We present DES16C3cje, a low-luminosity, long-lived type II supernova (SN II) at redshift 0.0618, detected by the Dark Energy Survey (DES). DES16C3cje is a unique SN. The spectra are characterized by extremely narrow photospheric lines corresponding to very low expansion velocities of less than or similar to 1500 km s(-1), and the light curve shows an initial peak that fades after 50 d before slowly rebrightening over a further 100 d to reach an absolute brightness of M-r similar to 15.5 mag. The decline rate of the late-time light curve is then slower than that expected from the powering by radioactive decay of Co-56, but is comparable to that expected from accretion power. Comparing the bolometric light curve with hydrodynamical models, we find that DES16C3cje can be explained by either (i) a low explosion energy (0.11 foe) and relatively large Ni-56 production of 0.075 M-circle dot from an similar to 15 M-circle dot red supergiant progenitor typical of other SNe II, or (ii) a relatively compact similar to 40 M-circle dot star, explosion energy of 1 foe, and 0.08 M-circle dot of Ni-56. Both scenarios require additional energy input to explain the late-time light curve, which is consistent with fallback accretion at a rate of similar to 0.5 x 10(-)(8) M-circle dot s(-1).

Robotic fiber positioner (RFP) arrays are becoming heavily adopted in wide-field massively multiplexed spectroscopic survey instruments. RFP arrays decrease nightly operational overheads through rapid reconfiguration between fields and exposures. In comparison to similar instruments, SDSS-V has selected a very dense RFP packing scheme where any point in a field is typically accessible to three or more robots. This design provides flexibility in target assignment. However, the task of collisionless trajectory planning is especially challenging. We present two multiagent distributed control strategies that are highly efficient and computationally inexpensive for determining collision-free paths for RFPs in heavily overlapping workspaces. We demonstrate that a reconfiguration path between two arbitrary robot configurations can be efficiently found if a "folded" state, in which all robot arms are retracted and aligned in a lattice-like orientation, is inserted between the initial and final states. Although developed for SDSS-V, the approach we describe is generic and thus applicable to a wide range of RFP designs and layouts. Robotic fiber positioner technology continues to advance rapidly, and in the near future ultra-densely packed RFP designs may be feasible. Our algorithms are especially capable in routing paths in very crowded environments, where we see efficient results even in regimes significantly more crowded than the SDSS-V RFP design.

There is a wide consensus that Type Ia supernovae (SNe Ia) originate from the thermonuclear explosion of CO white dwarfs (WDs), with the lack of hydrogen in the observed spectra as a distinctive feature. Here, we present supernova (SN) 2016jae, which was classified as an SN Ia from a spectrum obtained soon after its discovery. The SN reached a B-band peak of -17.93 +/- 0.34 mag, followed by a fast luminosity decline with s(BV)0.56 +/- 0.06 and inferred Delta m(15)(B) of 1.88 +/- 0.10 mag. Overall, the SN appears to be a 'transitional' event between a 'normal' SN Ia and a very dim SN Ia, such as 91bg-like SNe. Its peculiarity is that two late-time spectra, taken at +84 and +142 days after the peak, show a narrow line of H alpha (with full width at half maximum of similar to 650 and 1000 km s(-1), respectively). This is the third low-luminosity and fast-declining SN Ia, after SN2018cqj/ATLAS18qtd and SN2018fhw/ASASSN-18tb, found in the 100IAS survey to show a resolved narrow H alpha line in emission in its nebular-phase spectra. We argue that the nebular H alpha emission originates in an expanding hydrogen-rich shell (with velocity <= 1000 km s(-1)). The hydrogen shell velocity is too high to be produced during a common envelope phase, though it may be consistent with some material stripped from an H-rich companion star in a single-degenerate progenitor system. However, the derived mass of this stripped hydrogen is similar to 0.002-0.003 M-circle dot, which is much less than that expected (> 0.1 M-circle dot) from standard models for these scenarios. Another plausible sequence of events is a weak SN ejecta interaction with an H shell ejected by optically thick winds or a nova-like eruption on the CO WD progenitor some years before the SN explosion.

