Table of contents

We present the results of our systematic search for the reddest far-infrared (FIR) and submillimeter (sub-mm) galaxies using the data from the Herschel Multi-tiered Extragalactic Survey (HerMES) and the SCUBA2 Cosmological Legacy Survey (S2CLS). The red FIR galaxies are "500 μm risers," whose spectral energy distributions increase with wavelength across the three FIR passbands of the Spectral and Photometric Imaging REceiver (SPIRE) of Herschel. Within 106.5 deg² of the HerMES fields, we have selected 629 500 μm risers. The red sub-mm galaxies are "SPIRE drop-outs," which are prominent detections in the S2CLS 850 μm data but are extremely weak or invisible in the SPIRE bands. Within the 2.98 deg² common area of HerMES and S2CLS, we have selected 95 such objects. These very red sources could be dusty starbursts at high redshifts (z ≳ 4–6) because the peak of their cold-dust emission heated by star formation is shifted to the reddest FIR/sub-mm bands. The surface density of 500 μm risers is ∼8.2 deg⁻² at the ≥20 mJy level in 500 μm, while that of SPIRE drop-outs is ∼19.3 deg⁻² at the ≥5 mJy level in 850 μm. Both types of objects could span a wide range of redshifts, however. Using deep radio data in these fields to further select the ones likely at the highest redshifts, we find that the surface density of z > 6 candidates is 5.5 deg⁻² among 500 μm risers and is 0.8–13.6 deg⁻² among SPIRE drop-outs. If this is correct, the dust-embedded star formation processes in such objects could contribute comparably as Lyman-break galaxies to the global SFR density at z > 6.

The overwhelming foreground causes severe contamination on the detection of 21 cm signal during the Epoch of Reionization (EoR). Among various foreground components, the Galactic free–free emission is less studied, so that its impact on the EoR observation remains unclear. To better constrain this emission, we perform Monte Carlo simulation of Hα emission, which comprises direct and scattered Hα radiation from H ii regions and warm ionized medium (WIM). The positions and radii of H ii regions are quoted from the Wide-Field Infrared Survey Explorer H ii catalog, and the WIM is described by an axisymmetric model. The scattering is off dust and free electrons that are realized by applying an exponential fitting to the HI4PI H i map and an exponential disk model, respectively. The simulated Hα intensity, the Simfast21 software, and the latest SKA1-Low layout configuration are employed to simulate the SKA "observed" images of Galactic free–free emission and the EoR signal. By analyzing the one-dimensional power spectra, we find that the Galactic free–free emission can be about 10^5.4–10^2.1, 10^5.0–10^1.7, and 10^4.3–10^1.1 times more luminous than the EoR signal on scales of $0.1\,{\mathrm{Mpc}}^{-1}\lt k\lt 2\,{\mathrm{Mpc}}^{-1}$ in the 116–124, 146–154, and 186–194 MHz frequency bands, respectively. We further calculate the two-dimensional power spectra inside the EoR window and show that the power leaked by Galactic free–free emission can still be significant, as the power ratios can reach about 110%–8000%, 30%–2400%, and 10%–250% on scales of $0.5\,{\mathrm{Mpc}}^{-1}\lesssim k\lesssim 1\,{\mathrm{Mpc}}^{-1}$ in three frequency bands. Therefore, we indicate that the Galactic free–free emission should be carefully treated in future EoR detections.

This paper documents the 16th data release (DR16) from the Sloan Digital Sky Surveys (SDSS), the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the Southern Hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey and new data from the SPectroscopic IDentification of ERosita Survey programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).

The design and implementation of a new framework for adaptive mesh refinement calculations are described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design enables its use for a wide variety of physics. The framework works with both uniform and nonuniform grids in Cartesian and curvilinear coordinate systems. It adopts a dynamic execution model based on a simple design called a "task list" that improves parallel performance by overlapping communication and computation, simplifies the inclusion of a diverse range of physics, and even enables multiphysics models involving different physics in different regions of the calculation. We describe physics modules implemented in this framework for both nonrelativistic and relativistic magnetohydrodynamics (MHD). These modules adopt mature and robust algorithms originally developed for the Athena MHD code and incorporate new extensions: support for curvilinear coordinates, higher-order time integrators, more realistic physics such as a general equation of state, and diffusion terms that can be integrated with super-time-stepping algorithms. The modules show excellent performance and scaling, with well over 80% parallel efficiency on over half a million threads. The source code has been made publicly available.

