Sazuna/UAT_keywords huggingface dataset:
Key Signatures of Prominence Materials and Category of Cold Materials Identified by Random Forest Classifier. The origin of cold materials identified by different criteria is unclear. They are highly suspected to be erupted prominences. However, some cold materials defined by charge depletion exist in both quiet solar wind and interplanetary coronal mass ejections (ICMEs). Recently, solar observations show failed prominence eruption in coronal mass ejections (CMEs) that the prominence sometimes did not propagate into interplanetary space. This work uses Random Forest Classifier (RFC), which is an interpretable supervised machine-learning algorithm to study the distinct signatures of prominence cold materials (PCs) compared to quiet solar wind (QSW) and ICMEs excluding cold materials (ICMEEs). Twelve physical features measured by ACE at 1 au and the monthly averaged sunspot number are used in this study. The measurements from ACE are proton moments, magnetic field component B  z , He/H, He/O, Fe/O, mean charge of oxygen and carbon, C6+/C5, C6+/C4+, and O7+/O6+. According to the returned weights from RFC that are checked by support vector machine classifier, the most important in situ signatures of PCs are obtained. Next, the trained RFC is used to check the category of the cold materials not related to CME observations. The results show that most segments of the cold materials are from prominences, but four of them are possibly from ICMEEs; another one segment is possibly from QSW. The most distinct signatures of PCs are lower (C6+/C5+)/(O7+/O6+), proton temperature, and He/O. Considering the obvious overlaps on key physical features between QSW, ICMEEs, and PCs, the multifeature classifier shows an advantage in identifying them than solid criteria.

Keywords: Solar coronal mass ejections, Solar prominences
Improved GALEX UV Photometry for 700,000 SDSS Galaxies. The Galaxy Evolution Explorer (GALEX) satellite performed the first and only large-area UV survey, which in tandem with the Sloan Digital Sky Survey (SDSS) has facilitated modeling of the spectral energy distributions of low-redshift galaxies and the determination of various galaxy properties, in particular the star formation rate. However, the relatively crude angular resolution of GALEX (5″) made its images susceptible to blending of sources, resulting in potentially biased far-UV and near-UV (NUV) pipeline photometry. To remedy this issue and take advantage of model-fit photometry, we use the EMphot software to obtain forced GALEX photometry for ~700,000 SDSS galaxies at z &lt; 0.3. Positional priors of target galaxies and potentially contaminating neighbors were taken from SDSS. New photometry is based on the best-fitting of three model profiles: optical-like, exponential, and flat. New photometry mitigates blending present in the original pipeline catalogs, which affected 16% of galaxies at a level of &gt;0.2 mag and 2% at a level of &gt;1 mag. Pipeline NUV magnitudes are severely affected (≳1 mag) when the neighbor is brighter than the target galaxy and within 10″, or when the neighbor is fainter and within ~3″ of the target. New photometry fixes edge-of-detector bias, which affected pipeline photometry by up to 0.1 mag in NUV. We present catalogs with new photometry for GALEX observations of different depths, corresponding to the all-sky imaging survey (AIS), medium imaging survey, and deep imaging survey. Catalogs feature combined magnitudes for multiple detections of the same galaxy in a survey.

Keywords: Galaxies, Sky surveys, Near ultraviolet astronomy, Galactic and extragalactic astronomy, Ultraviolet astronomy, Galaxy photometry, Star formation, Spectral energy distribution, Photometry, Ultraviolet photometry, Broad band photometry, Catalogs
A New 6-15 GHz Solar Radio Observation System. In this study, we have developed a centimeter-band solar radio telescope covering the 6-15 GHz frequency band. The radio telescope has the outstanding advantages of a large instantaneous sampling bandwidth and wide frequency coverage. As a new solar radio telescope, its time resolution reaches a very high level of 0.26 ms at a frequency resolution of 3 MHz, which is very conducive to observing the fine structure of radio burst signals. In terms of the structure design, the system employs a 3 m diameter parabolic antenna to receive solar radio signals. The antenna has high gain and good directivity, and the pointing accuracy reaches 0.°02, which ensures the ability to accurately track the Sun in real time. In the analog signal processing module, the combination of radio frequency direct acquisition and down conversion is used to reduce the interference caused by multiple spectrum shifts. Regarding the digital receiver, a digital receiving module with high sampling rate and acquisition resolution is used for data acquisition and processing, which ensures that the observation system can obtain observation data with high time and frequency resolutions and real-time data processing. During the trial operation of the system, solar radio bursts have been observed many times, and these observations have been supported by similar international observation equipment. According to a data comparison, the data obtained by our observation system are more precise. At present, equipment calibration methods are being improved and constructed to obtain more accurate observation data.

