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We study the quiescent ultradiffuse galaxy FCC 224 in the Fornax cluster using Hubble Space Telescope (HST) imaging, motivated by peculiar properties of its globular cluster (GC) system revealed in shallower imaging. The surface brightness fluctuation distance of FCC 224 measured from HST is 18.6 ± 2.7 Mpc, consistent with the Fornax cluster distance. We use Prospector to infer the stellar population from a combination of multiwavelength photometry (HST, ground-based, Wide-field Infrared Survey Explorer) and Keck Cosmic Web Imager spectroscopy. The galaxy has a mass-weighted age of ∼10 Gyr, metallicity [M/H] of ∼ −1.25 dex, and a very short formation e-folding time of τ ∼ 0.3 Gyr. Its 12 candidate GCs exhibit highly homogeneous g_475−I_814 colors, merely 0.04 mag bluer than the diffuse starlight, which supports a single-burst formation scenario for this galaxy. We confirm a top-heavy GC luminosity function, similar to the two dark matter deficient galaxies NGC 1052-DF2 and DF4. However, FCC 224 differs from those galaxies with relatively small GC sizes of ∼3 pc (∼35% smaller than typical for other dwarfs), and with radial mass segregation in its GC system. We are not yet able to identify a formation scenario to explain all of the GC properties in FCC 224. Follow-up measurements of the dark matter content in FCC 224 will be crucial because of the mix of similarities and differences among FCC 224, DF2, and DF4. 

Chip-scale integrated imaging spectrometers show significant potential for high-performance spectral analysis due to advancements in fabrication and computational techniques. Many practical applications, such as astronomy and molecular spectroscopy, require analyzing light at sub-nanowatt levels, where inherent enhancement in spectrometer signals can reduce the need for expensive photodetectors or long integration time. Previously, we introduced an integrated spectrometer scheme using machine learning to reconstruct spectra from imaging the wavelength-dependent patterns scattered out of a multimode interference (MMI) waveguide. In this work, we report a signal enhancement of 13.6 dB and an increase of device sensitivity and dynamic range by 15 dB by selective roughening of the waveguide surface via plasma etching. By imaging interference patterns at various points along the waveguide, we determine that the best spectrometer performance is achieved by imaging MMI sections with highest pattern variation. We report accurate spectral measurements using convolutional neural network-based spectral reconstruction with 1 nm resolution at input powers as low as 300 pW for the present experimental configuration, and a scattering coefficient of 1.109 cm^-1from the etched section. 

Abstract Integral field spectroscopy (IFS) is a powerful tool for understanding the formation of galaxies across cosmic history. We present the observing strategy and first results of MSA-3D, a novel JWST program using multi-object spectroscopy in a slit-stepping strategy to produce IFS data cubes. The program observed 43 normal star-forming galaxies at redshifts 0.5 ≲z≲ 1.5, corresponding to the epoch when spiral thin-disk galaxies of the modern Hubble sequence are thought to emerge, obtaining kiloparsec-scale maps of rest-frame optical nebular emission lines with spectral resolutionR≃ 2700. Here we describe the multiplexed slit-stepping method, which is >15 times more efficient than the NIRSpec IFS mode for our program. As an example of the data quality, we present a case study of an individual galaxy atz= 1.104 (stellar massM_*= 10^10.3M_⊙, star formation rate, SFR = 3M_⊙yr⁻¹) with prominent face-on spiral structure. We show that the galaxy exhibits a rotationally supported disk with moderate velocity dispersion ( $\sigma =36_{-4}^{+5}$km s⁻¹), a negative radial metallicity gradient (−0.020 ± 0.002 dex kpc⁻¹), a dust attenuation gradient, and an exponentially decreasing SFR density profile that closely matches the stellar continuum. These properties are characteristic of local spirals, indicating that mature galaxies are in place atz∼ 1. We also describe the customized data reduction and original cube-building software pipelines that we have developed to exploit the powerful slit-stepping technique. Our results demonstrate the ability of JWST slit-stepping to study galaxy populations at intermediate to high redshifts, with data quality similar to current surveys of thez∼ 0.1 Universe. 

