Sazuna/UAT_keywords huggingface dataset:
Simulations of Global Solar Convection with a Fully Compressible CHORUS++ Code. Fluid-dynamics simulations of global solar convection are a critically important tool for assessing the dynamics of the solar interior. However, simulation studies with a fully compressible hydrodynamics code are not yet common. The Compressible High-Order Unstructured Spectral differencing (CHORUS++) code solves robustly and efficiently the fully compressible hydrodynamics equations using a compact local spectral method and semiunstructured grid system. Using the CHORUS++ code, we simulate the solar interior plasma flows from 0.7 to 0.99 of the solar radius using the values of the solar total luminosity and the sidereal rotation rate. In this paper, we analyze the simulated global flow structures before the statistically stable state to assess the compressibility of the plasma flows obtained with the fully compressible hydrodynamic code. The divergence of mass flux with the compressible model is overall small in the examined state before reaching the equilibrium state of the convection, which implies that the differences between the fully compressible flows and those obtained with the anelastic, incompressible, or linear-equation models are small in the simulated inner part of the convection zone. Although a fully relaxed stationary convection has not been achieved yet in the examined state, the model qualitatively reproduces the solar-type differential rotation. Simulations for longer periods are needed to achieve the system relaxation state. This work, assessing the early phase of the hydrodynamic evolution of solar convection, is our first step toward a better understanding of the nature of solar convection and the dynamo processes.

Keywords: Solar interior
An Advanced Identification Method for Gamma-Ray Bursts with Data and Feature Enhancements. Gamma-ray bursts (GRBs) are challenging to identify due to their transient nature, complex temporal profiles, and limited observational datasets. We address this with a one-dimensional convolutional neural network integrated with an adaptive frequency feature enhancement module and physics-informed data augmentation. Our framework generates 100,000 synthetic GRB samples, expanding training data diversity and volume while preserving physical fidelity—especially for low-significance events. The model achieves 97.46% classification accuracy, outperforming all tested variants with conventional enhancement modules, highlighting enhanced domain-specific feature capture. Feature visualization shows the model focuses on deep-seated morphological features and confirms the capability to extract physically meaningful burst characteristics. Dimensionality reduction and clustering reveal GRBs with similar morphologies or progenitor origins cluster in the feature space, linking learned features to physical properties. This perhaps offers a novel diagnostic tool for identifying kilonova- and supernova-associated GRB candidates, establishing criteria to enhance multimessenger early-warning systems. The framework aids current time-domain surveys, generalizes to other rare transients, and advances automated detection in large-volume observational data.

Keywords: Gamma-ray bursts, High energy astrophysics, Convolutional neural networks, Astronomy data analysis, Gamma-ray astronomy, Dimensionality reduction
An 11 yr Catalog of Gamma-Ray Transients: A Comprehensive Search with Fermi Gamma-Ray Burst Monitor Data. The Gamma-ray Burst Monitor (GBM) on board the Fermi Gamma-ray Space Telescope has produced the largest database of all-sky observations in gamma rays with its continuous data with high time and energy resolutions. These data contain a wealth of unidentified transient events that did not trigger the detectors for various reasons. We conducted extensive searches to identify such untriggered transient events observed by GBM during the 11 yr period of 2010 July─2021 June. In particular, we employed four different search modes with various energy ranges (mainly below 300 keV) and time resolutions (from 8 ms to 2 s), utilizing three statistical methods (signal-to-noise ratio, Poisson, and Bayesian statistics), each with different effectiveness in identifying specific classes of transients. Moreover, we developed algorithms for known event flagging as well as unknown event classification for our candidate events found in the searches. In this paper, we present our search methodologies, event flagging and classification algorithms, and the resulting comprehensive event catalog. The catalog contains more than a million events in total, including known events such as gamma-ray bursts, soft gamma repeater bursts, Galactic X-ray source activities, terrestrial gamma flashes, and solar flares. For each candidate event, the catalog presents the event time, detection significance, event duration, hardness ratios, known event flagging results, and classification probabilities. Our short-transient catalog significantly expands the currently existing list of known events and complements the GBM Trigger Catalog. The event database with filtering capabilities is also publicly available at https://magnetars.sabanciuniv.edu/gbm, which allows users to retrieve event information based on their input queries along with the event lightcurves.

