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We present a Bayesian inference on the neutral hydrogen fraction of the intergalactic medium (IGM), x small HI, at z ∼6-8 using the properties of Lyman break galaxies (LBGs) during the epoch of reionization. We use large samples of LBG candidates at 5.5 ≤ z ≤ 8.2 with spectroscopy from Keck/DEIMOS and Keck/MOSFIRE. For each galaxy, we incorporate either the Lyman-α (Lyα) equivalent width (EW) for detections or the EW limit spectrum for non-detections to parametrize the EW distribution at various ultraviolet brightnesses for a given redshift. Using our reference sample of galaxy candidates from the ionized universe at z ∼6.0, we are able to infer x small HI at two redshifts: z ∼6.7 and z ∼7.6. This work includes intrinsically faint, gravitationally lensed galaxies at z ∼6.0 in order to constrain the intrinsic faint-end Lyα EW distribution and provide a comparable population of galaxies to counterparts in our sample that are at higher redshift. The inclusion of faint galaxy candidates, in addition to a more sophisticated modelling framework, allows us to better isolate effects of the interstellar medium and circumgalactic medium on the observed Lyα distribution from those of the IGM. We infer an upper limit of x small HI ≤ 0.25 (0.44) at z = 6.7 ± 0.2 and a neutral fraction of x small HI = 0.83+0.08 -0.11 (0.83 +0.11 -0.21) at z = 7.6 ± 0.6, both within 68 per cent (95 per cent) uncertainty, results that favour a moderately late and fairly rapid reionization.

PypeIt is a Python package for semi-automated reduction of astronomical,spectroscopic data. Its algorithms build on decades-long development ofprevious data reduction pipelines by the developers (Bernstein, Burles, &Prochaska, 2015; Bochanski et al., 2009). The reduction procedure -- includinga complete list of the input parameters and available functionality -- isprovided as online documentation hosted by Read the Docs, which is regularlyupdated. (https://pypeit.readthedocs.io/en/latest/). Release v1.0.3 serves thefollowing spectrographs: Gemini/GNIRS, Gemini/GMOS, Gemini/FLAMINGOS 2,Lick/Kast, Magellan/MagE, Magellan/Fire, MDM/OSMOS, Keck/DEIMOS (600ZD, 830G,1200G), Keck/LRIS, Keck/MOSFIRE (J and Y gratings tested), Keck/NIRES,Keck/NIRSPEC (low-dispersion), LBT/Luci-I, Luci-II, LBT/MODS (beta), NOT/ALFOSC(grism4), VLT/X-Shooter (VIS, NIR), VLT/FORS2 (300I, 300V), WHT/ISIS.

PypeIt is a Python package for semi-automated reduction of astronomical,spectroscopic data. Its algorithms build on decades-long development ofprevious data reduction pipelines by the developers (Bernstein, Burles, &Prochaska, 2015; Bochanski et al., 2009). The reduction procedure -- includinga complete list of the input parameters and available functionality -- isprovided as online documentation hosted by Read the Docs, which is regularlyupdated. (https://pypeit.readthedocs.io/en/latest/). Release v1.0.3 serves thefollowing spectrographs: Gemini/GNIRS, Gemini/GMOS, Gemini/FLAMINGOS 2,Lick/Kast, Magellan/MagE, Magellan/Fire, MDM/OSMOS, Keck/DEIMOS (600ZD, 830G,1200G), Keck/LRIS, Keck/MOSFIRE (J and Y gratings tested), Keck/NIRES,Keck/NIRSPEC (low-dispersion), LBT/Luci-I, Luci-II, LBT/MODS (beta), NOT/ALFOSC(grism4), VLT/X-Shooter (VIS, NIR), VLT/FORS2 (300I, 300V), WHT/ISIS.

Recent zoom-in cosmological simulations have shown that stellar feedback can flatten the inner density profile of the dark matter halo in low-mass galaxies. A correlation between the stellar/gas velocity dispersion (σ star, σ gas) and the specific star formation rate (sSFR) is predicted as an observational test of the role of stellar feedback in re-shaping the dark matter density profile. In this work we test the validity of this prediction by studying a sample of star-forming galaxies at 0.6 < z < 1.0 from the LEGA-C survey, which provides high signal-to-noise measurements of stellar and gas kinematics. We find that a weak but significant correlation between σ star (and σ gas) and sSFR indeed exists for galaxies in the lowest mass bin (M ∗ ∼ 1010 M o˙). This correlation, albeit with a ∼35% scatter, holds for different tracers of star formation, and becomes stronger with redshift. This result generally agrees with the picture that at higher redshifts star formation rate was generally higher, and galaxies at M ∗ ≲ 1010 M o˙ have not yet settled into a disk. As a consequence, they have shallower gravitational potentials more easily perturbed by stellar feedback. The observed correlation between σ star (and σ gas) and sSFR supports the scenario predicted by cosmological simulations, in which feedback-driven outflows cause fluctuations in the gravitation potential that flatten the density profiles of low-mass galaxies.

We investigate the impact of local environment on the galaxy stellar mass function (SMF) spanning a wide range of galaxy densities from the field up to dense cores of massive galaxy clusters. Data are drawn from a sample of eight fields from the Observations of Redshift Evolution in Large-Scale Environments (ORELSE) survey. Deep photometry allow us to select mass-complete samples of galaxies down to 109M⊙. Taking advantage of > 4000 secure spectroscopic redshifts from ORELSE and precise photometric redshifts, we construct threedimensional density maps between 0.55 < z < 1.3 using a Voronoi tessellation approach. We find that the shape of the SMF depends strongly on local environment exhibited by a smooth, continual increase in the relative numbers of high- to low-mass galaxies towards denser environments. A straightforward implication is that local environment proportionally increases the efficiency of (a) destroying lower mass galaxies and/or (b) growth of higher mass galaxies. We also find a presence of this environmental dependence in the SMFs of starforming and quiescent galaxies, although not quite as strongly for the quiescent subsample. To characterize the connection between the SMFof field galaxies and that of denser environments, we devise a simple semi-empirical model. The model begins with a sample of ≈106 galaxies at zstart = 5 with stellar masses distributed according to the field. Simulated galaxies then evolve down to zfinal = 0.8 following empirical prescriptions for star-formation, quenching and galaxy-galaxy merging.We run the simulationmultiple times, testing a variety of scenarios with differing overall amounts of merging. Our model suggests that a large number of mergers are required to reproduce the SMF in dense environments. Additionally, a large majority of these mergers would have to occur in intermediate density environments (e.g. galaxy groups).