Abstract The radial gradient of gas-phase metallicity is a powerful probe of the chemical and structural evolution of star-forming galaxies, closely tied to disk formation and gas kinematics in the early Universe. We present spatially resolved chemical and dynamical properties for a sample of 25 galaxies at 0.5 ≲ z ≲ 1.7 from theMSA-3Dsurvey. These innovative observations provide 3D spectroscopy of galaxies at a spatial resolution approaching JWST’s diffraction limit and a high spectral resolution ofR ≃ 2700. The metallicity gradients measured in our galaxy sample range from −0.03 to 0.02 dex kpc⁻¹. Most galaxies exhibit negative or flat radial gradients, indicating lower metallicity in the outskirts or uniform metallicity throughout the entire galaxy. We confirm a tight relationship between stellar mass and metallicity gradient atz ∼ 1 with small intrinsic scatter of 0.02 dex kpc⁻¹. Our results indicate that metallicity gradients become increasingly negative as stellar mass increases, likely because the more massive galaxies tend to be more “disky.” This relationship is consistent with the predictions from cosmological hydrodynamic zoom-in simulations with strong stellar feedback. This work presents the effort to harness the multiplexing capability of the JWST NIRSpec microshutter assembly in slit-stepping mode to map the chemical and kinematic profiles of high-redshift galaxies in large samples and at high spatial and spectral resolution. 

Spectral analysis of light is one of the oldest and most versatile scientific methods and the basis of countless techniques and instruments. Miniaturized spectrometers have recently seen great advances, but challenges remain before they are widely deployed. We report an integrated photonic spectrometer that achieves high performance with minimal component complexity by combining imaging of light propagation patterns in multi-mode interference waveguides with machine learning analysis. We demonstrate broadband operation in the visible and near-infrared, 0.05 nm spectral resolution, and an array of four spectrometers on a single chip. Two canonical applications are implemented: spectral analysis of the solar spectrum with neural network reconstruction and detection of Rayleigh scattering from microbeads on an optofluidic chip using principal component classification. These results illustrate the potential of this approach for high-performance spectroscopy across disciplines. 

ABSTRACT We have re-observed $$\rm \sim$$40 low-inclination, star-forming galaxies from the MaNGA survey (σ ∼ 65 km s−1) at ∼6.5 times higher spectral resolution (σ ∼ 10 km s−1) using the HexPak integral field unit on the WIYN 3.5-m telescope. The aim of these observations is to calibrate MaNGA’s instrumental resolution and to characterize turbulence in the warm interstellar medium and ionized galactic outflows. Here we report the results for the Hα region observations as they pertain to the calibration of MaNGA’s spectral resolution. Remarkably, we find that the previously reported MaNGA line-spread-function (LSF) Gaussian width is systematically underestimated by only 1 per cent. The LSF increase modestly reduces the characteristic dispersion of H ii regions-dominated spectra sampled at 1–2 kpc spatial scales from 23 to 20 km s−1 in our sample, or a 25 per cent decrease in the random-motion kinetic energy. This commensurately lowers the dispersion zeropoint in the relation between line-width and star-formation rate surface-density in galaxies sampled on the same spatial scale. This modest zero-point shift does not appear to alter the power-law slope in the relation between line-width and star-formation rate surface-density. We also show that adopting a scheme whereby corrected line-widths are computed as the square root of the median of the difference in the squared measured line width and the squared LSF Gaussian avoids biases and allows for lower signal-to-noise data to be used reliably. 

Abstract Despite the importance of active galactic nuclei (AGNs) in galaxy evolution, accurate AGN identification is often challenging, as common AGN diagnostics can be confused by contributions from star formation and other effects (e.g., Baldwin–Phillips–Terlevich diagrams). However, one promising avenue for identifying AGNs is “coronal emission lines” (“CLs”), which are highly ionized species of gas with ionization potentials ≥100 eV. These CLs may serve as excellent signatures for the strong ionizing continuum of AGNs. To determine if CLs are in fact strong AGN tracers, we assemble and analyze the largest catalog of optical CL galaxies using the Sloan Digital Sky Survey's Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) catalog. We detect CL emission in 71 MaNGA galaxies, out of the 10,010 unique galaxies from the final MaNGA catalog, with ≥5σconfidence. In our sample, we measure [Nev]λ3347,λ3427, [Fevii]λ3586,λ3760,λ6086, and [Fex]λ6374 emission and crossmatch the CL galaxies with a catalog of AGNs that were confirmed with broad-line, X-ray, IR, and radio observations. We find that [Nev] emission, compared to [Fevii] and [Fex] emission, is best at identifying high-luminosity AGNs. Moreover, we find that the CL galaxies with the least dust extinction yield the most iron CL detections. We posit that the bulk of the iron CLs are destroyed by dust grains in the galaxies with the highest [Oiii] luminosities in our sample, and that AGNs in the galaxies with low [Oiii] luminosities are possibly too weak to be detected using traditional techniques.