This paper characterizes the actual science performance of the James Webb Space Telescope (JWST), as determined from the six month commissioning period. We summarize the performance of the spacecraft, telescope, science instruments, and ground system, with an emphasis on differences from pre-launch expectations. Commissioning has made clear that JWST is fully capable of achieving the discoveries for which it was built. Moreover, almost across the board, the science performance of JWST is better than expected; in most cases, JWST will go deeper faster than expected. The telescope and instrument suite have demonstrated the sensitivity, stability, image quality, and spectral range that are necessary to transform our understanding of the cosmos through observations spanning from near-earth asteroids to the most distant galaxies.

We present a comprehensive study of massive young stellar objects (YSOs) in the metal-poor galaxy NGC 6822 using IRAC and MIPS data obtained from the Spitzer Space Telescope. We find over 500 new YSO candidates in seven massive star-formation regions; these sources were selected using six colour-magnitude cuts. Via spectral energy distribution fitting to the data with YSO radiative transfer models we refine this list, identifying 105 high-confidence and 88 medium-confidence YSO candidates. For these sources we constrain their evolutionary state and estimate their physical properties. The majority of our YSO candidates are massive protostars with an accreting envelope in the initial stages of formation. We fit the mass distribution of the Stage I YSOs with a Kroupa initial mass function and determine a global star-formation rate of 0.039 M yr −1 . This is higher than star-formation rate estimates based on integrated UV fluxes. The new YSO candidates are preferentially located in clusters which correspond to seven active high-mass star-formation regions which are strongly correlated with the 8 and 24 µm emission from PAHs and warm dust. This analysis reveals an embedded high-mass star-formation region, Spitzer I, which hosts the highest number of massive YSO candidates in NGC 6822. The properties of Spitzer I suggest it is younger and more active than the other prominent H ii and star-formation regions in the galaxy.

Reward dysfunction is thought to be play a critical role in the pathogenesis of depression. Multiple studies have linked depression to abnormal neural sensitivity to monetary rewards, but it remains unclear whether this reward dysfunction is generalizable to other rewards types. The current study begins to address this gap by assessing abnormal sensitivity to both monetary and social rewards in relation to depressive symptoms. We recorded event-related potentials (ERPs) during two incentive delay tasks, one with monetary reward and one with social reward. Both tasks were administered within the same sample, enabling a direct comparison of reward types. ERPs elicited by social and nonsocial rewards were morphologically similar across several stages of processing: cue salience, outcome anticipation, early outcome evaluation, outcome salience. Moderation analyses showed depression was linked with a pattern of general deficits across social and monetary rewards, specifically for the stages of outcome anticipation (stimulus-preceding negativity) and outcome salience (feedback-P3); self-reported reward sensitivity was generally associated with early outcome evaluation (reward positivity). Regression analyses modeling task-specific variance, however, showed a unique association between depression and outcome salience for social rewards, controlling for monetary rewards. The findings from this study underscore the importance of assessing neural sensitivity to multiple reward types in depression, particularly social reward. Characterizing the profile of reward functioning in depression across reward types may help to link laboratory-based deficits to relatively global vs. focal difficulties in real-world functioning.

We present the classification of 197 point sources observed with the Infrared Spectrograph in the SAGE-Spec Legacy programme on the Spitzer Space Telescope. We introduce a decisiontree method of object classification based on infrared spectral features, continuum and spectral energy distribution shape, bolometric luminosity, cluster membership and variability information, which is used to classify the SAGE-Spec sample of point sources. The decision tree has a broad application to mid-infrared spectroscopic surveys, where supporting photometry and variability information are available. We use these classifications to make deductions about the stellar populations of the Large Magellanic Cloud and the success of photometric classification methods. We find 90 asymptotic giant branch (AGB) stars, 29 young stellar objects, 23 post-AGB objects, 19 red supergiants, eight stellar photospheres, seven background galaxies, seven planetary nebulae, two H II regions and 12 other objects, seven of which remain unclassified.

