Predicting emission line fluxes and number counts of distant galaxies for cosmological surveys

Abstract

We estimate the number counts of line emitters at high redshift and their evolution with cosmic time based on a combination of photometry and spectroscopy. We predict the H$\alpha$, H$\beta$, [OII], and [OIII] line fluxes for more than $35,000$ galaxies down to stellar masses of $\sim 10^9$ $M_{\odot }$ in the COSMOS and GOODS-S fields, applying standard conversions and exploiting the spectroscopic coverage of the FMOS-COSMOS survey at $z\sim 1.55$ to calibrate the predictions. We calculate the number counts of H$\alpha$, [OII], and [OIII] emitters down to fluxes of $1\times 10^{-17}$ erg cm${}^{-2}$ s${}^{-1}$ in the range $1.4<z<1.8$ covered by the FMOS-COSMOS survey. We model the time evolution of the differential and cumulative H$\alpha$ counts, steeply declining at the brightest fluxes. We expect $\sim 9,300-9,700$ and $\sim 2,300-2,900$ galaxies deg${}^{-2}$ for fluxes $\ge 1\times 10^{-16}$ and $\ge 2\times 10^{-16}$ erg cm${}^{-2}$ s${}^{-1}$ over the range $0.9<z<1.8$. We show that the observed evolution of the Main Sequence of galaxies with redshift is enough to reproduce the observed counts variation at $0.2<z<2.5$. We characterize the physical properties of the H$\alpha$ emitters with fluxes $\ge 2\times 10^{-16}$ erg cm${}^{-2}$ s${}^{-1}$, including their stellar masses, UV sizes, [NII]/H$\alpha$ ratios, and H$\alpha$ equivalent widths. An aperture of $R\sim R_{\mathrm{e}}\sim 0.5$" maximizes the signal-to-noise ratio for a detection, while causing a factor of $\sim 2\times$ flux losses, influencing the recoverable number counts, if neglected. Our approach, based on deep and large photometric datasets, reduces the uncertainties on the number counts due to the selection and spectroscopic samplings, while exploring low fluxes. We publicly release the line flux predictions for the explored photometric samples.

arXiv commentAccepted for publication in MNRAS. 21 pages (+9 pages of appendix), 18 Figures. Machine readable tables will be available online

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