We present speculator—a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating spectra, we use a principal component analysis to construct a set of basis functions and neural networks to learn the basis coefficients as a function of the SPS model parameters. For photometry, we parameterize the magnitudes (for the filters of interest) as a function of SPS parameters by a neural network. The resulting emulators are able to predict spectra and photometry under both simple and complicated SPS model parameterizations to percent-level accuracy, giving a factor of 10³–10⁴ speedup over direct SPS computation. They have readily computable derivatives, making them amenable to gradient-based inference and optimization methods. The emulators are also straightforward to call from a GPU, giving an additional order of magnitude speedup. Rapid SPS computations delivered by emulation offers a massive reduction in the computational resources required to infer the physical properties of galaxies from observed spectra or photometry and simulate galaxy populations under SPS models, while maintaining the accuracy required for a range of applications.

The interstellar oxygen isotopic ratio of ¹⁸O/¹⁷O can reflect the relative amount of the secular enrichment by ejecta from high-mass versus intermediate-mass stars. Previous observations found a Galactic gradient of ¹⁸O/¹⁷O, i.e., low ratios in the Galactic center and large values in the Galactic disk, which supports the inside-out formation scenario of our Galaxy. However, there are not many observed objects and, in particular, there are not many at large galactocentric distances. For this reason, we started a systematic study on Galactic interstellar ¹⁸O/¹⁷O, through observations of C¹⁸O and C¹⁷O multi-transition lines toward a large sample of 286 sources (at least one order of magnitude larger than previous ones), from the Galactic center region to the far outer Galaxy (∼22 kpc). In this article, we present our observations of J = 1–0 lines of C¹⁸O and C¹⁷O, with the 12 m antenna of the Arizona Radio Observatory (ARO 12 m) and the Institut de Radio Astronomie Millimétrique (IRAM) 30 m telescopes. Among our IRAM 30 m sample of 50 targets, we detected successfully both C¹⁸O and C¹⁷O 1–0 lines for 34 sources. Similarly, our sample of 260 targets for ARO 12 m observations resulted in the detection of both lines for 166 sources. The C¹⁸O optical depth effect on our ratio results, evaluated by fitting results of C¹⁷O spectra with hyperfine components (assuming ${\tau }_{C18O}=4{\tau }_{C17O}$) and our radiative transfer and excitation model nonlocal thermodynamic equilibrium (non-LTE) model calculation for the strongest source, was found to be insignificant. Beam dilution does not seem to be a problem either, which was supported by the fact that there is no systematic variation between the isotopic ratio and the heliocentric distance, and ratios are consistently measured from two telescopes for most of those detected sources. With this study we obtained ¹⁸O/¹⁷O isotopic ratios for a large sample of molecular clouds with different galactocentric distances. Our results, though there are still very few detections made for sources in the outer Galaxy, confirm the apparent ¹⁸O/¹⁷O gradient of ¹⁸O/¹⁷O=(0.10 ± 0.03)R_GC+(2.95 ± 0.30), with a Pearson's rank correlation coefficient of R = 0.69. This is supported by the newest Galactic chemical evolution model including the impact of massive stellar rotators and novae. Our future J = 2–1 and J = 3–2 observations of C¹⁸O and C¹⁷O toward the same sample would be important to determine their physical parameters (opacities, abundances, etc.) and further accurately determine the Galactic radial gradient of the isotopic ratio ¹⁸O/¹⁷O.

Stellar ages play a crucial role in understanding the formation and evolution of stars and Galaxies, which pose many challenges while determining in practice. In this paper, we have introduced a new machine-learning method, Gaussian process regression (GPR), to estimate the stellar ages, which is different from the traditional isochrone fitting method, which fully utilizes the information provided by previous studies. To demonstrate the performance of our method, we have applied it to the field stars of two important phases of evolution, main-sequence turn-off (MSTO) stars and giants, whose ages and masses are available in the literature. Also, GPR is applied to the red giants of open clusters (e.g., M67). Results showed that the ages given by GPR are in better agreement with those given by isochrone fitting methods. The ages are also estimated from various other machine-learning methods (e.g., support vector regression, neural networks, and random forest) and are compared with GPR, which resulted in GPR outperforming others. In addition to ages, we have applied GPR to estimate the masses of the MSTO stars and red giants and found that the masses predicted by GPR for the red giants are within acceptable uncertainties of masses derived from the asteroseismic scaling relation. We have provided the constraints on the input parameters to GPR, which decides the accuracy of the output ages and masses. Results conclude that the newly introduced GPR is promising to provide a novel approach to estimate stellar ages and masses in the era of big data sets. As a supplement, masses and ages for the MSTO stars and red giants estimated from GPR are provided as a catalog that could be used as a training set for upcoming large data sets with spectroscopic parameters.

