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Probing Reionization-Era Galaxies with JWST UV Luminosity Functions and Large-Scale Clustering

Anirban Chakraborty, Tirthankar Roy Choudhury

TL;DR

We address the challenge of reconciling JWST measured UV luminosity functions with the observed redshift evolution of galaxy clustering within the context of cosmic reionization. Using a self-consistent semi-analytic framework, we show that a baseline one-to-one halo to galaxy mapping cannot fit UVLF and clustering simultaneously, motivating extensions that include a redshift- and mass-dependent star-formation duty cycle and a halo-mass dependent escaping efficiency. The extended model yields a coherent picture in which low-mass halos form stars in short bursts with smaller occupancy, while higher-mass halos maintain longer star-formation timescales, and the population-averaged escape fraction grows with redshift, enabling reionization histories in line with current constraints. Together, these results demonstrate the necessity of joint UVLF and bias constraints for interpreting JWST data and provide a framework for future refinements that incorporate stochastic star-formation histories and spatial fluctuations in reionization.

Abstract

JWST has transformed our understanding of early galaxy formation, providing an unprecedented view of the first billion years of cosmic history. In this work, we build upon our previously developed semi-analytical framework that self-consistently models the evolving UVLF of galaxies and the global reionization history while incorporating the effects of radiative feedback. Comparing our predictions with JWST and HST data, we identify a fundamental tension: models that match the UVLF fail to reproduce the observed evolution of galaxy clustering (bias) with redshift, and vice versa. To resolve this, we introduce a redshift- and mass-dependent duty cycle linked to the duration of star formation. This duty cycle increases towards higher redshifts, requiring either an enhanced production of UV radiation or increased star formation efficiency at z>10 to match the JWST UVLFs, but declines at lower redshifts (5<z<=9) and towards low-mass halos to remain consistent with the bias and HST UVLF measurements. Reconciling theory with observations requires the characteristic star formation timescale to be longer in massive halos, and to decrease with redshift at fixed halo mass, evolving from ~ 85 Myr at z=6 to ~ 45 Myr at z=14 for $10^{10} M_\odot$ halos. Finally, our extended model, assuming a halo mass-dependent escaping ionizing efficiency ($\varepsilon_{\rm esc} \equiv f_{\rm esc} \times ξ_{\rm ion}$), whose population-averaged value gradually increases with redshift and corresponds to $\langle f_{\rm esc} \rangle \sim$ 15% at z=5 for a fixed value of $ξ_{\rm ion} = 10^{25.23}$ erg$^{-1}$ Hz across all galaxies, produces a reionization history consistent with current constraints. These findings underscore the importance of jointly constraining high-redshift galaxy models using both UVLF and bias statistics to accurately interpret JWST data and refine our understanding of early cosmic evolution.

Probing Reionization-Era Galaxies with JWST UV Luminosity Functions and Large-Scale Clustering

TL;DR

We address the challenge of reconciling JWST measured UV luminosity functions with the observed redshift evolution of galaxy clustering within the context of cosmic reionization. Using a self-consistent semi-analytic framework, we show that a baseline one-to-one halo to galaxy mapping cannot fit UVLF and clustering simultaneously, motivating extensions that include a redshift- and mass-dependent star-formation duty cycle and a halo-mass dependent escaping efficiency. The extended model yields a coherent picture in which low-mass halos form stars in short bursts with smaller occupancy, while higher-mass halos maintain longer star-formation timescales, and the population-averaged escape fraction grows with redshift, enabling reionization histories in line with current constraints. Together, these results demonstrate the necessity of joint UVLF and bias constraints for interpreting JWST data and provide a framework for future refinements that incorporate stochastic star-formation histories and spatial fluctuations in reionization.

Abstract

JWST has transformed our understanding of early galaxy formation, providing an unprecedented view of the first billion years of cosmic history. In this work, we build upon our previously developed semi-analytical framework that self-consistently models the evolving UVLF of galaxies and the global reionization history while incorporating the effects of radiative feedback. Comparing our predictions with JWST and HST data, we identify a fundamental tension: models that match the UVLF fail to reproduce the observed evolution of galaxy clustering (bias) with redshift, and vice versa. To resolve this, we introduce a redshift- and mass-dependent duty cycle linked to the duration of star formation. This duty cycle increases towards higher redshifts, requiring either an enhanced production of UV radiation or increased star formation efficiency at z>10 to match the JWST UVLFs, but declines at lower redshifts (5<z<=9) and towards low-mass halos to remain consistent with the bias and HST UVLF measurements. Reconciling theory with observations requires the characteristic star formation timescale to be longer in massive halos, and to decrease with redshift at fixed halo mass, evolving from ~ 85 Myr at z=6 to ~ 45 Myr at z=14 for halos. Finally, our extended model, assuming a halo mass-dependent escaping ionizing efficiency (), whose population-averaged value gradually increases with redshift and corresponds to 15% at z=5 for a fixed value of erg Hz across all galaxies, produces a reionization history consistent with current constraints. These findings underscore the importance of jointly constraining high-redshift galaxy models using both UVLF and bias statistics to accurately interpret JWST data and refine our understanding of early cosmic evolution.

Paper Structure

This paper contains 14 sections, 33 equations, 23 figures, 2 tables.

Figures (23)

  • Figure 1: The galaxy UV luminosity functions at nine different redshift bins (with their respective mean values $\langle z \rangle$ mentioned in the upper left corner) for 200 random samples drawn from the MCMC chains of the UVLF+reion case, based on the baseline model. In each panel, the solid dark-blue line corresponds to the best-fit model, while the colored data points show the different observational constraints Bouwens2021Donnan2023Harikane2023Bouwens2023McLeod2024Donnan2024 used in the likelihood analysis.
  • Figure 2: The redshift evolution of the normalization (left panel) and power-law (right panel) scaling of the production efficiency of UV radiation with halo mass for 200 random samples drawn from the MCMC chains of the UVLF+reion case, based on the baseline model. The grey box encloses the range of average redshifts (5 $\leq \langle z \rangle \leq$ 13.2) at which UVLF observations have been used for comparison with the model in this work.
  • Figure 3: The evolution of (a) the globally averaged intergalactic neutral hydrogen fraction and (b) the effective galaxy bias as a function of redshift for 200 random samples drawn from the MCMC chains of the UVLF+reion case, based on the baseline model. The colored data points in each panel represent the respective observational measurements Davies2018Greig2022Gaikwad2023Umeda2023Durovcikova2024DalmassoJWSTShuntov2025. Note that, unlike the reionization history, the galaxy bias observations were not included in the likelihood analysis for the UVLF+reion case.
  • Figure 4: Same as Figure \ref{['fig:baseline_case1_reion_history_and_gal_bias']} but for 200 random samples drawn from the MCMC chains of the bias+reion case, based on the baseline model. Note that the likelihood analysis for the bias+reion case includes both the reionization history and galaxy bias observations, whereas the UVLF datasets were excluded.
  • Figure 5: Same as Figure \ref{['fig:baseline_case1_sfe_params']} but for 200 random samples drawn from the MCMC chains of the bias+reion case, based on the baseline model.
  • ...and 18 more figures