We investigate the occurrence of crystalline silicates in oxygen-rich evolved stars across a range of metallicities and mass-loss rates. It has been suggested that the crystalline silicate feature strength increases with increasing mass-loss rate, implying a correlation between lattice structure and wind density. To test this, we analyse Spitzer Infrared Spectrograph and Infrared Space Observatory Short Wavelength Spectrometer spectra of 217 oxygen-rich asymptotic giant branch and 98 red supergiants in the Milky Way, the Large and Small Magellanic Clouds, and Galactic globular clusters. These encompass a range of spectral morphologies from the spectrally rich which exhibit a wealth of crystalline and amorphous silicate features to 'naked' (dust-free) stars. We combine spectroscopic and photometric observations with the GRAMS grid of radiative transfer models to derive (dust) mass-loss rates and temperature. We then measure the strength of the crystalline silicate bands at 23, 28 and 33 µm. We detect crystalline silicates in stars with dust mass-loss rates which span over 3 dex, down to rates of ∼10 −9 M yr −1 . Detections of crystalline silicates are more prevalent in higher mass-loss rate objects, though the highest mass-loss rate objects do not show the 23-µm feature, possibly due to the low temperature of the forsterite grains or it may indicate that the 23-µm band is going into absorption due to high column density. Furthermore, we detect a change in the crystalline silicate mineralogy with metallicity, with enstatite seen increasingly at low metallicity.

The Mid-Infrared Instrument (MIRI) for the James Webb Space Telescope (JWST) will revolutionize our understanding of infrared stellar populations in the Local Volume. Using the rich Spitzer-IRS spectroscopic data-set and spectral classifications from the Surveying the Agents of Galaxy Evolution (SAGE)-Spectroscopic survey of over a thousand objects in the Magellanic Clouds, the Grid of Red supergiant and Asymptotic giant branch star ModelS (grams), and the grid of YSO models by Robitaille et al. (2006), we calculate the expected flux-densities and colors in the MIRI broadband filters for prominent infrared stellar populations. We use these fluxes to explore the JWST/MIRI colours and magnitudes for composite stellar population studies of Local Volume galaxies. MIRI colour classification schemes are presented; these diagrams provide a powerful means of identifying young stellar objects, evolved stars and extragalactic background galaxies in Local Volume galaxies with a high degree of confidence. Finally, we examine which filter combinations are best for selecting populations of sources based on their JWST colours.

The Infrared Spectrograph (IRS) on the Spitzer Space Telescope observed nearly 800 point sources in the Large Magellanic Cloud (LMC), taking over 1 000 spectra. 197 of these targets were observed as part of the SAGE-Spec Spitzer Legacy program; the remainder are from a variety of different calibration, guaranteed time and open time projects. We classify these point sources into types according to their infrared spectral features, continuum and spectral energy distribution shape, bolometric luminosity, cluster membership, and variability information, using a decisiontree classification method. We then refine the classification using supplementary information from the astrophysical literature. We find that our IRS sample is comprised substantially of YSO and H ii regions, post-Main Sequence low-mass stars: (post-)AGB stars and planetary nebulae and massive stars including several rare evolutionary types. Two supernova remnants, a nova and several background galaxies were also observed. We use these classifications to improve our understanding of the stellar populations in the Large Magellanic Cloud, study the composition and characteristics of dust species in a variety of LMC objects, and to verify the photometric classification methods used by mid-IR surveys. We discover that some widely-used catalogues of objects contain considerable contamination and others are missing sources in our sample.

The Magellanic clouds are uniquely placed to study the stellar contribution to dust emission. Individual stars can be resolved in these systems even in the mid-infrared, and they are close enough to allow detection of infrared excess caused by dust. We have searched the Spitzer Space Telescope data archive for all Infrared Spectrograph (IRS) staring-mode observations of the Small Magellanic Cloud (SMC) and found that 209 Infrared Array Camera (IRAC) point sources within the footprint of the Surveying the Agents of Galaxy Evolution in the Small Magellanic Cloud (SAGE-SMC) Spitzer Legacy programme were targeted, within a total of 311 staring mode observations. We classify these point sources using a decision tree method of object classification, based on infrared spectral features, continuum and spectral energy distribution shape, bolometric luminosity, cluster membership and variability information. We find 58 asymptotic giant branch (AGB) stars, 51 young stellar objects (YSOs), 4 post-AGB objects, 22 Red Supergiants (RSGs), 27 stars (of which 23 are dusty OB stars), 24 planetary nebulae (PNe), 10 Wolf-Rayet (WR) stars, 3 H ii regions, 3 R Coronae Borealis (R CrB) stars, 1 Blue Supergiant and 6 other objects, including 2 foreground AGB stars. We use these classifications to evaluate the success of photometric classification methods reported in the literature.