Software has been a crucial contributor to scientific progress in astronomy for decades, but practices that enable machine-actionable citations have not been consistently applied to software itself. Instead, software citation behaviors developed independently from standard publication mechanisms and policies, resulting in human-readable citations that remain hidden over time and that cannot represent the influence software has had in the field. These historical software citation behaviors need to be understood in order to improve software citation guidance and develop relevant publishing practices that fully support the astronomy community. To this end, a 23 year retrospective analysis of software citation practices in astronomy was developed. Astronomy publications were mined for 410 aliases associated with nine software packages and analyzed to identify past practices and trends that prevent software citations from benefiting software authors.

Binary evolution is indispensable in stellar evolution to understand the formation and evolution of most peculiar and energetic objects, such as binary compact objects, Type Ia supernovae, X-ray binaries, cataclysmic variables, blue stragglers, hot subdwarfs, and central binaries in planetary nebulae. Mass transfer in binary stars can change the evolutionary path and fate of the components compared to what is expected from single stellar evolution. The critical mass ratio at which unstable mass transfer occurs is an unsolved fundamental problem in binary evolution. To resolve this issue, we construct the thermal equilibrium mass-loss model and derive critical mass ratios for both thermal-timescale mass transfer and unstable mass transfer, the latter of which occurs when the outer Lagrangian point, L₂, is overfilled. Using several 3.2 M_⊙ stellar models as examples, we study the stellar response to thermal equilibrium mass loss and present the thresholds for thermal-timescale mass transfer. We study the possible mass-transfer channels of binary systems containing a 3.2 M_⊙ donor star, taking into account thermal-timescale mass transfer, unstable mass transfer through L₂, and dynamical-timescale mass transfer. We repeat this simulation for a grid of donor stars with different masses (from 0.1 to 100 M_⊙ with Z = 0.02) and at different evolutionary stages, and present our results. The results show that unstable mass transfer due to the overfilling of the outer Lagrangian point may also play an essential role in the formation of common envelopes for late red giant branch and asymptotic giant branch donors.

In this study, we examine whether the First-Order Taylor Expansion (FOTE) method can be applied to steady-state plasma flow fields in space. We particularly examine whether this method (termed FOTE-V) can be used to identify the flow critical points (including both stagnation point and vortex center) and reconstruct the flow patterns around these points. Quantitatively, we test the accuracy of this method using 3D kinetic simulation data, and find the FOTE-V method can give accurate reconstruction results within an area about 2 times the size of the spacecraft tetrahedron, particularly when there are no clear nonlinear flow structures in the simulation box. With simulation data, we also reveal the ability of the FOTE-V method on reconstructing 3D flow field topology of both radial-type null and spiral-type nulls. We further test the accuracy of this method using measurements from NASA's Magnetospheric Multi-scale (MMS) mission. In a current sheet crossing event, the FOTE-V method successfully identifies the spiral-type nulls in the reconnection exhaust region. In an EDR crossing event, the FOTE-V method detects the stagnation point near the reconnection center. We find these 3D flow structures are quasi-linear at the MMS separation scale. Utilizing the continuity equation of the steady flow, we define a parameter, $\alpha =\tfrac{{\rm{\nabla }}\cdot \left(n{\boldsymbol{V}}\right)}{{\rm{\nabla }}\times \left(n{\boldsymbol{V}}\right)}$, to quantify the error of this method—the smaller this parameter the better the results. This study demonstrates that the plasma flows at small scale are indeed linear, and thus the FOTE-V method can be applied to such flow fields. In particular, this method will be useful to study stagnation points and electron vortices in space plasmas.

