Quiescent Low-mass Galaxies Observed by JWST in the Epoch of Reionization

The growth of galaxies is regulated by the conversion of cold gas into stars and is affected by different feedback processes (Ciardi & Ferrara 2005), which can lead to the temporary or definitive quenching of the star formation activity. Internal feedback mechanisms include radiative feedback, which can destroy H₂ molecules preventing gas cooling (e.g., Johnson et al. 2007; Krumholz et al. 2009), and mechanical feedback from massive stars/supernovae (SN) or active galactic nuclei (AGNs), which can partially or completely remove the gas reservoir (e.g., Mac Low & Ferrara 1999; Croton et al. 2016; Carnall et al. 2023).

The evolution of low-mass galaxies, which we define here as those with stellar mass M_⋆ ≤ 10^9.5 M_⊙, is dramatically affected, regulated, and—in some cases—even halted by these physical mechanisms because of their shallow potential well (e.g., Ferrara & Tolstoy 2000; Salvadori et al. 2008; Wise et al. 2012; Collins & Read 2022). Furthermore, these systems can also be impacted by more global feedback mechanisms, such as reionization, preventing the accretion of fresh gas into the less-massive systems (e.g., Gnedin 2000; Dijkstra et al. 2004; Sobacchi & Mesinger 2013; Pereira-Wilson et al. 2023), and environmental effects, such as ram pressure stripping, which can remove the interstellar medium from satellite galaxies (e.g., Mayer et al. 2006; Emerick et al. 2016; Boselli et al. 2022). Thus, low-mass galaxies are the ideal laboratory to investigate feedback processes.

In the early Universe, low-mass galaxies are very common. Thanks to JWST we can now study them and investigate the role of the various feedback processes in their evolution. Looser et al. (2023) recently reported the discovery of a quiescent low-mass galaxy at redshift z = 7.3 (see also Strait et al. 2023 for another very low-mass quiescent system at z = 5.2) from the JADES program, JADES-GS-z7-01-QU. Following this work, we define as quiescent those galaxies with no (or negligible) star formation activity at the epoch of observation. ⁴ According to Looser et al. (2023), the spectral energy distribution (SED) of JADES-GS-z7-01-QU is consistent with a metal-poor M_⋆ ≈ 5 × 10⁸ M_⊙ stellar population formed in a short and intense burst of star formation followed by rapid quenching (star formation rate (SFR) < 10^−2.5 M_⊙ yr⁻¹), about 10-20 Myr before the epoch of observation. Given the rapidity of the transition from a star-forming to a quiescent state for JADES-GS-z7-01-QU, its quenching is expected to have been driven by a fast process. A reasonable explanation may therefore be associated with the injection of mechanical energy through outflows by either star formation or AGN.

In this Letter, we aim to interpret these new findings and address the following questions: What is the duty cycle of high-redshift low-mass galaxies? When and why do low-mass galaxies become quiescent? What are the key physical mechanisms causing their quenching?

To answer the above questions, we use the serra (Pallottini et al. 2022) suite of high-resolution cosmological zoom-in simulations that follow the evolution of typical Lyman break galaxies during the Epoch of Reionization. The simulations evolve from z = 100, where initial conditions are generated with music (Hahn & Abel 2011), in a cosmological volume of (20 Mpc/h)³ by assuming a Planck Collaboration et al. (2014) cosmology. ⁵ A customized version of the Adaptive Mesh Refinement code ramses (Teyssier 2002) is used for the evolution of dark matter (DM), stars, and gas, reaching a baryon mass resolution of 1.2 × 10⁴ M_⊙ and spatial resolution of ≃20 pc in the zoom-in regions, i.e., about the mass and size of molecular clouds.

On-the-fly radiative transfer is included through ramses-rt (Rosdahl et al. 2013), and a nonequilibrium chemical network generated with krome (Grassi et al. 2014) is used for regulating the interaction of the gas with photons (Pallottini et al. 2017a). Stars form according to a Schmidt–Kennicutt relation (Kennicutt 1998) depending on the molecular-hydrogen gas density and assuming a Kroupa (2001) initial mass function for the stellar particles. Stellar feedback modeling includes SNe explosions, winds, and radiation pressure (Pallottini et al. 2017b). The energy inputs and chemical yields, depending on the stellar age and metallicity, are computed through starburst99 (Leitherer et al. 1999) using padova stellar tracks (Bertelli et al. 1994), covering a metallicity range of Z_⋆/Z_⊙ = 0.02–1.0. Since the resolution does not allow us to follow the evolution of the first stars and mini-haloes, their effect on the interstellar medium (ISM) is reproduced by setting the initial gas metallicity to a floor value of Z_floor = 10⁻³ Z_⊙ (Wise et al. 2012; Pallottini et al. 2014).

