Sazuna/UAT_keywords huggingface dataset:
Cross Observatory Coordination with tilepy: A Novel Tool for Observations of Multimessenger Transient Events. Time-domain astrophysics has leaped forward with the direct discovery of gravitational waves and the emergence of new generation instruments for multimessenger studies. The capacity of the multimessenger multiwavelength community to effectively pursue follow-up observations is hindered by the suboptimal localization of numerous transient events and the escalating volume of alerts. Thus, we have developed an effective tool to overcome the observational and technical hurdles inherent in the emerging field of multimessenger astrophysics. We present tilepy, a Python package for the automatic scheduling of follow-up observations of poorly localized transient events. It is ideally suited to tackle the challenge of complex follow-up in mid- and small-field-of-view telescope campaigns, with or without human intervention. We demonstrate the capabilities of tilepy in the realm of multiobservatory, multiwavelength campaigns, to cover the localization uncertainty region of various events ultimately aiming at pinpointing the source of the multimessenger emission. The tilepy code is publicly available on GitHub and is sufficiently flexible to be employed either automatically or in a customized manner, tailored to collaboration and individual requirements. tilepy is also accessible via a public API and through the Astro-COLIBRI platform.

Keywords: Observational astronomy, Gamma-ray bursts, Gravitational wave sources, Transient detection, Astronomical methods
Se-ResNet+SVM Model: An Effective Method of Searching for Hot Subdwarfs from LAMOST. This paper presents a robust neural network approach for identifying hot subdwarfs. Our method leveraged the Squeeze-and-Excitation Residual Network to extract abstract features, which were combined with experience features to create hybrid features. These hybrid features were then classified using a support vector machine. To enhance accuracy, we employed a two-stage procedure. In the first stage, a binary classification model was constructed to distinguish hot subdwarfs, achieving a precision of 98.55% on the test set. In the second stage, a four-class classification model was employed to further refine the candidates, achieving a precision of 91.75% on the test set. Using the binary classification model, we classified 333,534 spectra from LAMOST DR8, resulting in a catalog of 3086 hot subdwarf candidates. Subsequently, the four-class classification model was applied to filter these candidates further. When applying thresholds of 0.5 and 0.9, we identified 2132 and 1247 candidates, respectively. Among these candidates, we visually inspected their spectra and identified 58 and 30 new hot subdwarfs, respectively, resulting in a precision of 82.04% and 88.21% for these discoveries. Furthermore, we evaluated the 3086 candidates obtained in the first stage and identified 168 new hot subdwarfs, achieving an overall precision of 62.54%. Lastly, we trained a Squeeze-and-Excitation regression model with mean absolute error values of 3009 K for T eff, 0.20 dex for log g, and 0.42 dex for log(nHe/nH). Using this model, we predicted the atmospheric parameters of these 168 newly discovered hot subdwarfs.

Keywords: A subdwarf stars, Stellar classification, Convolutional neural networks, Stellar types
An Imaging and Spectroscopic Exploration of the Dusty Compact Obscured Nucleus Galaxy Zw 049.057. Zw 049.057 is a moderate-mass, dusty, early-type galaxy that hosts a powerful compact obscured nucleus (CON, L FIR,CON ≥ 1011 L ☉). The resolution of the Hubble Space Telescope enabled measurements of the stellar light distribution and characterization of dust features. Zw 049.057 is inclined with a prominent three-zone disk; the R ≈ 1 kpc star-forming inner dusty disk contains molecular gas, a main disk with less dust and an older stellar population, and a newly detected outer stellar region at R &gt; 6 kpc with circular isophotes. Previously unknown polar dust lanes are signatures of a past minor merger that could have warped the outer disk to near face-on. Dust transmission measurements provide lower limit gas mass estimates for dust features. An extended region with moderate optical depth and M ≥ 2 × 108 M ☉ obscures the central 2 kpc. Optical spectra show strong interstellar Na D absorption with a constant velocity across the main disk, likely arising in this extraplanar medium. Opacity measurements of the two linear dust features, pillars, give a total mass of ≥106 M ☉, flow rates of ≥2 M ☉ yr−1, and few Myr flow times. Dust pillars are associated with the CON and are visible signs of its role in driving large-scale feedback. Our assessments of feedback processes suggest gas recycling sustains the CON. However, radiation pressure driven mass loss and efficient star formation must be avoided for the active galactic nucleus to retain sufficient gas over its lifespan to produce substantial mass growth of the central black hole. *Based in part on observations obtained with the Southern African Large Telescope (SALT).

