Galaxy formation and evolution

Abstract:

ABSTRACT We investigate the unusual emission-line luminosity ratios observed in the JWST Deep Extragalactic Survey (JADES) NIRSpec spectroscopy of GN-z11, which reveal exceptionally strong emission lines and a significant detection of the rarely observed N iii] $\lambda 1748-1753$, multiplet. These features suggest an elevated N/O abundance, challenging existing models of stellar populations and nebular emission. To assess whether Wolf–Rayet (WR) stars can account for the observed line ratios, we construct a suite of stellar and nebular models incorporating high-resolution stellar spectral libraries, enabling a more accurate treatment of WR evolution and its influence on the ionizing radiation field. We find that the inclusion of WR stars is essential for reproducing the observed position of GN-z11 in the C iii]/He ii versus C iii]/C iv diagnostic plane, resolving discrepancies from previous studies. The model-derived metallicity (0.07 $\lesssim$ Z/Z$_{\odot }\lesssim$ 0.15), ionization parameter ($\log \, U$$\approx$−2), and stellar ages are consistent with the literature estimates. However, our models underpredict the N iii/O iii] ratio, suggesting that WR stars alone cannot fully explain the nitrogen enrichment. This suggests that additional mechanisms, such as rapid chemical enrichment in a young, metal-poor environment, may be necessary to explain the nitrogen excess. While our models successfully reproduce most observed line ratios, further refinements to the models are needed to fully characterize the stellar populations and the enrichment processes of high-redshift galaxies like GN-z11.

Abstract:

Abstract Adaptive binning is a crucial step in the analysis of large astronomical datasets, such as those from integral-field spectroscopy, to ensure a sufficient signal-to-noise ratio ($\mathcal {S/N}$) for reliable model fitting. However, the widely-used Voronoi-binning method and its variants suffer from two key limitations: they scale poorly with data size, often as $\mathcal {O}(N^2)$, creating a computational bottleneck for modern surveys, and they can produce undesirable non-convex or disconnected bins. I introduce PowerBin, a new algorithm that overcomes these issues. I frame the binning problem within the theory of optimal transport, for which the solution is a Centroidal Power Diagram (CPD), guaranteeing convex bins. Instead of formal CPD solvers, which are unstable with real data, I develop a fast and robust heuristic based on a physical analogy of packed soap bubbles. This method reliably enforces capacity constraints even for non-additive measures like $\mathcal {S/N}$ with correlated noise. I also present a new bin-accretion algorithm with $\mathcal {O}(N\log N)$ complexity, removing the previous bottleneck. The combined PowerBin algorithm scales as $\mathcal {O}(N\log N)$, making it about two orders of magnitude faster than previous methods on million-pixel datasets. I demonstrate its performance on a range of simulated and real data, showing it produces high-quality, convex tessellations with excellent $\mathcal {S/N}$ uniformity. The public Python implementation provides a fast, robust, and scalable tool for the analysis of modern astronomical data.

Abstract:

ABSTRACT Recent studies of gas kinematics at high redshift have reported discy systems that appear to challenge models of galaxy formation, but it is unclear whether they are representative of the underlying galaxy population. We present the first statistical sample of spatially resolved ionized gas kinematics at high redshift, comprised of 213 H $\alpha$ emitters in GOODS-S and GOODS-N at redshifts $z\approx 3.9\!-\!6.5$, observed with James Webb Space Telescope/NIRCam slitless spectroscopy and imaging from JADES, FRESCO, and CONGRESS. The sample probes two orders of magnitude in stellar mass ($\log (M_{\star }[\mathrm{M}_{\odot }])\approx 8\!-\!10$) and star formation rate ($\text{SFR}\approx 0.3\!-\!100\, \mathrm{M}_{\odot }\, \mathrm{yr}^{-1}$), and is representative down to $\log (M_{\star }[\mathrm{M}_{\odot }])\approx 9$. Using a novel inference tool, geko, we model the grism data to measure morphological and kinematic properties of the ionized gas, as probed by H $\alpha$. Our results are consistent with a decrease of the rotational support $v/\sigma _0$ and increase of the velocity dispersion $\sigma _0$ with redshift, when compared to $z< 3$, with $\sigma _0\approx 100$ km s$^{-1}$ and $v/\sigma _0\approx 1\!-\!2$ at $z\approx 3.9\!-\!6.5$. We study the relations between $\sigma _0$ and $v/\sigma _0$, and different star formation tracers and find a large scatter and diversity, with the most significant correlation between $\sigma _0$ and SFR. We find no evolution of the fraction of rotationally supported systems ($v/\sigma _0>1$) from $z\sim 5.5$ to $z\sim 4.5$, measured at $f=(34\pm 5){{\ \rm per\ cent}}$ in both redshift bins, for galaxies with masses $9<\log (M_{\star }[\mathrm{M}_{\odot }])< 10$. Overall, discs do not dominate the turbulent high-redshift galaxy population in the mass range probed by this work, but they remain a sizeable population. When placed in the context of studies up to cosmic noon, our results are consistent with a needed increase of disc-like systems with cosmic time.