The emission of the galaxies is modeled using starburst99 for the stellar and nebular continuum (see also Gelli et al. 2021). We use cloudy (Ferland et al. 2017) to compute nebular line emission (considering the main ones typically contributing to the rest-frame UV-optical spectrum, i.e., Hα, Hβ, Hγ, [O ii]λ λ 3726,3729, [O iii]λ λ 4959,5007, and C iii]1909), accounting for the ISM density, metallicity, internal structure, and radiation field (e.g., Vallini et al. 2018; Kohandel et al. 2019; Pallottini et al. 2019). Finally, we take into account the presence of dust, which attenuates the intrinsic galaxy spectrum (i.e., Gelli et al. 2021), adopting a dust-to-metal ratio f_d = 0.08 and assuming a Milky Way-like dust composition and grain size distribution ⁶ (Weingartner & Draine 2001).

We analyze multiple snapshots of different serra runs in the range 6 < z < 8.4. We follow the stellar-density method implemented in Gelli et al. (2020) to select low-mass galaxies with M_⋆ ≲ 10^9.5 M_⊙. The final sample has 130 galaxies.

As an example, in Figure 1 we show stellar and gas density maps from one of the simulations at z = 6. The displayed volume (10⁶ kpc³) contains six galaxies. In the two insets, we zoom on typical low-mass systems: an actively star-forming ($\mathrm{log}{M}_{\star }/{M}_{\odot }=8.97$), and a quiescent system with no ongoing star formation ($\mathrm{log}{M}_{\star }/{M}_{\odot }=7.96$). The former shows an extended (∼500 pc in radius) stellar distribution, and a gas proto-disk structure, typical of more massive galaxies. The quiescent galaxy is instead smaller, both in terms of stellar mass and size, with all of its stars concentrated in the inner ≲200 pc, and almost completely devoid of gas.

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In Figure 2 we show the star formation histories (SFHs) in terms of age of the Universe t_H for some serra low-mass galaxies up to different observation redshifts. The SFHs have an intermittent nature made of bursts followed by star formation drops or even halts. Such behavior results from stellar feedback, efficiently decreasing or even suppressing star formation in low-mass galaxies. Note that all galaxies with final mass M_⋆ ≲ 10⁹ M_⊙ have experienced quiescent SF phases, or are still quenched at the final snapshot, which is identified as the redshift of observation. On average, these quenched galaxies represent 30% of the population.

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Interestingly, after the SF peak, these low-mass galaxies feature a smooth SFR decrease lasting some tens of Myr until the final quenching. This trend is typical of stellar feedback powered by SNe, as explosions occur with a delay time that increases with a decreasing SN progenitor mass (see Gelli et al. 2020). This behavior is encountered in all low-mass systems, i.e., in both field and satellite galaxies, implying that environmental processes do not drive their evolution.

In the middle panel of Figure 2, we pinpoint the galaxy Lilium, which is quiescent at z = 7.3 and has the same stellar mass as JADES-GS-z7-01-QU (10^8.7 M_⊙).

Figure 3 shows the galaxy SFR duty cycle, i.e., the ratio between the actively star-forming (SFR > 0) time interval, Δt_on, and the time elapsed between the first star formation event, t_form, and the observation redshift at t_obs:

$$\begin{eqnarray}&&{f}_{\mathrm{duty}}=\displaystyle \frac{{\rm{\Delta }}{t}_{\mathrm{on}}}{{t}_{\mathrm{obs}}-{t}_{\mathrm{form}}}.\end{eqnarray} \tag{ 1 }$$

Galaxies are color-coded with the mass-averaged age of their stellar populations; quiescent systems (Q1–Q4) identified in Figure 2 are specifically indicated.

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Galaxies with M_⋆ < 10⁹ M_⊙ can be either quiescent or active, and the fraction of quiescent systems increases with decreasing stellar mass, becoming the dominating population for M_⋆ < 10^8.3 M_⊙ (see histograms in the upper panel of Figure 3). In this mass range, quiescent galaxies (a) are older (average ages >100 Myr), and (b) have lower and more scattered duty cycles (f_duty ≈ 0.2–0.9) than active galaxies (f_duty ≈ 0.8–0.99). For M_⋆ > 10⁹ M_⊙, instead, all galaxies are active, and they have been forming stars for ≥95% of their lifetime.