Keywords: Interstellar dust, Active galaxies, Galaxy photometry, Galaxy mergers, Galaxy evolution, Galaxy spectroscopy, Galaxy processes
CMBFSCNN: Cosmic Microwave Background Polarization Foreground Subtraction with a Convolutional Neural Network. In our previous study, we introduced a machine learning technique, namely Cosmic Microwave Background Foreground Subtraction with Convolutional Neural Networks (CMBFSCNN), for the removal of foreground contamination in cosmic microwave background (CMB) polarization data. This method was successfully employed on actual observational data from the Planck mission. In this study, we extend our investigation by considering the CMB lensing effect in simulated data and utilizing the CMBFSCNN approach to recover the CMB lensing B-mode power spectrum from multifrequency observational maps. Our method is first applied to simulated data with the performance of the CMB-S4 experiment. We achieve reliable recovery of the noisy CMB Q (or U) maps with a mean absolute difference of 0.016 ± 0.008 μK (or 0.021 ± 0.002 μK) for the CMB-S4 experiment. To address the residual instrumental noise in the foreground-cleaned map, we employ a "half-split maps" approach, where the entire data set is divided into two segments sharing the same sky signal but having uncorrelated noise. Using cross-correlation techniques between two recovered half-split maps, we effectively reduce instrumental noise effects at the power spectrum level. As a result, we achieve precise recovery of the CMB EE and lensing B-mode power spectra. Furthermore, we also extend our pipeline to full-sky simulated data with the performance of the LiteBIRD experiment. As expected, various foregrounds are cleanly removed from the foregrounds contamination observational maps, and recovered EE and lensing B-mode power spectra exhibit excellent agreement with the true results. Finally, we discuss the dependency of our method on the foreground models.

Keywords: Observational cosmology, Cosmic microwave background radiation, Convolutional neural networks
A Comparative Study of Ultraluminous Infrared Galaxies in the IRAS and SDSS Surveys. We present a comprehensive study of ultraluminous infrared galaxies (ULIRGs), leveraging data from the Infrared Astronomical Satellite Faint Source Catalogue and the spectroscopic catalog in the Sloan Digital Sky Survey Data Release 16. Our meticulous crossmatching technique significantly enhances the reliability of ULIRG identification, resulting in the identification of 283 reliable ULIRGs, including 102 new detections, while discarding 120 previously reported false sources. Covering a redshift range of z = 0.018–0.996, with a median redshift of , our uniform sample reveals apparent interaction features in approximately 40% of ULIRGs, increasing to 92% for those with z &lt; 0.1. Through optical spectra analysis, it is indicated that over 58% of ULIRGs host an active galactic nucleus (AGN), which is twice as high as detections based solely on infrared colors. Moreover, a pronounced excess of radio emissions associated with AGN activity results in a steeper radio–far-infrared correlation. Notably, Type I ULIRGs exhibit properties similar to those of narrow-line Seyfert 1 galaxies, with an elevated incidence rate of Mg II broad absorption lines (16.7%), surpassing that of typical optically selected quasars by over tenfold, consistent with current evolutionary models. We anticipate that forthcoming telescopes such as the China Space Station Telescope and Leighton Chajnantor Telescope will provide deeper insights into ULIRG morphology, dust distribution, molecular gas, and AGN activity.

