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Lyman α emitters (LAEs) are excellent probes of the reionization process, as they must be surrounded by large ionized bubbles in order to be visible during the reionization era. Large ionized regions are thought to correspond to overdense regions and may be protoclusters, making them interesting test-beds for early massive structures. Close associations containing several LAEs are often assumed to mark overdense, ionized bubbles. Here, we develop the first framework to quantify the ionization and density fields of high-z galaxy associations. We explore the interplay between (i) the large-scale density of a survey field, (ii) Poisson noise due to the small number density of bright sources at high redshifts (z ∼ 7), and (iii) the effects of the ionized fraction on the observation of LAEs. We use Bayesian statistics, a simple model of reionization, and a Monte Carlo simulation to construct a more comprehensive method for calculating the large-scale density of LAE regions than previous works. We find that Poisson noise has a strong effect on the inferred density of a region and show how the ionized fraction can be inferred. We then apply our framework to the strongest association yet identified: Hu et al. found 14 LAEs in a volume of ∼50 000 cMpc3 inside the COSMOS field at z ∼ 7. We show that this is most likely a 2.4σ overdensity inside of an ionized or nearly ionized bubble. We also show that this LAE association implies that the global ionized fraction is $\bar{Q} = 0.59^{+0.10}_{-0.11}$, within the context of a simple reionization model.

 

The epoch of reionization (EoR) offers a unique window into the dawn of galaxy formation, through which high-redshift galaxies can be studied by observations of both themselves and their impact on the intergalactic medium. Line intensity mapping (LIM) promises to explore cosmic reionization and its driving sources by measuring intensity fluctuations of emission lines tracing the cosmic gas in varying phases. Using LIMFAST, a novel seminumerical tool designed to self-consistently simulate LIM signals of multiple EoR probes, we investigate how building blocks of galaxy formation and evolution theory, such as feedback-regulated star formation and chemical enrichment, might be studied with multitracer LIM during the EoR. On galaxy scales, we show that the star formation law and the feedback associated with star formation can be indicated by both the shape and redshift evolution of LIM power spectra. For a baseline model of metal production that traces star formation, we find that lines highly sensitive to metallicity are generally better probes of galaxy formation models. On larger scales, we demonstrate that inferring ionized bubble sizes from cross-correlations between tracers of ionized and neutral gas requires a detailed understanding of the astrophysics that shape the line luminosity–halo mass relation. Despite various modeling and observational challenges, wide-area, multitracer LIM surveys will provide important high-redshift tests for the fundamentals of galaxy formation theory, especially the interplay between star formation and feedback by accessing statistically the entire low-mass population of galaxies as ideal laboratories, complementary to upcoming surveys of individual sources by new-generation telescopes.

 

One of the key processes driving galaxy evolution during the Cosmic Dawn is supernova feedback. This likely helps regulate star formation inside of galaxies, but it can also drive winds that influence the large-scale intergalactic medium. Here, we present a simple semi-analytic model of supernova-driven galactic winds and explore the contributions of different phases of galaxy evolution to cosmic metal enrichment in the high-redshift (z ≳ 6) Universe. We show that models calibrated to the observed galaxy luminosity function at z ∼ 6–8 have filling factors $\sim 1{{\%}}$ at z ∼ 6 and $\sim 0.1{{\%}}$ at z ∼ 12, with different star formation prescriptions providing about an order of magnitude uncertainty. Despite the small fraction of space filled by winds, these scenarios predict an upper limit to the abundance of metal-line absorbers in quasar spectra at $z \gtrsim 5$ which is comfortably above that currently observed. We also consider enrichment through winds driven by Pop III star formation in minihalos. We find that these can dominate the total filling factor at $z \gtrsim 10$ and even compete with winds from normal galaxies at z ∼ 6, at least in terms of the total enriched volume. But these regions have much lower overall metallicities, because each one is generated by a small burst of star formation. Finally, we show that Compton cooling of these supernova-driven winds at $z \gtrsim 6$ has only a small effect on the cosmic microwave background.

 

One of the most exciting advances of the current generation of telescopes has been the detection of galaxies during the epoch of reionization, using deep fields that have pushed these instruments to their limits. It is essential to optimize our analyses of these fields in order to extract as much information as possible from them. In particular, standard methods of measuring the galaxy luminosity function discard information on large-scale dark matter density fluctuations, even though this large-scale structure drives galaxy formation and reionization during the Cosmic Dawn. Measuring these densities would provide a bedrock observable, connecting galaxy surveys to theoretical models of the reionization process and structure formation. Here, we use existing Hubble deep field data to simultaneously fit the universal luminosity function and measure large-scale densities for each Hubble deep field at z = 6–8 by directly incorporating priors on the large-scale density field and galaxy bias. Our fit of the universal luminosity function is consistent with previous methods but differs in the details. For the first time, we measure the underlying densities of the survey fields, including the most over/underdense Hubble fields. We show that the distribution of densities is consistent with current predictions for cosmic variance. This analysis on just 17 fields is a small sample of what will be possible with the James Webb Space Telescope, which will measure hundreds of fields at comparable (or better) depths and at higher redshifts.

 

Cosmic variance from large-scale structure will be a major source of uncertainty for galaxy surveys at $z \gtrsim 6$, but that same structure will also provide an opportunity to identify and study dense environments in the early Universe. Using a robust model for galaxy clustering, we directly incorporate large-scale densities into an inference framework that simultaneously measures the high-z ($z \gtrsim 6$) UV luminosity function and the average matter density of each distinct volume in a survey. Through this framework, we forecast the performance of several major upcoming James Webb Space Telescope (JWST) galaxy surveys. We find that they can constrain field matter densities down to the theoretical limit imposed by Poisson noise and unambiguously identify over-dense (and under-dense) regions on transverse scales of tens of comoving Mpc. We also predict JWST will measure the luminosity function with a precision at z = 12 comparable to existing Hubble Space Telescope’s constraints at z = 8 (and even better for the faint-end slope). We also find that wide-field surveys are especially important in distinguishing luminosity function models.

 

ABSTRACT Cosmic variance is the intrinsic scatter in the number density of galaxies due to fluctuations in the large-scale dark matter density field. In this work, we present a simple analytic model of cosmic variance in the high-redshift Universe (z ∼ 5–15). We assume that galaxies grow according to the evolution of the halo mass function, which we allow to vary with large-scale environment. Our model produces a reasonable match to the observed ultraviolet (UV) luminosity functions in this era by regulating star formation through stellar feedback and assuming that the UV luminosity function is dominated by recent star formation. We find that cosmic variance in the UV luminosity function is dominated by the variance in the underlying dark matter halo population, and not by differences in halo accretion or the specifics of our stellar feedback model. We also find that cosmic variance dominates over Poisson noise for future high-z surveys except for the brightest sources or at very high redshifts (z ≳ 12). We provide a linear approximation of cosmic variance for a variety of redshifts, magnitudes, and survey areas through the public python package galcv. Finally, we introduce a new method for incorporating priors on cosmic variance into estimates of the galaxy luminosity function and demonstrate that it significantly improves constraints on that important observable.