The average duty cycle of quiescent and active galaxies clearly reflects these trends with stellar mass, slowly increasing from f_duty ≈ 0.6 for M_⋆ ≈ 10^7.5 M_⊙ to ≈0.99 for M_⋆ ≥ 10⁹ M_⊙. Noticeably, the quiescent galaxy Lilium ($\mathrm{log}{M}_{\star }/{M}_{\odot }=8.7$) has a duty cycle f_duty ≈ 0.84, which is consistent with the values obtained for JADES-GS-z7-01-QU using different stellar population synthesis tools by Looser et al. (2023). For instance, when considering the values derived with bagpipes in Table 1 therein, ⁷ the time from the first star formation event is t_obs − t_form ≈ 40 Myr, and the time of active star formation is Δt_on ≈ 30 Myr. This implies a duty cycle (see Equation (1)) for JADES-GS-z7-01-QU of f_duty ≈ 0.75.

Lilium was selected among serra quiescent galaxies due to its similarity with JADES-GS-z7-01-QU in terms of stellar mass, duty cycle (Figure 3), and the time elapsed between SF quenching and observation redshift (Δt_quench ∼ 15 Myr for Lilium versus Δt_quench ∼ 10–40 Myr for JADES-GS-z7-01-QU). However, the stellar populations of Lilium are more metal-rich (Z_⋆ ≈ Z_⊙) than deduced by Looser et al. (2023) for JADES-GS-z7-01-QU, Z_⋆ ≈ 0.01 Z_⊙. In spite of these similarities, the SED we predict for Lilium (Figure 4, left panel) is too faint to match the one observed in JADES-GS-z7-01-QU. What is the origin of such a discrepancy?

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We first check the role of stellar metallicity by imposing that all the stars in Lilium have Z_⋆ ≈ 0.01 Z_⊙. However, the resulting SED only increases by ≲0.2 dex (see Figure 4, left panel). The right panel of Figure 4 displays the SFH of Lilium. At z ≈ 8.4, i.e., around 120 Myr before observations, Lilium started to form stars at a progressively increasing rate. After ≈35 Myr it experienced a short and intense burst of star formation (SFR ≳ 25 M_⊙ yr⁻¹), after which 80% of the final stellar mass was already in place. Then, the SFR was gradually suppressed by SNe, which are the dominating feedback mechanism in our simulations. Indeed, the galaxy continued to form stars at a much lower rate, ≲2 M_⊙ yr⁻¹, for ≈50 Myr, i.e., up to z ≈ 7.45 when it was completely quenched. Therefore, at the redshift of observation, z = 7.3, the average stellar age of Lilium is ≈90 Myr old (see the color bar in Figure 3).

In the same panel, we plot an SFH similar to the one derived by Looser et al. (2023) using bagpipes, essentially a top-hat with an SFR = 15 M_⊙ yr⁻¹ but with the same Δt_quench and M_⋆ as Lilium. With this SFR, the observed M_⋆ is produced in only ≈30 Myr, resulting in a much younger (≈30 Myr) stellar population. The other SED-fitting codes ⁸ used by Looser et al. (2023), prospector (Johnson et al. 2021) and pxff (Cappellari 2017), also draw similar conclusions, resulting in average stellar ages always lower than ≲50 Myr. As a consequence, the corresponding experimentally derived SED reaches fluxes about 10 times higher than Lilium (Figure 4, left) and matches JADES-GS-z7-01-QU photometry if a metallicity of 0.01 Z_⊙ is further assumed.

This result shows that the discrepancy between the SEDs of Lilium and JADES-GS-z7-01-QU is largely due to differences in their SFHs, and to a lesser extent, metallicity. The key difference is the fact the SFRs decrease in Lilium after the SF peak is too prolonged, resulting in a high fraction of old stars at the time of the observation. This suggests the need for an abrupt quenching right after the SF peak.

To test this hypothesis, we artificially impose that SF in Lilium was abruptly halted ∼5 Myr after the peak, and we renormalize it to get the same M_⋆ value. We then assume to observe the galaxy after Δt_quench = 10–20 Myr from the halt, and thus shift the SFHs to match the redshift of the observations, i.e., z = 7.3. As a consequence of the overall galaxy lifetime time being shorter, the duty cycle of Lilium lowers to ≈0.7. We find that such modified Lilium SED now perfectly matches the observed one even by assuming the simulated stellar metallicity, Z_⋆ ≈ Z_⊙.