Keywords: Starburst galaxies, Galaxy formation, Active galaxies, Infrared galaxies
Identification of Carbon Stars in LAMOST DR9 Based on Deep Learning. Carbon stars play a crucial role in astronomical research and are significant for understanding stellar evolution, measuring cosmic distances, and studying galaxy kinematics. In recent years, identifying carbon stars using machine learning methods and traditional line-index methods has become a research hotspot, but there are still limitations regarding accuracy and automation. In this study, we propose to build a five-class model to identify carbon stars using spectral data from LAMOST DR9. The model achieved 99.45% precision and 91.21% recall on the carbon star testing set. We conducted independent tests using a sample of 1333 known carbon stars that were not used in the training and testing phases, and our model ultimately identified 1199 carbon stars. On this basis, we used this model to screen 11,226,252 spectra of LAMOST DR9 and identified 4383 carbon stars, including 1197 newly discovered carbon stars. To gain a more comprehensive understanding of the characteristics of the 4383 carbon stars obtained, further visual inspection of these spectra was performed to provide more detailed carbon star subtypes.

Keywords: Stellar classification, Carbon stars, Convolutional neural networks
AstroSR: A Data Set of Galaxy Images for Astronomical Superresolution Research. In the past decade, various sky surveys with a wide range of wavelengths have been conducted, resulting in an explosive growth of survey data. There may be overlapping regions between different surveys, but the data quality and brightness are different. The translation of data quality between different surveys provides benefits for studying the properties of galaxies in specific regions that high-quality surveys have not yet covered. In this paper, we create a data set for analyzing the quality transformation of different surveys, AstroSR, using the galaxy images from overlapping regions from the Subaru/Hyper Suprime-Cam (HSC) and the Sloan Digital Sky Survey (SDSS). In addition, we use superresolution (SR) techniques to improve the quality of low-resolution images in the AstroSR and explore whether the proposed data set is suitable for SR. We try four representative models: EDSR, RCAN, ENLCN, and SRGAN. Finally, we compare the evaluation metrics and visual quality of the above methods. SR models trained with AstroSR successfully generate HSC-like images from SDSS images, which enhance the fine structure present in the SDSS images while retaining important morphological information and increasing the brightness and signal-to-noise. Improving the resolution of astronomical images by SR can improve the size and quality of the sky surveys. The data set proposed in this paper provides strong data support for the study of galaxy SR and opens up new research possibilities in astronomy. The data set is available online at https://github.com/jiaweimmiao/AstroSR.

Keywords: Computational astronomy, Astronomy data modeling, Astronomy data acquisition, Optical astronomy, Galaxy equators, Convolutional neural networks, Astronomy data analysis, Ground-based astronomy, Astronomy data visualization, Galaxies
X-Ray Winds in Nearby-to-distant Galaxies (X-WING). I. Legacy Surveys of Galaxies with Ultrafast Outflows and Warm Absorbers in z ∼ 0─4. As an inaugural investigation under the X-ray Winds In Nearby-to-distant Galaxies (X-WING) program, we assembled a data set comprising 132 active galactic nuclei (AGNs) spanning redshifts z ∼ 0─4 characterized by blueshifted absorption lines indicative of X-ray winds. Through an exhaustive review of previous research, we compiled the outflow parameters for 583 X-ray winds, encompassing key attributes such as outflow velocities (V out), ionization parameters (ξ), and hydrogen column densities. By leveraging the parameters V out and ξ, we systematically categorized the winds into three distinct groups: ultrafast outflows (UFOs), low-ionization parameter (low-IP) UFOs, and warm absorbers (WAs). Strikingly, a discernible absence of linear correlations in the outflow parameters, coupled with distributions approaching instrumental detection limits, was observed. Another notable finding was the identification of a velocity gap around V out ∼ 10,000 km s−1. This gap was particularly evident in the winds detected via absorption lines within the ≲2 keV band, indicating disparate origins for low-IP UFOs and WAs. In cases involving Fe XXV/Fe XXVI lines, where the gap might be attributed to potential confusion between emission/absorption lines and the Fe K-edge, the possibility of UFOs and galactic-scale WAs being disconnected is considered. An examination of the outflow and dust sublimation radii revealed a distinction: UFOs appear to consist of dust-free material, whereas WAs likely comprise dusty gas. From 2024, the X-Ray Imaging and Spectroscopy Mission is poised to alleviate observational biases, providing insights into the authenticity of the identified gap, a pivotal question in comprehending AGN feedback from UFOs.

