Sazuna/UAT_keywords huggingface dataset:
Stellar Parameters and Chemical Abundances Estimated from LAMOST-II DR8 MRS Based on Cycle-StarNet. Deriving stellar atmospheric parameters and chemical abundances from stellar spectra is crucial for understanding the evolution of the Milky Way. By performing a fitting with MARCS model atmospheric theoretical synthetic spectra combined with a domain-adaptation method, we estimate the fundamental stellar parameters (T eff, log g, [Fe/H], v mic, and v mac) and 11 chemical abundances for 1.38 million FGKM-type stars of the Medium-Resolution Spectroscopic Survey (MRS) from LAMOST-II DR8. The domain-adaptation method, CYCLE-STARNET, is employed to reduce the gap between observed and synthetic spectra, and the L-BFGS algorithm is used to search the best-fit synthetic spectra. By combining the Two Micron All Sky Survey photometric survey data, Gaia EDR3 parallax, and MIST isochrones, the surface gravities of the stars are constrained after estimating their bolometric luminosities. The accuracy of T eff, log g, and [Fe/H] can reach 150 K, 0.11 dex, and 0.15 dex, evaluated by the PASTEL catalog, asteroseismic samples, and other spectroscopic surveys. The precision of these parameters and elemental abundances ([C/Fe], [Na/Fe], [Mg/Fe], [Si/Fe], [Ca/Fe], [Ti/Fe], [Cr/Fe], [Mn/Fe], [Co/Fe], [Ni/Fe], and [Cu/Fe]) is assessed by repeated observations and validated by cluster members. For spectra with signal-to-noise ratios (S/Ns) greater than 10, the precision of the three stellar parameters and elemental abundances can achieve 76 K, 0.014 dex, 0.096 dex, and 0.04-0.15 dex. For spectra with S/Ns higher than 100, the precision stabilizes at 22 K, 0.006 dex, 0.043 dex, and 0.01-0.06 dex. The full LAMOST MRS stellar properties catalog is available at doi: 10.12149/101242.

Keywords: Fundamental parameters of stars, Chemical abundances, Stellar astronomy, Stellar physics, Stellar atmospheres
HST Low-resolution Stellar Library. In order to provide fundamental stellar spectra that extend into the UV, Hubble Space Telescope's Space Telescope Imaging Spectrograph targeted 556 stars via proposals GO9088, GO9786, GO10222, and GO13776. Exposures through three low-resolution gratings provide wavelength coverage from 0.2 &lt; λ &lt; 1 μm at λ/Δλ ~ 1000. The UV grating (G230LB) scatters red light that results in unwanted signal, especially in cool stars. We applied scattered-light corrections and flux corrections arising from pointing errors relative to the center of the 0.″2 slit based on Worthey et al. We present 513 fully reduced stellar spectra, fluxed, dereddened, and cross correlated to zero velocity. Because of the broad spectral range, we can simultaneously study Hα and Mg II λ2800, indicators of chromospheric activity. Their behaviors are decoupled. Besides three cool dwarfs and one giant with mild flares in Hα, only Be stars show strong Hα emission. Mg2800 emission, however, strongly anticorrelates with temperature such that warm stars show absorption and stars cooler than 5000 K universally show chromospheric emission regardless of dwarf/giant status or metallicity. Transformed to Mg2800 flux emerging from the stellar surface, we find a correlation with temperature with approximately symmetric astrophysical scatter. Previous work had indicated a basal level with asymmetric scatter to strong values. The discrepancy is primarily due to our improved treatment of extinction. We confirm statistically significant time variability in Mg2800 strength for one star.

Keywords: Hubble Space Telescope, Stellar chromospheres
Propagating Uncertainties in the SALT3 Model-training Process to Cosmological Constraints. Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low-z or poorly calibrated U-band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U-band data, and can be shifted by ~5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low-z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data-the resulting w measurement can be biased by ~2% if the color distribution is not sufficiently wide. Future low-z data, particularly u-band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

