Galaxy clustering dependence on the $\left[\mathrm{O\scriptsize{II}}\right]$ emission line luminosity in the local Universe

TL;DR

This study investigates how galaxy clustering in the local universe depends on [OII] emission line luminosity, using SDSS data and cosmological simulations to model and interpret the relationship.

Contribution

It introduces a modified (Sub)Halo Abundance Matching scheme that accounts for stellar mass incompleteness and satellite fraction, improving clustering predictions for emission line galaxies.

Findings

[OII] luminosity correlates with galaxy clustering and bias.

Clustering strength is more strongly linked to r-band magnitude than [OII] luminosity.

The method reliably predicts host halo masses and satellite fractions for emission line galaxies.

Abstract

We study the galaxy clustering dependence on the $\left[\mathrm{O\scriptsize{II}}\right]$ emission line luminosity in the SDSS DR7 Main galaxy sample at mean redshift $z\sim0.1$. We select volume-limited samples of galaxies with different $\left[\mathrm{O\scriptsize{II}}\right]$ luminosity thresholds and measure their projected, monopole and quadrupole two-point correlation functions. We model these observations using the 1$h^{-1}\rm{Gpc}$ MultiDark Planck cosmological simulation and generate light-cones with the SUrvey GenerAtoR algorithm. To interpret our results, we adopt a modified (Sub)Halo Abundance Matching scheme, accounting for the stellar mass incompleteness of the emission line galaxies. The satellite fraction constitutes an extra parameter in this model and allows to optimize the clustering fit on both small and intermediate scales (i.e. $r_p\lesssim 30h^{-1}\rm{Mpc})$, with no need of any velocity bias correction. We find that, in the local Universe, the $\left[\mathrm{O\scriptsize{II}}\right]$ luminosity correlates with all the clustering statistics explored and with the galaxy bias. This latter quantity correlates more strongly with the SDSS $r$-band magnitude than $\left[\mathrm{O\scriptsize{II}}\right]$ luminosity. In conclusion, we propose a straightforward method to produce reliable clustering models, entirely built on the simulation products, which provides robust predictions of the typical ELG host halo masses and satellite fraction values. The SDSS galaxy data, MultiDark mock catalogues and clustering results are made publicly available.