Keywords: Solar radio telescopes, Flux calibration
A White Dwarf Search Model Based on a Deep Transfer-learning Method. White dwarfs represent the ultimate stage of evolution for over 97% of stars and play a crucial role in studies of the Milky Way's structure and evolution. Recent years have witnessed significant progress in using deep-learning methods for identifying unique objects in large-scale data. In this paper, we present a model based on transfer learning for identifying white dwarfs. We constructed a data set using the spectra released by LAMOST DR9 and trained a convolutional neural network model. The model was then further trained using a transfer-learning approach for a binary classification model. Our final model is comprised of a seven-class classification model and a binary classification model. The testing set yielded an accuracy rate of 96.08%. Our proposed model successfully identifies 4314 of the 4479 white dwarfs published in previous papers. We applied this model to filter the 1,121,128 spectral data from the LAMOST DR9 V1 catalog. Subsequently, we obtained 6317 white dwarf candidates, of which 5014 were cross-validated and found to be known white dwarfs. We finally identified 489 new white dwarfs out of the remaining 1303 candidates, containing 377 DAs, 1 DB, 4 DZs, 1 magnetic WD, 101 DA+M binaries, and 1 DB+M binary. Our study also compared transfer-learning methods with non-transfer-learning methods, and the results show that transfer learning provides faster training speed and a higher accuracy rate. We provide the trained model and a corresponding usage program for subsequent studies.

Keywords: Stellar types, Stellar classification, White dwarf stars, Convolutional neural networks
Age of FGK Dwarfs Observed with LAMOST and GALAH: Considering the Oxygen Enhancement. Varying oxygen abundance could impact modeling-inferred ages. This work aims to estimate the ages of dwarfs considering observed oxygen abundance. To characterize 67,503 LAMOST and 4006 GALAH FGK-type dwarf stars, we construct a grid of stellar models, which take into account oxygen abundance as an independent model input. Compared with ages determined with commonly used α-enhanced models, we find a difference of ~9% on average when the observed oxygen abundance is considered. The age differences between the two types of models are correlated to [Fe/H] and [O/α], and they are relatively significant on stars with [Fe/H] ≲ -0.6 dex. Generally, varying 0.2 dex in [O/α] will alter the age estimates of metal-rich (-0.2 &lt; [Fe/H] &lt; 0.2) stars by ~10% and relatively metal-poor (-1 &lt; [Fe/H] &lt; -0.2) stars by ~15%. Of the low-O stars with [Fe/H] &lt; 0.1 dex and [O/α] ~-0.2 dex, many have fractional age differences of ≥ 10% and even reach up to 27%. The fractional age difference of high-O stars with [O/α] ~0.4 dex reaches up to -33% to -42% at [Fe/H] ≲ -0.6 dex. We also analyze the chemical properties of these stars. We find a decreasing trend of [Fe/H] with ages from 7.5-9 Gyr to 5-6.5 Gyr for the stars from the LAMOST and GALAH. The [O/Fe] of these stars increases with decreasing age from 7.5-9 Gyr to 3-4 Gyr, indicating that the younger population is more O rich.