Keywords: Cosmology, Type Ia supernovae
Delensing of Cosmic Microwave Background Polarization with Machine Learning. Primordial B-mode detection is one of the main goals of next-generation cosmic microwave background (CMB) experiments. Primordial B-modes are a unique signature of primordial gravitational waves (PGWs). However, the gravitational interaction of CMB photons with large-scale structures will distort the primordial E modes, adding a lensing B-mode component to the primordial B-mode signal. Removing the lensing effect ("delensing") from observed CMB polarization maps will be necessary to improve the constraint of PGWs and obtain a primordial E-mode signal. Here, we introduce a deep convolutional neural network model named multi-input multi-output U-net (MIMO-UNet) to perform CMB delensing. The networks are trained on simulated CMB maps with size 20° × 20°. We first use MIMO-UNet to reconstruct the unlensing CMB polarization (Q and U) maps from observed CMB maps. The recovered E-mode power spectrum exhibits excellent agreement with the primordial EE power spectrum. The recovery of the primordial B-mode power spectrum for noise levels of 0, 1, and 2 μK-arcmin is greater than 98% at the angular scale of ℓ &lt; 150. We additionally reconstruct the lensing B map from observed CMB maps. The recovery of the lensing B-mode power spectrum is greater than roughly 99% at the scales of ℓ &gt; 200. We delens the observed B-mode power spectrum by subtracting the reconstructed lensing B-mode spectrum. The recovery of tensor B-mode power spectrum for noise levels of 0, 1, and 2 μK-arcmin is greater than 98% at the angular scales of ℓ &lt; 120. Even at ℓ = 160, the recovery of tensor B-mode power spectrum is still around 71%.

Keywords: Observational cosmology, Cosmic microwave background radiation, Convolutional neural networks
Interplanetary Coronal Mass Ejections and Stream Interaction Regions Observed by Tianwen-1 and MAVEN at Mars. The Tianwen-1 spacecraft is China's first Mars exploration mission. The Mars Orbiter Magnetometer (MOMAG) is a scientific instrument on board the Tianwen-1 mission that is designed to study magnetic fields at Mars, including the solar wind to the magnetosheath and the ionosphere. Using the first Tianwen-1/MOMAG data that is publicly available, we present an interplanetary coronal mass ejection (ICME) and stream interaction region (SIR) list based on in situ observations at Mars between 2021 November 16 and 2021 December 31. We compared the magnetic field intensity and vector magnetic field measurements from Tianwen-1/MOMAG and Mars Atmospheric Volatile EvolutioN (MAVEN)/Magnetometer (MAG) during the ICME and SIR interval and found a generally good consistency between them. Due to MAVEN's orbital adjustment since 2019, the Tianwen-1/MOMAG instrument is almost unique in its status as an interplanetary magnetic field monitor currently at Mars. The observations indicate that the MOMAG instrument on Tianwen-1 is performing well and can provide accurate measurements of the vector magnetic field in the near-Mars solar wind space. The multipoint observations combining MOMAG, MINPA, and MEPA on board Tianwen-1 with MAG, SWIA, and STATIC on board MAVEN will help develop systematic studies of the characteristics of ICMEs and SIRs at Mars, and their influences on the Martian atmosphere and ionosphere.

Keywords: Space weather, Solar coronal mass ejections, Heliosphere
Chemical Differentiation around Five Massive Protostars Revealed by ALMA: Carbon-chain Species and Oxygen/Nitrogen-bearing Complex Organic Molecules. We present Atacama Large Millimeter/submillimeter Array Band 3 data toward five massive young stellar objects (MYSOs), and investigate relationships between unsaturated carbon-chain species and saturated complex organic molecules (COMs). An HC5N (J = 35-34) line has been detected from three MYSOs, where nitrogen (N)-bearing COMs (CH2CHCN and CH3CH2CN) have been detected. The HC5N spatial distributions show compact features and match with a methanol (CH3OH) line with an upper-state energy around 300 K, which should trace hot cores. The hot regions are more extended around the MYSOs where N-bearing COMs and HC5N have been detected compared to two MYSOs without these molecular lines, while there are no clear differences in the bolometric luminosity and temperature. We run chemical simulations of hot-core models with a warm-up stage, and compare with the observational results. The observed abundances of HC5N and COMs show good agreements with the model at the hot-core stage with temperatures above 160 K. These results indicate that carbon-chain chemistry around the MYSOs cannot be reproduced by warm carbon-chain chemistry, and a new type of carbon-chain chemistry occurs in hot regions around MYSOs.