Keywords: Gamma-ray transient sources, Astronomy databases
ACCEPT 2.0: A Compilation of X-Ray Gas Properties for Clusters of Galaxies Observed by the Chandra X-Ray Observatory. Archive of Chandra Cluster Entropy Profile Tables (ACCEPT) 2.0 is an updated library of uniformly produced measurements of 532 galaxy clusters based on Chandra archival data. It contains radial density, temperature, and entropy profiles for 377 galaxy clusters of galaxies, along with integrated luminosities and average temperatures out to 0.4R500 for 288 galaxy clusters. It includes both projected and deprojected temperature and metallicity profiles, and therefore enhances the original ACCEPT database, which relied on projected temperature profiles. In addition, it uses background models more detailed than the ones used in ACCEPT. Nevertheless, ACCEPT and ACCEPT 2.0 yield similar results, except for occasional offsets of 20%─40% in electron density resulting from improper conversions of X-ray surface brightness to electron density in ACCEPT. When deprojection results in lower central temperatures, entropy estimates at 10─20 kpc are somewhat lower than in ACCEPT. However, deprojection occasionally produces poor central temperature estimates for clusters with low central surface-brightness profiles, which complicates interpretations of results from automated deprojection pipelines. As in ACCEPT, we classify cluster cores by fitting their inner entropy profiles with a simple power law plus a constant entropy floor K0s. ACCEPT 2.0 also provides more robust estimators of entropy at 10 and 20 kpc from the center. We explore relationships between those entropy estimates and morphological parameters, such as surface-brightness concentration, centroid offsets, and power ratios. Among those quantifiers of morphology, we find that surface-brightness concentration is most sensitive to core entropy and can be reliably used to distinguish likely cool-core clusters from non-cool-core clusters.

Keywords: Galaxy clusters, Intracluster medium, Cooling flows, High energy astrophysics
Dark Energy Survey Year 6 Results: Photometric Dataset for Cosmology. We describe the photometric dataset assembled from the full 6 yr of observations by the Dark Energy Survey (DES) in support of static-sky cosmology analyses. DES Y6 Gold is a curated dataset derived from DES Data Release 2 (DR2) that incorporates improved measurement, photometric calibration, object classification and value-added information. Y6 Gold comprises nearly 5000 deg2 of grizY imaging in the south Galactic cap and includes 669 million objects with a depth of iAB ∼ 23.4 mag at a signal-to-noise ratio ∼ 10 for extended objects and a top-of-the-atmosphere photometric uniformity &lt;2 mmag. Y6 Gold augments DES DR2 with simultaneous fits to multiepoch photometry for more robust galaxy shapes, colors, and photometric redshift estimates. Y6 Gold features improved morphological star─galaxy classification with an efficiency of 98.6% and a contamination of 0.8% for galaxies with 17.5 &lt; iAB &lt; 22.5. Additionally, it includes per-object quality information, and accompanying maps of the footprint coverage, masked regions, imaging depth, survey conditions, and astrophysical foregrounds that are used for cosmology analyses. After quality selections, benchmark samples contain 448 million galaxies and 120 million stars. This publication is complemented by data access and documentation.

Keywords: Sky surveys, Astronomy image processing, Observational cosmology, Catalogs, Dark energy
A Morphokinematic Study of Galactic High-abundance Discrepancy Factor Planetary Nebulae Based on the VLT/UVES Deep Spectroscopy. We report detailed analyses of deep, high-resolution spectra of three Galactic planetary nebulae (PNe) with high abundance discrepancy factors (ADFs), Hf 2-2, M 1-42, and NGC 6153, obtained with the Ultraviolet and Visual Echelle Spectrograph on the 8.2 m Very Large Telescope. These spectra were carefully reduced, including rigorous absolute flux calibration, yielding a detection of ∼410─800 emission lines in each PN. Plasma diagnostics and abundance calculations were performed using nebular lines. In all three PNe, the electron temperatures derived using the collisionally excited lines (CELs) are higher than that yielded by the H I Balmer and Paschen jumps, while the temperatures yielded by the O II and N II optical recombination lines (ORLs) are very low, ≲2000 K, indicating that the heavy-element ORLs probe cold nebular regions. The ORL abundances of N, O, and Ne are systematically higher than the corresponding CEL values, confirming high ADFs in the three objects. Position─velocity diagrams were created, and spatiokinematical studies show that CELs come from the outer nebular regions, while the ORL-emitting regions are close to the nebular center. Additionally, the velocity indicated by CEL line-splitting decreases with ionization potential, which was not obvious in ORLs. These spatial and kinematic differences support two distinct components of ionized gas: a cold, metal-rich component and a warmer component with normal metallicity. Heavy elements are strongly enriched in the cold gas, while its H+ fraction is low but still produces significant H I emission, affecting CEL abundance estimates. *Based on the observations obtained with the Very Large Telescope (VLT) through program ID #69.D-0174A.