Keywords: Stellar ages, Stellar kinematics, Stellar abundances, Fundamental parameters of stars, Milky Way disk
Investigating 16 Open Clusters in the Kepler/K2-Gaia DR3 Field. I. Membership, Binary Systems, and Rotation. Using data from Gaia Data Release 3 and Kepler/K2, we present a catalog of 16 open clusters with ages ranging from 4-4000 Myr that provides detailed information on membership, binary systems, and rotation. We assess the memberships in 5D phase space, and estimate the basic parameters of each cluster. Among the 20,160 members, there are 4381 stars identified as binary candidates and 49 stars identified as blue straggler stars. The fraction of binaries varies in each cluster, and the range is between 9% and 44%. We obtain the rotation periods of 5467 members, of which 4304 are determined in this work. To establish a benchmark for the rotation-age-color relation, we construct color-period diagrams. We find that the rotational features of binaries are similar to that of single stars, while the features for binaries are more scattered in the rotation period. Moreover, the morphology of the color-period relationship is already established for Upper Scorpius at the age of 19 Myr, and some stars of varying spectral types (i.e., FG, K, and M type) show different spin-down rates after the age of ~110 Myr. By incorporating the effects of stalled spin-down into our analysis, we develop an empirical rotation-age-color relation, which is valid with ages between 700-4000 Myr and colors corresponding to a range of 0.5 &lt; ${({G}_{\mathrm{BP}}-{G}_{\mathrm{RP}})}_{0}$ &lt; 2.5 mag.

Keywords: Binary stars, Stellar ages, Open star clusters, Stellar rotation, Star clusters
The Multiwavelength Environment of Second Bologna Catalog Sources. We present the first results of the Chandra Cool Targets (CCT) survey of the Second Bologna Catalog (B2CAT) of powerful radio sources, aimed at investigating the extended X-ray emission surrounding these sources. For the first 33 sources observed in the B2CAT CCT survey, we performed both imaging and spectral X-ray analysis, producing multiband Chandra images, and compared these images with radio observations. To evaluate the presence of extended emission in the X-rays, we extracted surface flux profiles comparing them with simulated ACIS point-spread functions. We detected X-ray nuclear emission for 28 sources. In addition, we detected eight regions of increased X-ray flux originating from radio hot spots or jet knots, and a region of decreased flux, possibly associated with an X-ray cavity. We performed X-ray spectral analysis for 15 nuclei and found intrinsic absorption significantly larger than the Galactic values in four of them. We detected significant extended X-ray emission in five sources, and fitted their spectra with thermal models with gas temperatures ~2 keV. In the case of B2.1 0742+31, the surrounding hot gas is compatible with the intracluster medium of low-luminosity clusters of galaxies, while the X-ray diffuse emission surrounding the highly disturbed wide-angle-tailed radio galaxy B2.3 2254+35 features a luminosity similar to those of relatively bright galaxy groups, although its temperature is similar to those of low-luminosity galaxy clusters. These results highlight the power of low-frequency radio selection, combined with short Chandra snapshot observations, for investigating the properties of X-ray emission from radio sources.

Keywords: Galaxy clusters, Active galaxies, Galaxy jets
Powerful Radio Sources in the Southern Sky. II. A Swift X-Ray Perspective. We recently constructed the G4Jy-3CRE, a catalog of extragalactic radio sources based on the GLEAM 4-Jy (G4Jy) sample, with the aim of increasing the number of powerful radio galaxies and quasars with similar selection criteria to those of the revised release of the Third Cambridge Catalog (3CR). The G4Jy-3CRE consists of a total of 264 radio sources mainly visible from the Southern Hemisphere. Here, we present an initial X-ray analysis of 89 G4Jy-3CRE radio sources with archival X-ray observations from the Neil Gehrels Swift Observatory. We reduced a total of 624 Swift observations, for about 0.9 Ms of integrated exposure time. We found X-ray counterparts for 59 radio sources belonging to the G4Jy-3CRE, nine of them showing extended X-ray emission. The remaining 30 sources do not show any X-ray emission associated with their radio cores. Our analysis demonstrates that X-ray snapshot observations, even if lacking uniform exposure times, as those carried out with Swift, allow us to (i) verify and/or refine the host galaxy identification; (ii) discover the extended X-ray emission around radio galaxies of the intracluster medium when harbored in galaxy clusters, as the case of G4Jy 1518 and G4Jy 1664; and (iii) detect X-ray radiation arising from their radio lobes, as for G4Jy 1863.

