This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 survey that publicly releases infrared spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the subsurvey Time Domain Spectroscopic Survey data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey subsurvey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated value-added catalogs. This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper, Local Volume Mapper, and Black Hole Mapper surveys.

We present piXedfit, pixelized spectral energy distribution (SED) fitting, a Python package that provides tools for analyzing spatially resolved properties of galaxies using multiband imaging data alone or in combination with integral field spectroscopy (IFS) data. It has six modules that can handle all tasks in the spatially resolved SED fitting. The SED-fitting module uses the Bayesian inference technique with two kinds of posterior sampling methods: Markov Chain Monte Carlo (MCMC) and random dense sampling of parameter space (RDSPS). We test the performance of the SED-fitting module using mock SEDs of simulated galaxies from IllustrisTNG. The SED fitting with both posterior sampling methods can recover physical properties and star formation histories of the IllustrisTNG galaxies well. We further test the performance of piXedfit modules by analyzing 20 galaxies observed by the CALIFA and MaNGA surveys. The data are comprised of 12-band imaging data from the Galaxy Evolution Explorer, SDSS, 2MASS, and WISE and the IFS data from CALIFA or MaNGA. The piXedfit package can spatially match (in resolution and sampling) the imaging and IFS data. By fitting only the photometric SEDs, piXedfit can predict the spectral continuum, Dn 4000, H α , and H β well. The star formation rate derived by piXedfit is consistent with that derived from H α emission. The RDSPS method gives equally good fitting results as the MCMC and is much faster. As a versatile tool, piXedfit is equipped with a parallel computing module for efficient analysis of large data sets and will be made publicly available (https://github.com/aabdurrouf/piXedfit).

We investigate the relation between star formation rate (SFR) and stellar mass (M * ) in sub-galactic (∼ 1kpc) scale of 93 local (0.01 < z < 0.02) massive (M * > 10 10.5 M ) spiral galaxies. To derive spatially-resolved SFR and stellar mass, we perform so-called pixelto-pixel SED fitting, which fits an observed spatially-resolved multiband SED with a library of model SEDs using Bayesian statistics approach. We use 2 bands (FUV and NUV ) and 5 bands (u, g, r, i, and z) imaging data from Galaxy Evolution Explorer (GALEX) and Sloan Digital Sky Survey (SDSS), respectively. We find a tight nearly linear relation between the local surface density of SFR (Σ SFR ) and stellar mass (Σ * ) which has flattening in high Σ * . The near linear relation between Σ * and Σ SFR suggests constant sSFR throughout the galaxies, and the scatter of the relation is directly related to that of sSFR. Therefore, we analyse the variation of sSFR in various scales. More massive galaxies on average have lower sSFR throughout them than less massive galaxies. We also find that barred galaxies have lower sSFR in a core region than non-barred galaxies. However, in the outside region, sSFR of barred and non-barred galaxies are similar and lead to the similar total sSFR.

The gravitationally lensed star WHL 0137–LS, nicknamed Earendel, was identified with a photometric redshift z phot = 6.2 ± 0.1 based on images taken with the Hubble Space Telescope. Here we present James Webb Space Telescope (JWST) Near Infrared Camera images of Earendel in eight filters spanning 0.8–5.0 μm. In these higher-resolution images, Earendel remains a single unresolved point source on the lensing critical curve, increasing the lower limit on the lensing magnification to μ > 4000 and restricting the source plane radius further to r < 0.02 pc, or ∼4000 au. These new observations strengthen the conclusion that Earendel is best explained by an individual star or multiple star system and support the previous photometric redshift estimate. Fitting grids of stellar spectra to our photometry yields a stellar temperature of T eff ≃ 13,000–16,000 K, assuming the light is dominated by a single star. The delensed bolometric luminosity in this case ranges from log ( L ) = 5.8 to 6.6 L ⊙, which is in the range where one expects luminous blue variable stars. Follow-up observations, including JWST NIRSpec scheduled for late 2022, are needed to further unravel the nature of this object, which presents a unique opportunity to study massive stars in the first billion years of the universe.

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We study spatially resolved properties (on spatial scales of ∼1–2 kpc out to at least 3 effective radii) of the stars, dust, and gas in 10 nearby spiral galaxies. The properties of the stellar population and dust are derived by fitting the spatially resolved spectral energy distribution (SED) with more than 20 photometric bands ranging from far-ultraviolet to far-infrared. Our newly developed software piXedfit performs point-spread function matching of images, pixel binning, and models the stellar light, dust attenuation, dust emission, and emission from a dusty torus heated by an active galactic nucleus simultaneously through the energy-balance approach. With this self-consistent analysis, we present the spatially resolved version of the IRX–β relation, finding that it is consistent with the relationship from the integrated photometry. We show that the old stellar populations contribute to the dust heating, which causes an overestimation of the star formation rate (SFR) derived from the total ultraviolet and infrared luminosities on kiloparsec scales. With archival high-resolution maps of atomic and molecular gas, we study the radial variation of the properties of the stellar populations (including stellar mass, age, metallicity, and SFR), dust (including dust mass, dust temperature, and abundance of polycyclic aromatic hydrocarbon), and gas, as well as dust-to-stellar mass and dust-to-gas mass ratios. We observe a depletion of the molecular gas mass fraction in the central region of the majority of the galaxies, suggesting that the lack of available fuel is an important factor in suppressing the specific SFR at the center.

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This research is focused on the synthesis of a polystiren layer for biosensors based on a Quartz Crystal Microbalance sensor (QCM) to immobilize the biomolecule. The polystyrene thin film was deposited by means of spin coating method with various solvents, such as chloroform, toluene, xylene, and tetrahydrofuran (THF), containing a 3% polystyrene solution by mass. The morphologies of the polystyrene layers were observed via SEM/EDx. The polystyrene surface coated using chloroform as the solvent has a rougher morphology and the largest diameter pores compared with the other solvents. The result show the polystyrene surface coating produced with chloroform caused a higher frequency change, which resulted in the binding of a wider range of biomolecules.