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1. NOEMA redshift measurements of bright Herschel galaxies

   https://doi.org/10.1051/0004-6361/201936988  

   Neri, R.; Cox, P.; Omont, A.; Beelen, A.; Berta, S.; Bakx, T.; Lehnert, M.; Baker, A. J.; Buat, V.; Cooray, A.; et al (March 2020, Astronomy & Astrophysics)

   Using the IRAM NOrthern Extended Millimeter Array (NOEMA), we conducted a program to measure redshifts for 13 bright galaxies detected in the Herschel Astrophysical Large Area Survey with S 500  μ m  ≥ 80 mJy. We report reliable spectroscopic redshifts for 12 individual sources, which are derived from scans of the 3 and 2 mm bands, covering up to 31 GHz in each band, and are based on the detection of at least two emission lines. The spectroscopic redshifts are in the range 2.08 <   z  <  4.05 with a median value of z  = 2.9 ± 0.6. The sources are unresolved or barely resolved on scales of 10 kpc. In one field, two galaxies with different redshifts were detected. In two cases the sources are found to be binary galaxies with projected distances of ∼140 kpc. The linewidths of the sources are large, with a mean value for the full width at half maximum of 700 ± 300 km s −1 and a median of 800 km s −1 . We analyze the nature of the sources with currently available ancillary data to determine if they are lensed or hyper-luminous ( L FIR  >  10 13   L ⊙ ) galaxies. We also present a reanalysis of the spectral energy distributions including the continuum flux densities measured at 3 and 2 mm to derive the overall properties of the sources. Future prospects based on these efficient measurements of redshifts of high- z galaxies using NOEMA are outlined, including a comprehensive survey of all the brightest Herschel galaxies. 

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2. Evidence of Environmental Quenching at Redshift z ≈ 2

   https://doi.org/10.3847/1538-4357/aacc2c  

   Ji, Zhiyuan; Giavalisco, Mauro; Williams, Christina C.; Faber, Sandra M.; Ferguson, Henry C.; Guo, Yicheng; Liu, Teng; Lee, Bomee (August 2018, The Astrophysical Journal)
3. The Properties of GRB 120923A at a Spectroscopic Redshift of z ≈ 7.8

   https://doi.org/10.3847/1538-4357/aadba9  

   Tanvir, N. R.; Laskar, T.; Levan, A. J.; Perley, D. A.; Zabl, J.; Fynbo, J. P.; Rhoads, J.; Cenko, S. B.; Greiner, J.; Wiersema, K.; et al (October 2018, The Astrophysical Journal)
4. Complex Ly α Profiles in Redshift 6.6 Ultraluminous Ly α Emitters

   https://doi.org/10.3847/1538-4357/aac021  

   Songaila, A.; Hu, E. M.; Barger, A. J.; Cowie, L. L.; Hasinger, G.; Rosenwasser, B.; Waters, C. (June 2018, The Astrophysical Journal)
5. Paving the way for Euclid and JWST via probabilistic selection of high-redshift quasars

   https://doi.org/10.1093/mnras/stac1944  

   Nanni, Riccardo; Hennawi, Joseph F; Wang, Feige; Yang, Jinyi; Schindler, Jan-Torge; Fan, Xiaohui (August 2022, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We introduce a probabilistic approach to select 6 ≤ $$z$$ ≤ 8 quasar candidates for spectroscopic follow-up, which is based on density estimation in the high-dimensional space inhabited by the optical and near-infrared photometry. Densities are modelled as Gaussian mixtures with principled accounting of errors using the extreme deconvolution (XD) technique, generalizing an approach successfully used to select lower redshift ($$z$$ ≤ 3) quasars. We train the probability density of contaminants on 1902 071 7-d flux measurements from the 1076 deg2 overlapping area from the Dark Energy Camera Legacy Survey (DECaLS) ($$z$$), VIKING (YJHKs), and unWISE (W1W2) imaging surveys, after requiring they dropout of DECaLS g and r, whereas the distribution of high-$$z$$ quasars are trained on synthetic model photometry. Extensive simulations based on these density distributions and current estimates of the quasar luminosity function indicate that this method achieves a completeness of $$\ge 56{{\ \rm per\ cent}}$$ and an efficiency of $$\ge 5{{\ \rm per\ cent}}$$ for selecting quasars at 6 < $$z$$ < 8 with JAB < 21.5. Among the classified sources are 8 known 6 < $$z$$ < 7 quasars, of which 2/8 are selected suggesting a completeness $$\simeq 25{{\ \rm per\ cent}}$$, whereas classifying the 6 known (JAB < 21.5) quasars at $$z$$ > 7 from the entire sky, we select 5/6 or a completeness of $$\simeq 80{{\ \rm per\ cent}}$$. The failure to select the majority of 6 < $$z$$ < 7 quasars arises because our quasar density model is based on an empirical quasar spectral energy distribution model that underestimates the scatter in the distribution of fluxes. This new approach to quasar selection paves the way for efficient spectroscopic follow-up of Euclid quasar candidates with ground-based telescopes and James Webb Space Telescope. 

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