Filaments are very common physical phenomena on the Sun and are often taken as important proxies of solar magnetic activities. The study of filaments has become a hot topic in the space weather research. For a more comprehensive understanding of filaments, especially for an understanding of solar activities of multiple solar cycles, it is necessary to perform a combined multifeature analysis by constructing a data set of multiple solar cycle data. To achieve this goal, we constructed a centennial data set that covers the Hα data from five observatories around the world. During the data set construction, we encountered varieties of problems, such as data fusion, accurate determination of the solar edge, classifying data by quality, dynamic threshold, and so on, which arose mainly due to multiple sources and a large time span of data. But fortunately, these problems were well solved. The data set includes seven types of data products and eight types of feature parameters with which we can implement the functions of data searching and statistical analyses. It has the characteristics of better continuity and highly complementary to space observation data, especially in the wavelengths not covered by space observations, and covers many solar cycles (including more than 60 yr of high-cadence data). We expect that this new comprehensive data set as well as the tools will help researchers to significantly speed up their search for features or events of interest, for either statistical or case study purposes, and possibly help them get a better and more comprehensive understanding of solar filament mechanisms.

Future surveys focusing on understanding the nature of dark energy (e.g., Euclid and WFIRST) will cover large fractions of the extragalactic sky in near-IR slitless spectroscopy. These surveys will detect a large number of galaxies that will have only one emission line in the covered spectral range. In order to maximize the scientific return of these missions, it is imperative that single emission lines are correctly identified. Using a supervised machine-learning approach, we classified a sample of single emission lines extracted from the WFC3 IR Spectroscopic Parallel survey, one of the closest existing analogs to future slitless surveys. Our automatic software integrates a spectral energy distribution (SED)-fitting strategy with additional independent sources of information. We calibrated it and tested it on a "gold" sample of securely identified objects with multiple lines detected. The algorithm correctly classifies real emission lines with an accuracy of 82.6%, whereas the accuracy of the SED-fitting technique alone is low (∼50%) due to the limited amount of photometric data available (≤6 bands). While not specifically designed for the Euclid and WFIRST surveys, the algorithm represents an important precursor of similar algorithms to be used in these future missions.

Several studies have shown the importance of electromagnetic ion cyclotron (EMIC) waves to the pitch angle scattering of energetic particles in the radiation belt, especially relativistic electrons, thus contributing to their net loss from the outer radiation belt to the upper atmosphere. The huge amount of data collected thus far provides us with the opportunity to use a deep learning technique referred to as the Bag-of-Features (BoF). When applied to images of magnetic field spectrograms in the frequency range of EMIC waves, the BoF allows us to distinguish, in a semi-automated way, several patterns in these spectrograms that can be relevant to describe physical aspects of EMIC waves. Each spectrogram image provided as an input to the BoF corresponds to the windowed Fourier transform of a ∼40 minutes to 1 hour interval of Van Allen Probes' high time-resolution vector magnetic field observations. Our data set spans the 2012 September 8 to 2016 December 31 period and is at geocentric distances larger than 3 Earth radii. A total of 66,204 spectrogram images are acquired in this interval, and about 45% of them, i.e., 30,190 images, are visually inspected to validate the BoF technique. The BoF's performance in identifying spectrograms with likely EMIC wave signatures is comparable to the visual inspection method, with the enormous advantage that the BoF technique greatly expedites the analysis by accomplishing the task in just a few minutes.

A large number of observations from the Parkes 64 m diameter radio telescope, recorded with high time resolution, are publicly available. We have reprocessed all of the observations obtained during the first four years (from 1997–2001) of the Parkes Multibeam Receiver system in order to identify transient events, and have built a database that records the 568,736,756 pulse candidates generated during this search. We have discovered a new fast radio burst (FRB), FRB 010305, with a dispersion measure (DM) of 350 ± 5 cm⁻³ pc and explored why so few FRBs have been discovered in data prior to 2001. After accounting for the dispersion smearing across the channel bandwidth and the sky regions surveyed, the number of FRBs is found to be consistent with model predictions. We also present five single pulse candidates from unknown sources, but with Galactic DMs. We extract a diverse range of sources from the database, which can be used, for example, as a training set of data for new software being developed to search for FRBs in the presence of radio frequency interference.

From Hubble Space Telescope/Cosmic Origins Spectrograph spectra of five quasars, 16 outflows are detected. For 11 outflows, we are able to constrain their distances to the central source (R) and their energetics. In instances of multiple electron number density determinations (used in the calculation of R) for the same outflow, the values are consistent within errors. For the 11 outflows, eight have measurements for R (between 10 and 1000 pc), one has a lower limit, another has an upper limit, and the last has a range in R. There are two outflows that have enough kinetic luminosity to be major contributors to active galactic nucleus feedback. The outflowing mass is found primarily in a very high-ionization phase, which is probed using troughs from, e.g., Ne viii, Na ix, Mg x, and Si xii. Such ions connect the physical conditions of these ultraviolet outflows to the X-ray warm absorber outflows seen in nearby Seyfert galaxies. The ion Cl vii and several new transitions from Ne v have been detected for the first time.

