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Both observations and simulations have shown strong evidence for highly time-variable star formation in low-mass and/or high-redshift galaxies, which has important observational implications because high-redshift galaxy samples are rest-ultraviolet (rest-UV) selected and therefore particularly sensitive to the recent star formation. Using a suite of cosmological ‘zoom-in’ simulations at z > 5 from the Feedback in Realistic Environments project, we examine the implications of bursty star formation histories for observations of high-redshift galaxies with JWST. We characterize how the galaxy observability depends on the star formation history. We also investigate selection effects due to bursty star formation on the physical properties measured, such as the gas fraction, specific star formation rate, and metallicity. We find the observability to be highly time-dependent for galaxies near the survey’s limiting flux due to the star formation rate variability: as the star formation rate fluctuates, the same galaxy oscillates in and out of the observable sample. The observable fraction $f_\mathrm{obs} = 50~{{\ \rm per\ cent}}$ at z ∼ 7 and M⋆ ∼ 108.5–$10^{9}\, {\rm M}_{\odot }$ for a JWST/NIRCam survey reaching a limiting magnitude of $m^\mathrm{lim}_\mathrm{AB} \sim 29{\!-\!}30$, representative of surveys such as JADES and CEERS. JWST-detectable galaxies near the survey limit tend to have properties characteristic of galaxies in the bursty phase: on average, they show approximately 2.5 times higher cold, dense gas fractions and 20 times higher specific star formation rates at a given stellar mass than galaxies below the rest-UV detection threshold. Our study represents a first step in quantifying selection effects and the associated biases due to bursty star formation in studying high-redshift galaxy properties.

 

Recent discoveries of a significant population of bright galaxies at cosmic dawn$\left(z\gtrsim 10\right)$have enabled critical tests of cosmological galaxy formation models. In particular, the bright end of the galaxys’ UV luminosity functions (UVLFs) appear higher than predicted by many models. Using approximately 25,000 galaxy snapshots at 8 ≤z≤ 12 in a suite of FIRE-2 cosmological “zoom-in” simulations from the Feedback in Realistic Environments (FIRE) project, we show that the observed abundance of UV-bright galaxies at cosmic dawn is reproduced in these simulations with a multichannel implementation of standard stellar feedback processes, without any fine-tuning. Notably, we find no need to invoke previously suggested modifications, such as a nonstandard cosmology, a top-heavy stellar initial mass function, or a strongly enhanced star formation efficiency. We contrast the UVLFs predicted by bursty star formation in these original simulations to those derived from star formation histories (SFHs) smoothed over prescribed timescales (e.g., 100 Myr). The comparison demonstrates that the strongly time-variable SFHs predicted by the FIRE simulations play a key role in correctly reproducing the observed, bright-end UVLFs at cosmic dawn: the bursty SFHs induce order-or-magnitude changes in the abundance of UV-bright (M_UV≲ −20) galaxies atz≳ 10. The predicted bright-end UVLFs are consistent with both the spectroscopically confirmed population and the photometrically selected candidates. We also find good agreement between the predicted and observationally inferred integrated UV luminosity densities, which evolve more weakly with redshift in FIRE than suggested by some other models.

 

Understanding the star formation rate (SFR) variability and how it depends on physical properties of galaxies is important for developing and testing the theory of galaxy formation. We investigate how statistical measurements of the extragalactic background light (EBL) can shed light on this topic and complement traditional methods based on observations of individual galaxies. Using semi-empirical models of galaxy evolution and SFR indicators sensitive to different star formation time-scales (e.g. H α and ultraviolet continuum luminosities), we show that the SFR variability, quantified by the joint probability distribution of the SFR indicators (i.e. the bivariate conditional luminosity function), can be characterized as a function of galaxy mass and redshift through the cross-correlation between deep, near-infrared maps of the EBL and galaxy distributions. As an example, we consider combining upcoming SPHEREx maps of the EBL with galaxy samples from Rubin Observatory Legacy Survey of Space and Time. We demonstrate that their cross-correlation over a sky fraction of fsky ∼ 0.5 can constrain the joint SFR indicator distribution at high significance up to z ∼ 2.5 for mass-complete samples of galaxies down to $M_{*}\sim 10^9\, {\rm M}_{\odot }$. These constraints not only allow models of different SFR variability to be distinguished, but also provide unique opportunities to investigate physical mechanisms that require large number statistics such as environmental effects. The cross-correlations investigated illustrate the power of combining cosmological surveys to extract information inaccessible from each data set alone, while the large galaxy populations probed capture ensemble-averaged properties beyond the reach of targeted observations towards individual galaxies.

 

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.

 

We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly-α forest measurements. Using large cosmological hydrodynamic simulations, we model the emission from the CO rotational transition in the CO Mapping Array Project LIM experiment at the 5-yr benchmark and the Ly-α forest absorption signal for extended Baryon Acoustic Oscillations (BOSS), Dark energy survey instrument (DESI), and Prime Focus multiplex Spectroscopy survey (PFS). We show that CO × Ly-α forest significantly enhances the detection signal-to-noise ratio (S/N) of CO, with up to $300{{\ \rm per\, cent}}$ improvement when correlated with the PFS Ly-α forest survey and a 50–75 per cent enhancement with the available eBOSS or the upcoming DESI observations. This is competitive with even CO × spectroscopic galaxy surveys. Furthermore, our study suggests that the clustering of CO emission is tightly constrained by CO × Ly-α forest due to the increased sensitivity and the simplicity of Ly-α absorption modelling. Foreground contamination or systematics are expected not to be shared between LIM and Ly-α forest observations, providing an unbiased inference. Ly-α forest will aid in detecting the first LIM signals. We also estimate that [C ii] × Ly-α forest measurements from Experiment for Cryogenic Large-Aperture Intensity Mapping and DESI/eBOSS should have a larger S/N than planned [C ii] × quasar observations by about an order of magnitude.

 

ABSTRACT The cosmic near-infrared background (NIRB) offers a powerful integral probe of radiative processes at different cosmic epochs, including the pre-reionization era when metal-free, Population III (Pop III) stars first formed. While the radiation from metal-enriched, Population II (Pop II) stars likely dominates the contribution to the observed NIRB from the reionization era, Pop III stars – if formed efficiently – might leave characteristic imprints on the NIRB, thanks to their strong Lyα emission. Using a physically motivated model of first star formation, we provide an analysis of the NIRB mean spectrum and anisotropy contributed by stellar populations at z > 5. We find that in circumstances where massive Pop III stars persistently form in molecular cooling haloes at a rate of a few times $10^{-3}\, \mathrm{ M}_\odot \ \mathrm{yr}^{-1}$, before being suppressed towards the epoch of reionization (EoR) by the accumulated Lyman–Werner background, a unique spectral signature shows up redward of $1\, \mu$m in the observed NIRB spectrum sourced by galaxies at z > 5. While the detailed shape and amplitude of the spectral signature depend on various factors including the star formation histories, initial mass function, LyC escape fraction and so forth, the most interesting scenarios with efficient Pop III star formation are within the reach of forthcoming facilities, such as the Spectro-Photometer for the History of the Universe, Epoch of Reionization, and Ices Explorer. As a result, new constraints on the abundance and formation history of Pop III stars at high redshifts will be available through precise measurements of the NIRB in the next few years.