JADES Dark Horse: demonstrating high-multiplex observations with JWST/NIRSpec dense-shutter spectroscopy in the JADES Origins Field

Abstract

We present JWST/NIRSpec dense-shutter spectroscopy (DSS). This novel observing strategy with the NIRSpec/MSA deliberately permits a high number of controlled spectral overlaps to reach extreme multiplex while retaining the low background of slit spectroscopy. In a single configuration over the JADES Origins Field, we opened shutters on all faint (mF444W$<$30 mag) z${}_{\mathrm{phot}}>$3 candidates, prioritising emission-line science and rejecting only bright continuum sources. Using 33.6 and 35.8 ks on-source in G235M and G395M, we observed a single mask with $\sim$850 sources, obtaining spectroscopic redshifts for $\sim$540 galaxies over 2.5$<$z$<$8.9. The per-configuration target density in DSS mode is 4-5x higher than standard no- and low-overlap MSA strategies ($<$200 sources), with no loss in redshift precision or accuracy. Line-flux sensitivities are 30 percent lower at fixed exposure time, matching the expected increase in background noise, but the gain in survey speed is 5x in our setup, more than justifying the penalty. The measured line sensitivity exceeds NIRCam/WFSS by at least $\sim$5x ($\sim$25x in exposure time) at $\lambda \sim 4\mu$m, demonstrating that DSS is a compelling method to gain deep, wide-band spectra for large samples. Crucially, NIRSpec/MSA could deliver even higher target allocation densities than those used here. We derive H$\alpha$-based SFRs, gas-phase metallicities (including a large sample suitable for strong-line calibrations), and identify rare mini-quenched galaxies and broadline AGN. DSS is immediately applicable wherever deep imaging enables robust pre-selection and astrometry, providing an efficient method to obtain large samples of faint emission-line galaxies, a compelling middle ground between the completeness of slitless surveys and the sensitivity and bandwidth of NIRSpec/MSA.

22 pages, 21 figures, 2 tables. Published in MNRAS

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