Keywords: Galaxy clusters, Radio jets, Surveys, Radio lobes, Galactic and extragalactic astronomy, Radio loud quasars, X-ray surveys, Radio active galactic nuclei
Homogenizing SOHO/EIT and SDO/AIA 171 Å Images: A Deep-learning Approach. Extreme-ultraviolet (EUV) images of the Sun are becoming an integral part of space weather prediction tasks. However, having different surveys requires the development of instrument-specific prediction algorithms. As an alternative, it is possible to combine multiple surveys to create a homogeneous data set. In this study, we utilize the temporal overlap of Solar and Heliospheric Observatory Extreme ultraviolet Imaging Telescope and Solar Dynamics Observatory Atmospheric Imaging Assembly 171 Å surveys to train an ensemble of deep-learning models for creating a single homogeneous survey of EUV images for two solar cycles. Prior applications of deep learning have focused on validating the homogeneity of the output while overlooking the systematic estimation of uncertainty. We use an approach called "approximate Bayesian ensembling" to generate an ensemble of models whose uncertainty mimics that of a fully Bayesian neural network at a fraction of the cost. We find that ensemble uncertainty goes down as the training set size increases. Additionally, we show that the model ensemble adds immense value to the prediction by showing higher uncertainty in test data that are not well represented in the training data.

Keywords: Solar atmosphere, Solar extreme ultraviolet emission, Convolutional neural networks, Calibration, Solar corona
The Classification of Galaxy Morphology in the H Band of the COSMOS-DASH Field: A Combination-based Machine-learning Clustering Model. By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band-selected massive galaxies in the COSMOS-DASH field, which includes 17,292 galaxies with stellar mass M ⋆ &gt; 1010 M ⊙ at 0.5 &lt; z &lt; 2.5. The classification scheme is designed to provide a complete morphology classification for galaxies via a combination of two machine-learning steps. We first use an unsupervised machine-learning method (i.e., bagging-based multiclustering) to cluster galaxies into five categories: spherical (SPH), early-type disk, late-type disk, irregular (IRR), and unclassified. About 48% of the galaxies (8258/17,292) are successfully clustered during this step. For the remaining sample, we adopt a supervised machine-learning method (i.e., GoogLeNet) to classify them, during which galaxies that are well classified in the previous step are taken as our training set. Consequently, we obtain a morphology classification result for the full sample. The t-SNE test shows that galaxies in our sample can be well aggregated. We also measure the parametric and nonparametric morphologies of these galaxies. We find that the Sérsic index increases from IRR to SPH and the effective radius decreases from IRR to SPH, consistent with the corresponding definitions. Galaxies from different categories are separately distributed in the G-M 20 space. Such consistencies with other characteristic descriptions of galaxy morphology demonstrate the reliability of our classification result, ensuring that it can be used as a basic catalog for further galaxy studies.

Keywords: Astrostatistics techniques, Galaxy structure, Astronomy data analysis
Spectral Energy Distributions of Southern Binary X-Ray Sources. The rapid variability of X-ray binaries (XRBs) produces a wide range of X-ray states that are linked to activity across the electromagnetic spectrum. It is particularly challenging to study a sample of sources large enough to include all types in their various states, and to cover the full range of frequencies that show flux density variations. Simultaneous observations with many telescopes are necessary. In this project, we monitor 48 XRBs with seven telescopes across the electromagnetic spectrum from 5 × 109 to 1019 Hz, including ground-based radio, IR, and optical observatories, and five instruments on two spacecraft over a 1 week period. We construct spectral energy distributions and matching X-ray color-intensity diagrams for 20 sources that have the most extensive detections. Our observations are consistent with several models of expected behavior proposed for the different classes: we detect no significant radio emission from pulsars or atoll sources, but we do detect radio emission from Z sources in the normal or horizontal branch, and from black holes in the high/soft, low/hard, and quiescent states. The survey data provide useful constraints for more detailed models predicting behavior from the different classes of sources.