Many phenomenologically successful cosmological simulations employ kinetic winds to model galactic outflows. Yet systematic studies of how variations in kinetic wind scalings might alter observable galaxy properties are rare. Here we employ GADGET-3 simulations to study how the baryon cycle, stellar mass function, and other galaxy and CGM predictions vary as a function of the assumed outflow speed and the scaling of the mass-loading factor with velocity dispersion. We design our fiducial model to reproduce the measured wind properties at 25 per cent of the virial radius from the Feedback In Realistic Environments simulations. We find that a strong dependence of eta similar to sigma(5) in low-mass haloes with sigma < 106 km s(-1) is required to match the faint end of the stellar mass functions at z > 1. In addition, faster winds significantly reduce wind recycling and heat more halo gas. Both effects result in less stellar mass growth in massive haloes and impact high ionization absorption in halo gas. We cannot simultaneously match the stellar content at z = 2 and 0 within a single model, suggesting that an additional feedback source such as active galactic nucleus might be required in massive galaxies at lower redshifts, but the amount needed depends strongly on assumptions regarding the outflow properties. We run a 50 Mpch(-1), 2 x 576(3) simulation with our fiducial parameters and show that it matches a range of star-forming galaxy properties at z similar to 0-2.

APOGEE is a high-resolution (R similar to 22,000), near-infrared, multi-epoch, spectroscopic survey of the Milky Way. The second generation of the APOGEE project, APOGEE-2, includes an expansion of the survey to the Southern Hemisphere called APOGEE-2S. This expansion enabled APOGEE to perform a fully panoramic mapping of all of the main regions of the Milky Way; in particular, by operating in the H band, APOGEE is uniquely able to probe the dust-hidden inner regions of the Milky Way that are best accessed from the Southern Hemisphere. In this paper we present the targeting strategy of APOGEE-2S, with special attention to documenting modifications to the original, previously published plan. The motivation for these changes is explained as well as an assessment of their effectiveness in achieving their intended scientific objective. In anticipation of this being the last paper detailing APOGEE targeting, we present an accounting of all such information complete through the end of the APOGEE-2S project; this includes several main survey programs dedicated to exploration of major stellar populations and regions of the Milky Way, as well as a full list of programs contributing to the APOGEE database through allocations of observing time by the Chilean National Time Allocation Committee and the Carnegie Institution for Science. This work was presented along with a companion article, Beaton et al. (2021), presenting the final target selection strategy adopted for APOGEE-2 in the Northern Hemisphere.

The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is a dual-hemisphere, near-infrared (NIR), spectroscopic survey with the goal of producing a chemodynamical mapping of the Milky Way. The targeting for APOGEE-2 is complex and has evolved with time. In this paper, we present the updates and additions to the initial targeting strategy for APOGEE-2N presented in Zasowski et al. (2017). These modifications come in two implementation modes: (i) "Ancillary Science Programs" competitively awarded to Sloan Digital Sky Survey IV PIs through proposal calls in 2015 and 2017 for the pursuit of new scientific avenues outside the main survey, and (ii) an effective 1.5 yr expansion of the survey, known as the Bright Time Extension (BTX), made possible through accrued efficiency gains over the first years of the APOGEE-2N project. For the 23 distinct ancillary programs, we provide descriptions of the scientific aims, target selection, and how to identify these targets within the APOGEE-2 sample. The BTX permitted changes to the main survey strategy, the inclusion of new programs in response to scientific discoveries or to exploit major new data sets not available at the outset of the survey design, and expansions of existing programs to enhance their scientific success and reach. After describing the motivations, implementation, and assessment of these programs, we also leave a summary of lessons learned from nearly a decade of APOGEE-1 and APOGEE-2 survey operations. A companion paper, F. Santana et al. (submitted; AAS29036), provides a complementary presentation of targeting modifications relevant to APOGEE-2 operations in the Southern Hemisphere.

We present a state-of-the-art report on visualization in astrophysics. We survey representative papers from both astrophysics and visualization and provide a taxonomy of existing approaches based on data analysis tasks. The approaches are classified based on five categories: data wrangling, data exploration, feature identification, object reconstruction, as well as education and outreach. Our unique contribution is to combine the diverse viewpoints from both astronomers and visualization experts to identify challenges and opportunities for visualization in astrophysics. The main goal is to provide a reference point to bring modern data analysis and visualization techniques to the rich datasets in astrophysics.