Keywords: Interstellar molecules, Massive stars, Star formation, Astrochemistry
S-type Stars from LAMOST DR10: Classification of Intrinsic and Extrinsic Stars. In this paper, we found 2939 S-type stars from LAMOST Data Release 10 using two machine-learning methods, and 2306 of them were reported for the first time. The main purpose of this work is to study how to divide S-type stars into intrinsic and extrinsic stars with photometric data and LAMOST spectra. Using infrared photometric data, we adopted two methods to distinguish S-type stars, i.e., the XGBoost algorithm and color-color diagrams. We trained the XGBoost model with 15 input features consisting of colors and absolute magnitudes from Two Micron All Sky Survey (2MASS), AllWISE, AKARI, and IRAS, and found that the model trained by input features with 2MASS, AKARI, and IRAS data has the highest accuracy of 95.52%. Furthermore, using this XGBoost model, we found four color-color diagrams with six infrared color criteria to divide S-type stars, which have an accuracy of about 90%. Applying the two methods to the 2939 S-type stars, 381 (XGBoost)/336 (color-color diagrams) intrinsic and 495 (XGBoost)/82 (color-color diagrams) extrinsic stars were classified, respectively. Using these photometrically classified intrinsic and extrinsic stars, we retrained the XGBoost model with their blue and red medium-resolution spectra, and the 2939 stars were divided into 855 intrinsic and 2056 extrinsic stars from spectra with an accuracy of 94.82%. In addition, we also found the four spectral regions of Zr I (6451.6 Å), Ne II (6539.6 Å), H α  (6564.5 Å), and Fe I (6609.1 Å) and C I (6611.4 Å) are the most important features, which can reach an accuracy of 92.1% when using them to classify S-type stars.

Keywords: S stars
Data-constrained Solar Modeling with GX Simulator. To facilitate the study of solar flares and active regions, we have created a modeling framework, the freely distributed GX Simulator IDL package, that combines 3D magnetic and plasma structures with thermal and nonthermal models of the chromosphere, transition region, and corona. Its object-based modular architecture, which runs on Windows, Mac, and Unix/Linux platforms, offers the ability to either import 3D density and temperature distribution models, or to assign numerically defined coronal or chromospheric temperatures and densities, or their distributions, to each individual voxel. GX Simulator can apply parametric heating models involving average properties of the magnetic field lines crossing a given voxel, as well as compute and investigate the spatial and spectral properties of radio, (sub)millimeter, EUV, and X-ray emissions calculated from the model, and quantitatively compare them with observations. The package includes a fully automatic model production pipeline that, based on minimal users input, downloads the required SDO/HMI vector magnetic field data, performs potential or nonlinear force-free field extrapolations, populates the magnetic field skeleton with parameterized heated plasma coronal models that assume either steady-state or impulsive plasma heating, and generates non-LTE density and temperature distribution models of the chromosphere that are constrained by photospheric measurements. The standardized models produced by this pipeline may be further customized through specialized IDL scripts, or a set of interactive tools provided by the graphical user interface. Here, we describe the GX Simulator framework and its applications.

Keywords: Astronomy data modeling, Solar flares, Microwave spectroscopy, Solar active regions, Non-thermal radiation sources, Solar electromagnetic emission
A Catalog of Young Stellar Objects from the LAMOST and ZTF Surveys. As astronomical data sets become too large for traditional analysis approaches, more machine-learning algorithms are employed in astronomy. A wealth of light variation data have been accumulated, which provide rich samples for astronomers to study variable stars. Facing the challenge of big data, this article takes the classification of variable and transient objects observed by the Zwicky Transient Facility (ZTF) as the main goal, and a self-paced ensemble (SPE) imbalanced-learning classifier is constructed to separate different classes. The performance of the classifier reveals that SPE is better than a traditional imbalanced-learning algorithm for the minority classes. In our work, the SPE classifier is satisfactory for young stellar objects (YSOs), and the completeness (recall) of YSOs is enhanced to 91%. As a result, 868,371 ZTF sources are classified into 15 classes by this classifier, which contains 8210 YSO candidates (YSO_prob ≥ 0.70). In order to further identify YSO candidates, these candidates are crossmatched with LAMOST DR9. Finally, 833 candidates are observed by LAMOST, among them 379 objects that are known YSOs in SIMBAD. For the remaining objects with good-quality LAMOST spectra, we visually check their spectral characteristics, and 238 objects are newly confirmed YSOs. These newfound YSOs supplement the present YSO sample, and other YSO candidates may be used for follow-up observation, which is useful for characterizing YSOs, finding more YSOs, and then giving a better stellar evolution model in the future. The classified ZTF sources by SPE provide reference to the study of variables and transients.