Keywords: High resolution spectroscopy, Chemical abundances, Stellar mass loss, Planetary nebulae, Galaxy abundances, Interstellar medium, Stellar evolution
Magellanic Outflow and Chemistry Survey (MAGOS): Hot Cores in the LMC. The Large Magellanic Cloud (LMC) provides a key laboratory for exploring the diversity of star formation and interstellar chemistry under subsolar metallicity conditions. We present the results of a hot core survey toward 30 massive protostellar objects in the LMC using the Atacama Large Millimeter/submillimeter Array at 350 GHz. Continuum imaging reveals 36 compact sources in total, among which line analyses identify nine hot cores and one hot-core candidate, including two newly identified sources. We detect CO, HCO+, H13CO+, HC15N, HC3N, SiO, SO, SO+, NS, SO2, 34SO2, 33SO2, CH3OH, 13CH3OH, HCOOH, HCOOCH3, CH3OCH3, C2H5OH, H2CCO (tentative), and hydrogen recombination lines from hot cores. CH3OCH3, a complex organic molecule (COM) larger than CH3OH, is detected for the first time in a hot core outside the LMC bar region. All hot cores show stronger emission in the high-excitation SO line compared to non-hot-core sources, suggesting that its strong detection will be useful for identifying hot-core candidates in the LMC. Chemical analysis reveals a spread of more than 2 orders of magnitude in CH3OH abundances, with some sources deficient in COMs. In contrast, SO2 is detected in all hot cores, and its abundance shows a good correlation with rotational temperature. The hot cores without CH3OH detections are all located outside the LMC bar region and are characterized by either high luminosity or active star formation in their surroundings. A combination of locally low metallicity, active star formation in the vicinity, and high protostellar luminosity may jointly trigger the COM-poor hot-core chemistry observed in the LMC.

Keywords: Interstellar molecules, Protostars, Astrochemistry, Magellanic Clouds, Submillimeter astronomy, Metallicity, Complex organic molecules
The Milky Way Imaging Scroll Painting Survey: Data Release 1. We present the first data release (DR1) of the Milky Way Imaging Scroll Painting (MWISP) survey, a mapping in the J = 1 → 0 transition lines of 12CO, 13CO, and C18O toward the northern Galactic plane during 2011─2022. The MWISP survey was conducted using the Purple Mountain Observatory 13.7 m telescope at a spatial resolution of approximately 50″ and a velocity resolution of 0.16 km s−1 at 115 GHz. DR1 fully covered 2310 deg2 within the Galactic longitude (l) and latitude (b) range of 9 .° 75 ≤ l ≤ 229 .° 75 and ∣b∣ ≤ 5 .° 25. The surveyed area was divided into cell units of  30'×30'  for practical purposes and on-the-fly mapping was performed toward each target cell unit. The data were regridded into a regular three-dimensional data cube in l─b─VLSR with a pixel size of 30″ in l─b axes and 0.16 km s−1 in the VLSR axis. The median rms noise is 0.47, 0.25, and 0.25 K for 12CO, 13CO, and C18O, respectively. The equivalent 3σ sensitivity in 12CO luminosity is approximately 0.23 K km s−1, making MWISP the most sensitive survey of its kind. In this paper, we describe the survey data, including the calibration, data cleaning, data mosaic processes, and the data products. The final mosaicked data cubes contain about 3.33 × 107 spectra (pixels) for each CO isotopologue line. Color composite images, made from the intensities of the isotopologue lines, and some concise descriptions are provided. We constructed a molecular cloud catalog based on the mosaicked 12CO data cube using the clustering algorithm DBSCAN, detecting 103,517 molecular clouds, 10,790 of which exhibit 13CO emission and 304 of which show C18O emission. Based on the histogram of voxel brightness temperature, we estimated a total 12CO flux of 7.69 ± 0.38 × 107 K km s−1 arcmin2, 82% of which is captured by the DBSCAN algorithm. The properties of molecular clouds show a large dynamic range, facilitating more accurate statistics. The data, together with the cloud sample, provide unique information on molecular gas in the northern Milky Way.

