High Equivalent Width of Hα+[N II] Emission in z~8 Lyman-break Galaxies from IRAC 5.8μm Observations: Evidence for Efficient Lyman-continuum Photon production in the Epoch of Re-ionization (2204.02986v1)
Abstract: We measure, for the first time, the median equivalent width (EW) of H$\alpha$+[N II] in star-forming galaxies at $z\sim8$. Our estimate leverages the unique photometric depth of the Spitzer/IRAC $5.8\mu$m-band mosaics (probing $\approx 5500 - 7100$ A at $z\sim8$) of the GOODS Reionization Era Wide Area Treasury from Spitzer (GREATS) program. We median stacked the stamps of $102$ Lyman-break galaxies in the $3.6, 4.5, 5.8$ and $8.0\mu$m bands, after carefully removing potential contamination from neighbouring sources. We infer an extreme rest-frame EW$0$(H$\alpha$+[N II])$=2328{+1326}{-1127}$ A from the measured red $[3.6]-[5.8]=0.82\pm0.27$ mag, consistent with young ($\lesssim107$ yr) average stellar population ages at $z\sim8$. This implies an ionizing photon production efficiency of $\log(\xi_{\mathrm{ion},0}/\mathrm{erg\ Hz}{-1})=25.97{+0.18}_{-0.28}$. Such a high value for photo production, similar to the highest values found at $z\lesssim4$, indicates that only modest escape fractions $f_\mathrm{esc}\lesssim0.3$ (at $2\sigma$) are sufficient for galaxies brighter than $M_\mathrm{UV}<-18$ mag to re-ionize the neutral Hydrogen at $z\sim8$. This requirement is relaxed even more to $f_\mathrm{esc}\le 0.1$ when considering galaxies brighter than $M_\mathrm{UV}\approx -13$ mag, consistent with recent luminosity functions and as typically assumed in studies addressing re-ionization. These exceptional results clearly indicate that galaxies can be the dominant source of reionizing photons, and provide us with an exciting glimpse into what we might soon learn about the early universe, and particularly about the Reionization Epoch, from forthcoming JWST/MIRI and NIRCam programs.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.