Keywords: Light curve classification , Astrostatistics techniques, Astronomy data analysis, Pre-main sequence stars, Time series analysis
Robust Data-driven Metallicities for 175 Million Stars from Gaia XP Spectra. We derive and publish data-driven estimates of stellar metallicity [M/H] for ~175 million stars with low-resolution XP spectra published in Gaia DR3. The [M/H] values, along with T eff and $\mathrm{log}g$ , are derived using the XGBoost algorithm, trained on stellar parameters from APOGEE, augmented by a set of very-metal-poor stars. XGBoost draws on a number of data features: the full set of XP spectral coefficients, narrowband fluxes derived from XP spectra, and broadband magnitudes. In particular, we include CatWISE magnitudes, as they reduce the degeneracy of T eff and dust reddening. We also include the parallax as a data feature, which helps constrain $\mathrm{log}g$ and [M/H]. The resulting mean stellar parameter precision is 0.1 dex in [M/H], 50 K in T eff, and 0.08 dex in $\mathrm{log}g$ . This all-sky [M/H] sample is substantially larger than published samples of comparable fidelity across -3 ≲ [M/H] ≲ +0.5. Additionally, we provide a catalog of over 17 million bright (G &lt; 16) red giants whose [M/H] values are vetted to be precise and pure. We present all-sky maps of the Milky Way in different [M/H] regimes that illustrate the purity of the data set, and demonstrate the power of this unprecedented sample to reveal the Milky Way's structure from its heart to its disk.

Keywords: Stellar abundances, Galaxy abundances, Galaxy stellar content, Catalogs
The First AGILE Solar Flare Catalog. We report the Astro-rivelatore Gamma a Immagini LEggero (AGILE) observations of solar flares, detected by the onboard anticoincidence system in the 80–200 keV energy range, from 2007 May 1 to 2022 August 31. In more than 15 yr, AGILE detected 5003 X-ray, minute-lasting transients, compatible with a solar origin. A cross-correlation of these transients with the Geostationary Operational Environmental Satellites (GOES) official solar flare database allowed us to associate an intensity class (i.e., B, C, M, or X) to 3572 of them, for which we investigated the main temporal and intensity parameters. The AGILE data clearly revealed the solar activity covering the last stages of the 23rd cycle, the whole 24th cycle, and the beginning of the current 25th cycle. In order to compare our results with other space missions operating in the high-energy range, we also analyzed the public lists of solar flares reported by RHESSI and Fermi Gamma-ray Burst Monitor. This catalog reports 1424 events not contained in the GOES official data set, which, after statistical comparisons, are compatible with low-intensity, short-duration solar flares. Besides providing a further data set of solar flares detected in the hard X-ray range, this study allowed to point out two main features: a longer persistence of the decay phase in the high-energy regime, with respect to the soft X-rays, and a tendency of the flare maximum to be reached later in the soft X-rays with respect to the hard X-rays. Both these aspects support a two-phase acceleration mechanism of electrons in the solar atmosphere.

Keywords: Solar flares, High energy astrophysics
Ultradiffuse Galaxies (UDGs) with Hyper Suprime-Cam. I. Revised Catalog of Coma Cluster UDGs. This is the first in a series of papers on the properties of ultradiffuse galaxies (UDGs) in clusters of galaxies. We present an updated catalog of UDGs in the Coma Cluster using g- and r-band images obtained with Hyper Suprime-Cam (HSC) of the Subaru telescope. We develop a method to find UDGs even in the presence of contaminating objects, such as halos and background galaxies. This study expands upon our previous works that covered about half the area of the Coma Cluster. The HSC observations covered the whole Coma Cluster up to the virial radius and beyond (an area twice as large as the previous studies) and doubled the numbers of UDGs (r eff, r ≥ 1.5 kpc) and sub-UDGs (1.0 ≤ r eff, r &lt; 1.5 kpc) to 774 and 729, respectively. The new UDGs show internal properties consistent with those of previous studies (e.g., a Sérsic index of approximately 1), and are distributed across the cluster, with a concentration around the cluster center. The whole cluster coverage clearly revealed an excess of their distribution toward the east to southwest direction along the cluster center, where Coma connects to other large-scale structure, and where a known substructure exists (the NGC 4839 subgroup). The alignment of the UDG distribution along the large-scale structure around Coma supports the interpretation that most of them lie at the distance of the Coma Cluster and the NGC 4839 subgroup. * This research is based on data collected at the Subaru Telescope, which is operated by the National Astronomical Observatory of Japan. We are honored and grateful for the opportunity of observing the universe from Maunakea, which has cultural, historical, and natural significance in Hawaii.

