Variability of the UV luminosity function with SPICE

TL;DR

The study uses the SPICE radiation-hydrodynamic simulations to quantify how different supernova feedback prescriptions alter the variability of the high-z UV luminosity function. By comparing bursty, smooth, and hypernova-influenced SN feedback, the authors link star formation-rate fluctuations to UVLF scatter and show that low-mass halos exhibit the strongest variability, with peak UVLF fluctuations reaching ~2.5 in the bursty SN case. Variability generally declines with decreasing redshift and differs in amplitude across models, yet all models remain broadly consistent with current observations. The results highlight SN feedback as a key driver of UVLF variability and suggest this mechanism could mitigate JWST bright-galaxy tensions by allowing more dynamic UV output in the early universe.

Abstract

We investigate the variability of the UV luminosity function (UVLF) at $z > 5$ using the SPICE suite of cosmological, radiation-hydrodynamic simulations, which include three distinct supernova (SN) feedback models: bursty-sn, smooth-sn, and hyper-sn. The bursty-sn model, driven by intense and episodic SN explosions, produces the highest fluctuations in the star formation rate (SFR). Conversely, the smooth-sn model, characterized by gentler SN feedback, results in minimal SFR variability. The hyper-sn model, featuring a more realistic prescription that incorporates hypernova (HN) explosions, exhibits intermediate variability, closely aligning with the smooth-sn trend at lower redshifts. These fluctuations in SFR significantly affect the $\rm{M_{UV} - M_{halo}}$ relation, a proxy for UVLF variability. Among the models, bursty-sn produces the highest UVLF variability, with a maximum value of 2.5. In contrast, the smooth-sn and hyper-sn models show substantially lower variability, with maximum values of 1.3 and 1.5, respectively. However, in all cases, UVLF variability strongly correlates with host halo mass, with lower-mass halos showing greater variability due to more effective SN feedback in their shallower gravitational wells. The bursty-sn model, though, results in higher amplitudes. Variability decreases in lower mass haloes with decreasing redshift for all feedback models. This study underscores the critical role of SN feedback in shaping the UVLF, and highlights the mass and redshift dependence of its variability, suggesting that UVLF variability may alleviate the bright galaxy tension observed by JWST at high redshifts.

Figures (12)

• Figure 1: 1500 $\angstrom$ luminosity functions at $z$ = 12 (top panel) and 11 (bottom panel) for three feedback models (in different colors). Solid and dashed curves refer to intrinsic and dust attenuated LFs, respectively. A compilation of observations from HST and JWSTbouwens2015harikane2022naidu2022adams2023harikane2023bouwens2023abouwens2023bleung2023donnan2023adonnan2023bperez2023casey2024robertson2024mcleod2024Whitler2025 is shown as gray data points.
• Figure 2: Distribution of stellar mass of objects with $\rm{\mathit{M}_{UV}^{dust}} \leq -17$ at $z=10$ (top panel), 8 (middle) and 6 (bottom). The corresponding median stellar masses are shown as vertical dotted lines, while the black dashed lines refer to the minimum stellar mass required for having such bright objects assuming the median SFE model of mason2015mason2023.
• Figure 3: Evolution of the dust-attenuated UVLF over time intervals of 10, 30, and 50 Myr (indicated by different color gradients, from dark to light), centered at $z \approx 10$ (left panel) and 8 (right), for three different feedback models: bursty-sn (top panels), smooth-sn ( middle), and hyper-sn ( bottom). The dashed and dotted curves show the UVLF before and after the reference time.
• Figure 4: Temporal evolution of the SFR averaged over 2 Myr accounting for all stellar particles inside the virial radius of the most massive halo at $z = 5$, which has a total stellar mass of $2.1 \times 10^{9} \rm{\mathrm{M_{\odot}}}$, $1.9 \times 10^{10} \rm{\mathrm{M_{\odot}}}$ and $1.7 \times 10^{10} \rm{\mathrm{M_{\odot}}}$ for the bursty-sn, smooth-sn and hyper-sn model, respectively. Colors refer to the different SN feedback models. In the inset, we show the distributions of $\delta\rm{_{SFR,X}}$, together with the corresponding standard deviation, $\sigma\rm{_{SFR,X}}$ (see text for the details of the calculation),where 'X' = 'bu', 'sm', 'hn' for the bursty-sn, smooth-sn and hyper-sn model, respectively.
• Figure 5: $\sigma\rm{_{SFR}}$ as a function of halo mass $M\rm{_{halo}}$ at different redshifts (indicated by the colorbar) for bursty-sn ( top panel), smooth-sn ( middle) and hyper-sn ( bottom).