In spite of the fact that Lilium is very similar to JADES-GS-z7-01-QU, the simulated SED does not match the observed one. We have shown that this is due to the fact that star formation in JADES-GS-z7-01-QU is quenched on a much shorter timescale than in Lilium.

If the quenching has to be produced by SNe, there is an intrinsic timescale on which such feedback acts, which is given by the time over which SNe associated with a given burst explode. This value is ≳30 Myr for a Kroupa initial mass function (see, e.g., Figure 2 in Pallottini et al. 2017a). The quenching cannot, therefore, be significantly shorter than this minimum value, and this is exactly what we see in the SFH of Lilium and the other quenched low-mass galaxies (Q1, Q2, Q3, and Q4). Basically, the SFR decline under the action of SN feedback is very gradual, resulting in too large a number of stars that are old by the time the galaxy is observed. This is a general problem of SF quenching in low-mass galaxies, which inherently depends on the delay of SN explosions associated with the deaths of progenitors of different masses (e.g., Rosdahl et al. 2017).

We speculate that the decline could be more abrupt if the mechanical energy is instead provided by a hidden AGN and/or radiation pressure from young massive stars (e.g., Carniani et al. 2016; Ferrara et al. 2023; Ziparo et al. 2023). Indeed, we may in general estimate the quenching timescale as Δt_quench = t_delay + t_ej, where t_delay is the delay time associated with the onset of the physical process causing the quenching and t_ej is the ejection time required for the outflow to drive the gas out of the galaxy. While for SNe we have t_delay ≳ 30 Myr, for radiation-driven feedback there is no such delay, and we can evaluate the overall quenching timescale simply as Δt_quench = t_ej. Assuming a typical outflow velocity of v > 200 km s⁻¹ and requiring an expelling of the gas at a distance of d ≈ 500 pc to quench star formation (given that the effective radius of the galaxy is ≈100 pc), we obtain ${\rm{\Delta }}\,{t}_{\mathrm{quench}}=d/v\lesssim \tfrac{500\,\mathrm{pc}}{200\,\mathrm{km}\,{{\rm{s}}}^{-1}}=2.4\,\mathrm{Myr}$. The gas in the galaxy is expected to be set in motion and removed in such a short time as soon as the galaxy exceeds the Eddington limit. Specifically, this can happen through (i) stellar radiation, when the specific SFR exceeds a threshold value (>13 Gyr⁻¹; see Fiore et al. 2023), and (ii) AGN feedback from massive black holes that may be a viable solution for high-z galaxies according to recent results (e.g., Maiolino et al. 2023). We therefore conclude that the SFR decline might be a powerful diagnostic of different feedback types.

Another puzzle posed by the JADES-GS-z7-01-QU observation is its long latency before the first episode of star formation. This source is observed at z = 7.3 and, according to the SED interpretation, has formed all of its stars in a short (≈30 Myr) burst. This sets the start of its star formation activity at z ≈ 7.8. From the observed stellar mass M_⋆ = 10^8.7 M_⊙, and conservatively assuming that all its baryons were turned into stars, we can set a lower limit to the host halo, M ≳ (Ω_m /Ω_b )M_⋆ = 3.2 × 10⁹ M_⊙. Assuming a standard growth history, this halo should have crossed the critical mass M ≈ 10⁸ M_⊙, marking the separation between mini-halos, in which the SF is easily suppressed, and the star-forming Lyα-cooling halos at z ≳ 11.7. Thus, in the redshift interval 7.8 < z < 11.7 (280 Myr), although conditions were in principle favorable to star formation in terms of gas cooling, the galaxy did not form a significant amount of stars. A possibility might be the following: if a galaxy spawns a massive stellar cluster (M_⋆ ≃ 10⁵ M_⊙) as its first star formation event, its radiation can photodissociate molecular hydrogen and prevent further star formation for up to ∼300 Myr (see Alyssum; Pallottini et al. 2022).

As JWST will build a sizable sample of quiescent high-z galaxies, we will be able to solve these puzzles and understand the nature of the feedback-regulated evolution of low-mass systems.

This project received funding from the ERC Starting Grant NEFERTITI H2020/804240 (PI: Salvadori). A.F., A.P., and S.C. acknowledge the ERC Advanced Grant INTERSTELLAR H2020/740120 (PI: Ferrara). We acknowledge the CINECA award under the ISCRA initiative, for the availability of high performance computing resources and support from Class B project SERRA HP10BPUZ8F (PI: Pallottini) and the computational resources of the Center for High Performance Computing (CHPC) at SNS.