The JWST EXCELS survey: Too much, too young, too fast? Ultra-massive quiescent galaxies at 3 < z < 5 (2405.02242v2)

Abstract: We report ultra-deep, medium-resolution spectroscopic observations for 4 quiescent galaxies with log${10}(M/\mathrm{M_\odot})>11$ at $3 < z < 5$. These data were obtained with JWST NIRSpec as part of the Early eXtragalactic Continuum and Emission Line Science (EXCELS) survey, which we introduce in this work. The first two galaxies are newly selected from PRIMER UDS imaging, both at $z=4.62$ and separated by $860$ pkpc on the sky, within a larger structure for which we confirm several other members. Both formed at $z\simeq8-10$. These systems could plausibly merge by the present day to produce a local massive elliptical galaxy. The other two ultra-massive quiescent galaxies are previously known at $z=3.99$ and $3.19$, with the latter (ZF-UDS-7329) having been the subject of debate as potentially too old and too massive to be accommodated by the $\Lambda$-CDM halo-mass function. Both exhibit high stellar metallicities, and for ZF-UDS-7329 we are able to measure the $\alpha-$enhancement, obtaining [Mg/Fe] = $0.42^{+0.19}_{-0.17}$. We finally evaluate whether these 4 galaxies are consistent with the $\Lambda$-CDM halo-mass function using an extreme value statistics approach. We find that the $z=4.62$ objects and the $z=3.19$ object are unlikely within our area under the assumption of standard stellar fractions ($f_\simeq0.1-0.2$). However, these objects roughly align with the most massive galaxies expected under the assumption of 100 per cent conversion of baryons to stars ($f_*$=1). Our results suggest extreme galaxy formation physics during the first billion years, but no conflict with $\Lambda$-CDM cosmology.

• The paper uses JWST NIRSpec data from the EXCELS survey to study four ultra-massive quiescent galaxies at redshifts 3 < z < 5, examining their formation histories and cosmological implications.
• Full-spectral-fitting of these galaxies with stellar masses > 10^11 solar masses suggests they formed intense starbursts followed by rapid quenching at very early cosmic epochs (z > 5.5).
• Comparing observed galaxy masses with extreme value statistics for expected halos indicates these galaxies do not violate Lambda-CDM cosmology but require highly efficient early star formation and advanced baryonic physics in models.

Overview of "The JWST EXCELS survey: Too much, too young, too fast? Ultra-massive quiescent galaxies at $3 < z < 5$"

The paper presents findings from the Early eXtragalactic Continuum and Emission Line Science (EXCELS) survey, utilizing JWST NIRSpec to investigate ultra-massive quiescent galaxies in the redshift range $3 < z < 5$. The authors examine the spectroscopic data of four such galaxies, each with stellar masses exceeding $10^{11}$ solar masses. Three key areas are addressed: their formation histories, implications for $\Lambda$-CDM cosmology, and their potential as precursors to local massive ellipticals.

Key Findings and Methodology

• Galaxy Selection and Properties: The paper focuses on four significant quiescent galaxies, among which a pair is newly identified at $z=4.62$. These galaxies exhibit Balmer absorption lines typical of post-starburst galaxies, indicating a cessation of star formation within recent cosmic epochs. High stellar metallicities and compact sizes are common traits, with measured metallicities indicating a range from sub-Solar to significantly above Solar.
• Star Formation Histories (SFHs): The paper utilizes full-spectral-fitting techniques to infer SFHs, revealing varied formation epochs spanning redshifts $5.5 < z < 11$. The SFH analysis suggests that these galaxies experienced intense star-forming periods followed by rapid quenching.
• Comparison with $\Lambda$-CDM Cosmology: Utilizing extreme value statistics (EVS), the authors compare the most-massive halos expected in their survey's volume against the inferred galaxy masses. Their results indicate that while high stellar fractions (approaching 100%) are necessary, these galaxies do not violate the $\Lambda$-CDM framework. This underscores a need for advanced baryonic physics that drive such efficient early star formation.

Implications and Future Work

The findings imply a more intricate galaxy formation scenario in the early Universe, likely needing revisions to models of star formation efficiency and feedback mechanisms in massive galaxies. The documentation of sizes and stellar densities provides foundational data for further studies into how such compact systems evolve into local massive elliptical galaxies.

The authors suggest that future work should explore understanding the progenitors of these galaxies, particularly at the redshifts where their formation peaks. Moreover, the EXCELS dataset offers a rich prospect for exploring broader galaxy demographics and refining cosmological models in light of newfound data.

Speculations on Future Developments

In the domain of observational cosmology, this work offers a crucial step towards unearthing the complexities of early star formation and galaxy evolution. The precise measurements obtained with JWST, combined with the application of advanced statistical approaches like EVS, create a pathway to reconciling observational evidence with theoretical constructs. As more data becomes available, particularly from similar high-redshift surveys, there will likely be enhanced understanding of the constraints on dark matter halo masses and the processes converting baryonic matter to stellar structures.

Future observational campaigns could focus on retrieving data at even shorter wavelengths to capture epochs nearer to reionization, providing further constraints on models of early Universe formation. Additionally, extending this analytical framework to different environments and lower stellar mass ranges could illuminate the dynamics of less massive, but perhaps equally intriguing, quiescent systems.

This paper sets a benchmark for future such studies, emphasizing the need for interdisciplinary approaches in astrophysics, blending precision observation with robust statistical and theoretical modeling.