Searches for gravitational microlensing events are traditionally concentrated on the central regions of the Galactic bulge but many microlensing events are expected to occur in the Galactic plane, far from the Galactic Center. Owing to the difficulty in conducting high-cadence observations of the Galactic plane over its vast area, which are necessary for the detection of microlensing events, their global properties were hitherto unknown. Here, we present results of the first comprehensive search for microlensing events in the Galactic plane. We searched an area of almost 3000 square degrees along the Galactic plane ($| b| \lt 7^\circ$, 0° < l < 50°, 190° < l < 360°) observed by the Optical Gravitational Lensing Experiment (OGLE) during 2013–2019 and detected 630 events. We demonstrate that the mean Einstein timescales of Galactic plane microlensing events are on average three times longer than those of Galactic bulge events, with little dependence on the Galactic longitude. We also measure the microlensing optical depth and event rate as a function of Galactic longitude and demonstrate that they exponentially decrease with the angular distance from the Galactic Center (with the characteristic angular scale length of 32°). The average optical depth decreases from 0.5 × 10⁻⁶ at l = 10° to 1.5 × 10⁻⁸ in the Galactic anticenter. We also find that the optical depth in the longitude range 240° < l < 330° is asymmetric about the Galactic equator, which we interpret as a signature of the Galactic warp.

We present measurements of the spectral properties for a total of 526,265 quasars, out of which 63% have a continuum signal-to-noise ratio > 3 pixel⁻¹, selected from the fourteenth data release of the Sloan Digital Sky Survey (SDSS-DR14) quasar catalog. We performed a careful and homogeneous analysis of the SDSS spectra of these sources to estimate the continuum and line properties of several emission lines such as Hα, Hβ, Hγ, Mg ii, C iii], C iv, and Lyα. From the derived emission line parameters, we estimated single-epoch virial black hole masses (M_BH) for the sample using Hβ, Mg ii, and C iv emission lines. The sample covers a wide range in bolometric luminosity ($\mathrm{log}{L}_{\mathrm{bol}};$ erg s⁻¹) between 44.4 and 47.3 and $\mathrm{log}{M}_{\mathrm{BH}}$ between 7.1 and 9.9 M_⊙. Using the ratio of L_bol to the Eddington luminosity as a measure of the accretion rate, the logarithm of the accretion rate is found to be in the range between −2.06 and 0.43. We performed several correlation analyses between different emission line parameters and found them to match the correlation known earlier using smaller samples. We note that strong Fe ii sources with a large Balmer line width and highly accreting sources with large M_BH are rare in our sample. We make an extended and complete catalog available online that contains various spectral properties of 526,265 quasars derived in this work along with other properties culled from the SDSS-DR14 quasar catalog.

The number of known periodic variables has grown rapidly in recent years. Thanks to its large field of view and faint limiting magnitude, the Zwicky Transient Facility (ZTF) offers a unique opportunity to detect variable stars in the northern sky. Here, we exploit ZTF Data Release 2 (DR2) to search for and classify variables down to r ∼ 20.6 mag. We classify 781,602 periodic variables into 11 main types using an improved classification method. Comparison with previously published catalogs shows that 621,702 objects (79.5%) are newly discovered or newly classified, including ∼700 Cepheids, ∼5000 RR Lyrae stars, ∼15,000 δ Scuti variables, ∼350,000 eclipsing binaries, ∼100,000 long-period variables, and about 150,000 rotational variables. The typical misclassification rate and period accuracy are on the order of 2% and 99%, respectively. 74% of our variables are located at Galactic latitudes, $| b| \lt 10^\circ$. This large sample of Cepheids, RR Lyrae, δ Scuti stars, and contact (EW-type) eclipsing binaries is helpful to investigate the Galaxy's disk structure and evolution with an improved completeness, areal coverage, and age resolution. Specifically, the northern warp and the disk's edge at distances of 15–20 kpc are significantly better covered than previously. Among rotational variables, RS Canum Venaticorum and BY Draconis-type variables can be separated easily. Our knowledge of stellar chromospheric activity would benefit greatly from a statistical analysis of these types of variables.