Keywords: Observational astronomy, Sky surveys, Astronomy data acquisition, Millimeter astronomy, Molecular clouds, Catalogs
Finite Plasma β Three-dimensional Magnetic Field Extrapolation Based on the Magnetohydrodynamic Relaxation Method. The three-dimensional (3D) magnetic field in the solar atmosphere provides crucial information to help understand explosive phenomena such as solar flares and coronal mass ejections. Since it is still hard to determine the 3D magnetic field from direct observation, a nonlinear force-free field (NLFFF) extrapolation is one of the best modeling methods that provides the 3D magnetic field. However, the method is based on a zero-β assumption, i.e., the model ignores the gas-pressure gradient and gravitational force. The magnetic field based on an NLFFF is not well reconstructed in the high-β region, such as in the chromospheric or lower-height layers and in the weak-field region. To overcome this problem, we need to consider the magnetohydrostatic equilibrium. In this study, we developed a finite plasma β magnetic field extrapolation method based on a magnetohydrodynamic relaxation method. In our method, we consider a force balance of the Lorentz force and the gas pressure. We tested three different schemes and extrapolated the 3D magnetic field using an observational photospheric vector magnetic field of one solar active region (AR), which is a quadrupole complex sunspot group and well studied with an NLFFF. The verification of three schemes is performed by comparing the residual force, and we concluded that our methods reduce ∼4% of the residual force of the previous NLFFF. We also examined the plasma β profile along the height and found that, in the core of the AR, plasma β reaches a local minimum of ≍0.01 in the lower corona with β ≍ 1 at the photosphere.

Keywords: Solar corona, Magnetohydrodynamics, Solar chromosphere, Solar magnetic fields
Galactic Interstellar <SUP>32</SUP>S/<SUP>34</SUP>S Isotopic Ratio Traced by Sulfur Monoxide. To date, the Galactic interstellar radial 32S/34S gradient has only been studied with the CS isotopologues, which may be affected by uncertainties due to the use of a single tracer. As another abundant S-bearing molecules, SO and its isotopomer 34SO could be considered as tracers of the 32S/34S ratio. We present the first systematic observations of SO and 34SO toward a large sample of molecular clouds with accurate distances, performed with the IRAM 30 m and the 10 m Submillimeter Telescope (SMT). With the IRAM 30 m, SO 22─11 was detected in 59 of 82 sources (∼82%), and 34SO 22─11 in eight sources (∼10%). With the SMT 10 m, SO 55─44 was detected in 136 of 184 sources (∼74%), and 34SO 55─44 in 55 of 77 strong SO sources (∼72%). SO/34SO ratios were derived for 8 (22─11) and 55 (55─44) sources. No correlation was found between the SO/34SO ratio and heliocentric distance or Tk, suggesting negligible distance and fractionation effects. Both LTE and non-LTE analyses consistently suggest that the optical-depth effect is also insignificant. 32S/34S ratios from the 22─11 transitions follow the increasing radial trend proposed by previous CS species measurements, while those from the 55─44 lines are systematically lower. The lower transitions of SO and 34SO may be suitable tracers of 32S/34S, though the detections are rare. Comparisons between measurements and Galactic chemical evolution model suggest that the nucleosynthesis prescriptions need to be revised in the low-metallicity regime, but more data for the outermost Galactic regions are crucial for drawing strong conclusions.