Keywords: Galaxy clusters, Galaxy structure, Coma Cluster, Galactic and extragalactic astronomy, Galaxies, Low surface brightness galaxies
Slow Solar Wind Connection Science during Solar Orbiter's First Close Perihelion Passage. The Slow Solar Wind Connection Solar Orbiter Observing Plan (Slow Wind SOOP) was developed to utilize the extensive suite of remote-sensing and in situ instruments on board the ESA/NASA Solar Orbiter mission to answer significant outstanding questions regarding the origin and formation of the slow solar wind. The Slow Wind SOOP was designed to link remote-sensing and in situ measurements of slow wind originating at open-closed magnetic field boundaries. The SOOP ran just prior to Solar Orbiter's first close perihelion passage during two remote-sensing windows (RSW1 and RSW2) between 2022 March 3-6 and 2022 March 17-22, while Solar Orbiter was at respective heliocentric distances of 0.55-0.51 and 0.38-0.34 au from the Sun. Coordinated observation campaigns were also conducted by Hinode and IRIS. The magnetic connectivity tool was used, along with low-latency in situ data and full-disk remote-sensing observations, to guide the target pointing of Solar Orbiter. Solar Orbiter targeted an active region complex during RSW1, the boundary of a coronal hole, and the periphery of a decayed active region during RSW2. Postobservation analysis using the magnetic connectivity tool, along with in situ measurements from MAG and SWA/PAS, showed that slow solar wind originating from two out of three of the target regions arrived at the spacecraft with velocities between ~210 and 600 km s-1. The Slow Wind SOOP, despite presenting many challenges, was very successful, providing a blueprint for planning future observation campaigns that rely on the magnetic connectivity of Solar Orbiter.

Keywords: Slow solar wind, Solar physics, Solar wind, Solar active regions
Critically Evaluated Atomic Data for the Au IV Spectrum. A spectral investigation of triply ionized gold (Au IV) has been carried out in the wavelength region of 500-2106 Å. The gold spectra were photographed at the National Institute of Standards and Technology, USA, on a 10.7 m normal incidence vacuum spectrograph (NIVS) using a sliding spark source as well as on a 3 m NIVS at the Antigonish laboratory in Canada with a triggered spark source. Our analysis is theoretically supported by the pseudorelativistic Hartree-Fock (HFR) formalism with a superposition of configuration interactions implemented in Cowan's suite of codes. Radiative transition parameters are also calculated using the HFR+CPOL (core polarization effects) model and the multiconfiguration Dirac-Hartree-Fock approach, and their comparisons are used to evaluate the transition rate data. All the previously reported levels of the 5d 8, 5d 76s, and 5d 76p configurations are confirmed, except one, and three are newly established. The missing 1 S 0 level of 5d 8 is now established at 55,277.8 cm-1. A total of 981 observed lines (E1 type), classified to 1031 transitions, including 133 newly identified, enabled us to optimize 139 energy levels. Several astrophysically important transitions, forbidden (M1- and E2-type) lines of 5d 8 and 5d 76s, are provided with their Ritz wavelengths and radiative parameters. A critically evaluated set of energy levels, observed and Ritz wavelengths along with their uncertainties, transition rates, and uniformly scaled intensities of Au IV lines have been presented. Also, large-scale atomic data to compute the opacity of Au IV in the kilonova ejecta have been supplemented in this work.

Keywords: Line positions, Atomic physics, Spectral line identification, Atomic data, Atomic spectroscopy, Atomic data benchmarking, Transition probabilities, Line intensities