Keywords: Low-mass x-ray binary stars, X-ray binary stars, High mass x-ray binary stars
An XMM-Newton View of the Andromeda Galaxy as Explored in a Legacy Survey (New-ANGELS). I. The X-Ray Source Catalog. We introduce the New-ANGELS program, an XMM-Newton survey of a ~7.2 deg2 area around M31, which aims to study the X-ray populations in the M31 disk and the X-ray-emitting hot gas in the inner halo of M31 up to 30 kpc. In this first paper, we report the catalog of 4506 detected X-ray sources and attempt to cross-identify or roughly classify them. We identify 352 single stars in the foreground, 35 globular clusters, and 27 supernova remnants associated with M31, as well as 62 active galactic nuclei, 59 galaxies, and one galaxy cluster in the background. We uniquely classify 236 foreground stars and 17 supersoft sources based on their X-ray colors. X-ray binaries (83 low-mass and one high-mass) are classified based on their X-ray colors and X-ray variabilities. The remaining X-ray sources either have too low signal-to-noise ratios to calculate their X-ray colors or do not have a unique classification, so are regarded as unclassified. The X-ray source catalog is published online. Studies of the X-ray source populations and the contribution of X-ray sources in the unresolved X-ray emissions based on this catalog will be published in companion papers.

Keywords: X-ray identification, Stellar populations, Andromeda Galaxy, X-ray sources
PSF-based Analysis for Detecting Unresolved Wide Binaries. Wide binaries play a crucial role in analyzing the birth environment of stars and the dynamical evolution of clusters. When wide binaries are located at greater distances, their companions may overlap in the observed images, becoming indistinguishable and resulting in unresolved wide binaries, which are difficult to detect using traditional methods. Utilizing deep learning, we present a method to identify unresolved wide binaries by analyzing the point-spread function (PSF) morphology of telescopes. Our trained model demonstrates exceptional performance in differentiating between single stars and unresolved binaries with separations ranging from 0.1 to 2 physical pixels, where the PSF FWHM is ~2 pixels, achieving an accuracy of 97.2% for simulated data from the Chinese Space Station Telescope. We subsequently tested our method on photometric data of NGC 6121 observed by the Hubble Space Telescope. The trained model attained an accuracy of 96.5% and identified 18 wide binary candidates with separations between 7 and 140 au. The majority of these wide binary candidates are situated outside the core radius of NGC 6121, suggesting that they are likely first-generation stars, which is in general agreement with the results of Monte Carlo simulations. Our PSF-based method shows great promise in detecting unresolved wide binaries and is well suited for observations from space-based telescopes with stable PSF. In the future, we aim to apply our PSF-based method to next-generation surveys such as the China Space Station Optical Survey, where a larger-field-of-view telescope will be capable of identifying a greater number of such wide binaries.

Keywords: Globular star clusters, Convolutional neural networks, Binary stars, Photometry
A Coronal Mass Ejection Source Region Catalog and Their Associated Properties. The primary objective of this study is to connect coronal mass ejections (CMEs) to their source regions, primarily to create a CME source region catalog, and secondarily to probe the influence that the source regions have on the different statistical properties of CMEs. We create a source region catalog for 3327 CMEs from 1998 to 2017, thus capturing the different phases of cycles 23 and 24. The identified source regions are segregated into three classes-active regions, prominence eruptions, and active prominences-while the CMEs are segregated into slow and fast groups, based on their average projected speeds. We find the contributions of these three source region types to the occurrences of slow and fast CMEs to be different in the above period. A study of the distribution of the average speeds reveals different power laws for CMEs originating from different sources, and the power laws are different during the different phases of cycles 23 and 24. A study of the statistical latitudinal deflections shows equatorward deflections, while the magnitudes of the deflections again bear imprints of the source regions. An east-west asymmetry is also noted, particularly in the rising phase of cycle 23, with the presence of active longitudes for the CMEs, with a preference toward the western part of the Sun. Our results show that different aspects of CME kinematics bear strong imprints of the source regions they originate from, thus indicating the existence of different ejection and/or propagation mechanisms of these CMEs.

Keywords: Solar cycle, Solar coronal mass ejections