matter within haloes, satellite ELGs preferentially reside both in the outskirts and inside haloes, and have a net infall velocity towards the centre. Finally, our results show evidence of assembly bias and conformity. All these findings are in qualitative agreement with the mock DESI catalogues. Conclusions. These results pave the way for a cosmological interpretation of DESI ELG measurements on small scales using SHAMe-SF.