Keywords: Observational astronomy, Black hole physics, Supermassive black holes, X-ray active galactic nuclei, Active galactic nuclei
Atomic Transition Probabilities for Ultraviolet and Optical Lines of Tm II. We report new branching fraction measurements for 224 ultraviolet and optical transitions of Tm II. These transitions range in wavelength (wavenumber) from 2350 to 6417 Å (42,532–15,579 cm‑1) and originate in 13 odd-parity and 24 even-parity upper levels. Thirty-five of the 37 levels, accounting for 213 of the 224 transitions, are studied for the first time. Branching fractions are determined for two levels studied previously for comparison to earlier results. The levels studied for the first time are high lying, ranging in energy from 35,753 to 54,989 cm‑1. The branching fractions are determined from emission spectra from two different high-resolution spectrometers. These are combined with radiative lifetimes reported in an earlier study to produce a set of transition probabilities and log(gf) values with accuracy ranging from 5% to 30%. Comparison is made to experimental and theoretical transition probabilities from the literature where such data exist. These new log(gf) values are used to derive an abundance from one previously unused Tm II line in the UV spectrum of the r-process-enhanced metal-poor star HD 222925, and this abundance is consistent with previous determinations based on other Tm II lines. *Based on observations made with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc. under NASA contract NAS5-26555 (program GO-15657). This paper also includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

Keywords: Atomic spectroscopy, Transition probabilities, Stellar abundances
Automatic Parallel Tempering Markov Chain Monte Carlo with Nii-C. Due to the high dimensionality or multimodality that is common in modern astronomy, sampling Bayesian posteriors can be challenging. Several publicly available codes based on different sampling algorithms can solve these complex models, but the execution of the code is not always efficient or fast enough. The article introduces a C language general-purpose code, Nii-C, that implements a framework of automatic parallel tempering Markov Chain Monte Carlo. Automatic in this context means that the parameters that ensure an efficient parallel tempering process can be set by a control system during the inital stages of a sampling process. The autotuned parameters consist of two parts, the temperature ladders of all parallel tempering Markov Chains and the proposal distributions for all model parameters across all parallel tempering chains. In order to reduce dependencies in the compilation process and increase the code's execution speed, Nii-C code is constructed entirely in the C language and parallelized using the message-passing interface protocol to optimize the efficiency of parallel sampling. These implementations facilitate rapid convergence in the sampling of high-dimensional and multimodal distributions, as well as the expeditious code execution time. The Nii-C code can be used in various research areas to trace complex distributions due to its high sampling efficiency and quick execution speed. This article presents a few applications of the Nii-C code.

Keywords: Astrostatistics tools, Bayesian statistics, Astrometric exoplanet detection, Astrostatistics
Adiabatic Mass Loss in Binary Stars. IV. Low- and Intermediate-mass Helium Binary Stars. The unstable mass transfer situation in binary systems will asymptotically cause the adiabatic expansion of the donor star and finally lead to the common envelope phase. This process could happen in helium binary systems once the helium donor star fills its Roche-lobe. We have calculated the adiabatic mass-loss model of naked helium stars with a mass range of 0.35 M ⊙–10 M ⊙, and every mass sequence evolved from the helium-zero-age main sequence to the cooling track of white dwarf or carbon ignition. In consideration of the influence of stellar wind, massive helium stars are not considered in this paper. Comparing the stellar radius with the evolution of the Roche-lobe under the assumption of conservative mass transfer, we give the critical mass ratio q crit = M He/M accretor as the binary stability criteria of low- and intermediate-mass helium binary stars. On the helium main sequence, the result shows 1.0 &lt; q crit &lt; 2.6, which is more unstable than the classical result of polytropic model q crit = 3. After the early helium Hertzsprung Gap, the q crit quickly increases even larger than 10 (more stable compared with the widely used result of q crit = 4), which is dominated by the expansion of the radiative envelope. Our result could be useful for these quick mass transfer binary systems such as AM CVns, ultra-compact X-ray binaries, and helium novae, and it could guide the binary population synthesis for the formation of special objects such as type Ia supernova and gravitational wave sources.