Keywords: Interstellar molecules, Isotopic abundances, Galaxy chemical evolution, Radio source counts, Milky Way evolution
BASS. L. Near-infrared Data Release 3: A Spectral Atlas and Characterization of Active Galactic Nuclei. We present an analysis of near-infrared (NIR) emission-line properties, active galactic nucleus (AGN) diagnostics, and circumnuclear gas dynamics for 453 hard X-ray selected (14─195 keV) AGNs from the BAT AGN Spectroscopic Survey NIR Data Release 3 (DR3; &lt;z&gt; = 0.036, z &lt; 1.0). This dataset is the largest compilation of rest-frame NIR spectroscopic observations of hard-X-ray-selected AGNs and includes the full DR2 sample. Observations were obtained with the Very Large Telescope X-Shooter, a multiwavelength (0.3─2.5 μm) spectrograph (R = 4000─18,000), using a ≥ 2σ detection threshold, enabling broad analysis of emission features. We find that NIR coronal lines, particularly [Si VI] λ1.964, are more reliable tracers of AGN luminosity than optical  OIII , showing a tighter correlation with hard X-ray luminosity (σ = 0.25 dex) than  OIII  λ5007 (σ = 0.55 dex). Broad Paschen lines (Paα and Paβ) are detected in 12% of Seyfert 2 and 57% of Seyfert 1.9 galaxies, consistent with previous hidden broad-line region (BLR) studies. We introduce a refined NIR diagnostic diagram ([Fe II] λ1.257 μm/Paβ and H2 λ2.122 μm/Brγ) that effectively distinguishes AGN, star-forming, and composite sources even when contamination limits individual diagnostics or only upper limits are available. Additionally, we find a moderate correlation (p ≍ 7.4 × 10−3) between hot molecular gas mass (traced by H2 2.121 μm) and X-ray luminosity, while its relation with Eddington ratio is weaker. The hot-to-cold gas mass ratio spans 4 orders of magnitude, averaging ∼3 × 10−7, indicating diverse molecular gas excitation processes likely driven by star formation and AGN feedback. Our results underscore the value of NIR spectroscopy in probing AGN activity, obscured BLRs, and the complex interactions between AGNs and their circumnuclear environments.

Keywords: Supermassive black holes, Molecular gas, Surveys, Seyfert galaxies, Active galactic nuclei, X-ray surveys, Catalogs
An Information-based Metric for Observing Strategy Optimization, Demonstrated in the Context of Photometric Redshifts for LSST. The observing strategy (OS) of an astronomical survey influences the degree to which its resulting data can be used to accomplish any science goal, necessitating upcoming programs, including those on the Rubin and Roman telescopes, to solicit metrics in order to optimally choose an OS balancing the costs and benefits to diverse science cases. The requirement that such metrics must be fast to compute often forces them to bake in analysis choices that may not hold for real data. Furthermore, such metrics do not typically share units, impairing objectivity in combining them in an ultimate decision. We propose a metric for OS optimization that is based on the potentially recoverable mutual information about a physical parameter of interest from a sample of data under the constraints of a realistic OS and present a tractable estimation of a variational lower bound of this mutual information implemented in a public code using conditional normalizing flows. We demonstrate the calculation and interpretation of our information-theoretic metric in the context of photometric redshifts, a data product essential to virtually all extragalactic science applications of the Legacy Survey of Space and Time, using mock galaxy catalogs, showing how it can discriminate between observing strategies that preclude robust redshift constraints and those that preserve more redshift information, without specifying an estimator. As our versatile metric reduces the reliance on analysis choices and is interpretable between science goals, we recommend its use to assess the impact of OS in any science application in which photometry may be forward modeled. ✎

Keywords: Astrostatistics tools, Sky surveys, Surveys, Astrostatistics techniques, Redshift surveys, Astrostatistics strategies
A Chemically Peculiar Star Catalog from LAMOST DR12 Based on Deep Learning. Chemically peculiar (CP) stars offer a unique observational sample for exploring key processes in stellar evolution. Leveraging the massive amounts of data obtained from large-scale sky surveys, deep learning technology has significantly advanced research in identifying special celestial objects in large datasets in recent years. In this study, we developed a hybrid deep learning approach that integrates a long short-term memory network with a convolutional neural network to search for CP1/CP2/CP3 stars in low-resolution spectra of LAMOST DR12 (v1.0). We first trained a binary classification model to distinguish CP stars from non-CP stars, achieving an accuracy of 95.92%. Applying this model to the LAMOST DR12 (v1.0) dataset, we identified 79,216 CP star candidates. We then constructed a three-class classification model to distinguish between CP1, CP2, and CP3, achieving an accuracy rate of 97.34%. This model further identified 59,333 CP1 stars, 15,179 CP2 stars, and 1424 CP3 stars from the CP star candidates. After cross validation, 51,241 stars were consistent with previously reported CP stars based on crossmatching results, with 24,695 newly identified CP1/CP2/CP3 candidates, including 16,432 new CP1 candidates, 7132 CP2 candidates, and 1131 CP3 candidates. By combining visual inspection with the MKCLASS code, we ultimately identified 2899 CP1 stars, 4536 CP2 stars, and 747 CP3 stars.

Keywords: Convolutional neural networks, Astronomy data analysis, Stellar classification, Stellar spectral types, Chemically peculiar stars