The CNIa0.02 project aims to collect a complete, nearby sample of Type Ia supernovae (SNe Ia) light curves, and the SNe are volume-limited with host-galaxy redshifts z (host) < 0.02. The main scientific goal is to infer the distributions of key properties (e.g., the luminosity function) of local SNe Ia in a complete and unbiased fashion in order to study SN explosion physics. We spectroscopically classify any SN candidate detected by the All-Sky Automated Survey for Supernovae (ASAS-SN) that reaches a peak brightness <16.5 mag. Since ASAS-SN scans the full sky and does not target specific galaxies, our target selection is effectively unbiased by host-galaxy properties. We perform multiband photometric observations starting from the time of discovery. In the first data release (DR1), we present the optical light curves obtained for 247 SNe from our project (including 148 SNe in the complete sample), and we derive parameters such as the peak fluxes, Delta m (15), and s (BV) .

The Sloan Extension for Galactic Understanding and Exploration 2 (SEGUE-2) obtained 128,288 low-resolution spectra (R similar to 1800) of 118,958 unique stars in the first year of the Sloan Digital Sky Survey III (2008-2009). SEGUE-2 targeted prioritized distant halo tracers (blue horizontal-branch stars, K giants, and M giants) and metal-poor or kinematically hot populations. The main goal of SEGUE-2 was to target stars in the distant halo and measure their kinematics and chemical abundances to learn about the formation and evolution of the Milky Way. We present the SEGUE-2 field placement and target selection strategies. We discuss the success rate of the targeting based on the SEGUE-2 spectra and other spectroscopic and astrometric surveys. We describe the final SEGUE-2/SDSS-III improvements to the stellar parameter determinations based on the SEGUE Stellar Parameter Pipeline. We report a (g - i) color-effective temperature relation calibrated to the IRFM. We evaluate the accuracy and uncertainties associated with these stellar parameters by comparing with fundamental parameters, a sample of high-resolution spectra of SEGUE stars analyzed homogeneously, stars in well-studied clusters, and stars observed in common by the APOGEE survey. The final SEGUE spectra, calibration data, and derived parameters described here were released in SDSS-III Data Release 9 and continue to be included in all subsequent SDSS Data Releases. Because of its faint limiting magnitude and emphasis on the distant halo, the public SEGUE-2 data remain an important resource for the spectroscopy of stars in the Milky Way.

The Sloan Digital Sky Survey (SDSS) has recently initiated its fifth survey generation (SDSS-V), with a central focus on stellar spectroscopy. In particular, SDSS-V's Milky Way Mapper program will deliver multiepoch optical and near-infrared spectra for more than 5 x 10(6) stars across the entire sky, covering a large range in stellar mass, surface temperature, evolutionary stage, and age. About 10% of those spectra will be of hot stars of OBAF spectral types, for whose analysis no established survey pipelines exist. Here we present the spectral analysis algorithm, ZETA-PAYNE, developed specifically to obtain stellar labels from SDSS-V spectra of stars with these spectral types and drawing on machine-learning tools. We provide details of the algorithm training, its test on artificial spectra, and its validation on two control samples of real stars. Analysis with ZETA-PAYNE leads to only modest internal uncertainties in the near-IR with APOGEE (optical with BOSS): 3%-10% (1%-2%) for T-eff, 5%-30% (5%-25%) for v sin i, 1.7-6.3 km s(-1) (0.7-2.2 km s(-1)) for radial velocity, <0.1 dex (<0.05 dex) for log g, and 0.4-0.5 dex (0.1 dex) for [M/H] of the star, respectively. We find a good agreement between atmospheric parameters of OBAF-type stars when inferred from their high- and low-resolution optical spectra. For most stellar labels, the APOGEE spectra are (far) less informative than the BOSS spectra of these stars, while log g, v sin i, and [M/H] are in most cases too uncertain for meaningful astrophysical interpretation. This makes BOSS low-resolution optical spectra better for stellar labels of OBAF-type stars, unless the latter are subject to high levels of extinction.