Keywords: Helium-rich stars, Common envelope evolution, Binary stars, Stellar evolution
pop-cosmos: A Comprehensive Picture of the Galaxy Population from COSMOS Data. We present pop-cosmos: a comprehensive model characterizing the galaxy population, calibrated to 140,938 (r &lt; 25 selected) galaxies from the Cosmic Evolution Survey (COSMOS) with photometry in 26 bands from the ultraviolet to the infrared. We construct a detailed forward model for the COSMOS data, comprising: a population model describing the joint distribution of galaxy characteristics and its evolution (parameterized by a flexible score-based diffusion model); a state-of-the-art stellar population synthesis model connecting galaxies' intrinsic properties to their photometry; and a data model for the observation, calibration, and selection processes. By minimizing the optimal transport distance between synthetic and real data, we are able to jointly fit the population and data models, leading to robustly calibrated population-level inferences that account for parameter degeneracies, photometric noise and calibration, and selection. We present a number of key predictions from our model of interest for cosmology and galaxy evolution, including the mass function and redshift distribution; the mass─metallicity-redshift and fundamental metallicity relations; the star-forming sequence; the relation between dust attenuation and stellar mass, star formation rate, and attenuation-law index; and the relation between gas-ionization and star formation. Our model encodes a comprehensive picture of galaxy evolution that faithfully predicts galaxy colors across a broad redshift (z &lt; 4) and wavelength range.

Keywords: Cosmology, Galaxy chemical evolution, Cosmological parameters, Galaxy abundances, Galaxy evolution, Redshift surveys
Precise Transit Photometry Using TESS. II. Revisiting 28 Additional Transiting Systems with Updated Physical Properties. Precise physical properties of the known transiting exoplanets are essential for their precise atmospheric characterization using modern and upcoming instruments. Leveraging the large volume of high-signal-to-noise-ratio photometric follow-up data from TESS, highly precise physical properties can be estimated for these systems, especially for those discovered using ground-based instruments prior to the TESS mission. In this work, I have used the publicly available TESS follow-up data for 28 transiting systems with 10 &lt; V mag &lt; 10.5, with an aim to update their known physical properties. The observed lightcurves have been analyzed by implementing a state-of-the-art critical noise treatment algorithm to effectively reduce both time-correlated and uncorrelated noise components, using sophisticated techniques like wavelet denoising and Gaussian-process regression. Compared with the previous studies, the estimated transit parameters are found to be more precise for most of the targets, including a few cases where a larger space-based instrument like Spitzer, Kepler, or CHEOPS has been used in the previous study. The large volume of transit observations used for each target has also resulted in a more accurate estimation of the physical properties, as this overcomes any error in parameter estimations from bias present in a smaller volume of data. Thus, comparing with the literature values, statistically significant improvements in the known physical properties of several targeted systems have been reported from this work. The large volume of transit-timing information from the analyses was also used to search for transit-timing variation trends in these targets, which has resulted in no significant detection.

Keywords: Hot Jupiters, Exoplanet astronomy, Gaussian Processes regression, Wavelet analysis, Transit photometry
The Self-organized Criticality Behaviors of Pulses in Magnetar Bursts. The overall temporal and spectral characteristics (e.g., duration, fluence, peak flux, peak count rate, and total counts) of X-ray bursts (XRBs) originating from magnetars have been extensively studied to confirm their self-organized criticality (SOC) behaviors. However, for the pulses in XRBs, which are an important part of unraveling radiation processes such as magnetic reconnection and crustal rupture, their variable statistical characteristics are still unclear. In this work, we investigate the distributions of fluctuations in duration, waiting time, peak count rate, and total counts of pulses within bursts from two active and prolific magnetars, SGR J1935+2154 and SGR J1550-5418, observed by Fermi's Gamma-ray Burst Monitor, Insight-HXMT, and GECAM. We report that the waiting time for pulses follows SOC, whereas previous studies indicated for bursts do not, possibly due to incomplete observations. Besides, the duration, peak count rate, and total counts for pulses are also SOC behaviors. The α-values for the duration of pulses for both magnetars are ∼2, and the inferred Euclidean dimension S is 3. Our findings provide evidence for the SOC of each radiation process during a burst, for example, multiple pulses produced by multiple magnetic reconnections triggered by a single starquake. Finally, the similar statistical characteristics for pulses from both magnetars lend support to their shared radiation processes.

Keywords: Magnetars