Sazuna/UAT_keywords huggingface dataset:
ExoMolHR: A Relational Database of Empirical High-resolution Molecular Spectra. ExoMolHR is an empirical, high-resolution molecular spectrum calculator for the high-temperature molecular line lists available from the ExoMol molecular database. Uncertainties, where available, in recommended ExoMol data sets are used to select highly accurate spectral lines. These lines largely rely on empirical energy levels generated through the MARVEL procedure, which is being systematically used to improve the energy and transition data provided by the ExoMol database. The freely accessible ExoMolHR database provides line positions with calculated intensities for a user-specified wavenumber/wavelength range and temperature. Spectra can be plotted on the ExoMolHR website https://www.exomol.com/exomolhr/ or downloaded as a .csv file. Cross sections can be calculated using the Python program PyExoCross. The ExoMolHR database currently provides 24,307,135 spectral lines for 33 molecules and 58 isotopologues; these numbers will increase as the ExoMol database is updated.

Keywords: Molecular spectroscopy
Solar Flare Forecasting Using Hybrid Neural Networks. Solar flares are one of the most intense solar activities, the result of a sudden large-scale release of magnetic energy in the form of electromagnetic radiation and energetic particles. Intense solar flares can severely threaten communication and navigation systems, oil pipelines, and power grids on Earth. Therefore, it is crucial to establish highly accurate solar flare prediction models to enable humans to anticipate solar flare eruptions in advance, thereby reducing human and economic losses. In this paper, we utilized the solar active region (AR) magnetogram provided by the Solar Dynamics Observatory's Helioseismic and Magnetic Imager and the associated feature parameters of the magnetic field; specifically, the feature vectors of the magnetic field's spatial structure characteristics and the magnetic field feature parameters are fused to predict solar flares. We built two solar flare prediction models based on a combination of convolutional neural networks (CNN) and a temporal convolutional network (TCN), called CNN-TCN, and predicted whether a ≥C- or ≥M-class flare event would erupt in ARs in the next 24 hr, respectively. Then, after training and testing our model, we focused on the true skill statistic (TSS). Through the model superiority discussion, the model obtained high average TSS values, with the ≥C and ≥M models achieving TSS scores of 0.798 ± 0.032 and 0.850 ± 0.074, respectively, suggesting that our models have good forecasting performance. We speculate that some key features automatically extracted by our model may not have been previously identified, and these features could provide important clues for studying the mechanisms of flares.

Keywords: Solar flares
APOKASC-3: The Third Joint Spectroscopic and Asteroseismic Catalog for Evolved Stars in the Kepler Fields. In the third APOKASC catalog, we present data for the complete sample of 15,808 evolved stars with APOGEE spectroscopic parameters and Kepler asteroseismology. We used 10 independent asteroseismic analysis techniques and anchor our system on fundamental radii derived from Gaia L and spectroscopic Teff. We provide evolutionary state, asteroseismic surface gravity, mass, radius, age, and the data used to derive them for 12,418 stars. This includes 10,036 exceptionally precise measurements, with median fractional uncertainties in  , ∆ν, mass, radius, and age of 0.6%, 0.6%, 3.8%, 1.8%, and 11.1%, respectively. We provide more limited data for 1624 additional stars that either have lower-quality data or are outside of our primary calibration domain. Using lower red giant branch (RGB) stars, we find a median age for the chemical thick disk of 9.14 ± 0.05(ran) ± 0.9(sys) Gyr with an age dispersion of 1.1 Gyr, consistent with our error model. We calibrate our red clump (RC) mass loss to derive an age consistent with the lower RGB and provide asymptotic GB and RGB ages for luminous stars. We also find a sharp upper-age boundary in the chemical thin disk. We find that scaling relations are precise and accurate on the lower RGB and RC, but they become more model dependent for more luminous giants and break down at the tip of the RGB. We recommend the use of multiple methods, calibration to a fundamental scale, and the use of stellar models to interpret frequency spacings.

Keywords: Stellar ages, Stellar pulsations, Stellar populations, Stellar masses, Asteroseismology, Stellar evolution
A Population Analysis of 20 Exoplanets Observed from Optical to Near-infrared Wavelengths with the Hubble Space Telescope: Evidence for Widespread Stellar Contamination. We present a population study of 20 exoplanets, ranging from Neptune-like to inflated hot-Jupiter planets, observed during transit with the Space Telescope Imaging Spectrograph (STIS) and Wide Field Camera 3 (WFC3) instruments on board the Hubble Space Telescope (HST). To obtain spectral information from the near-ultraviolet to the near-infrared, we reanalyzed 16 WFC3 and over 50 STIS archival data sets with our dedicated HST pipeline. We also include 24 WFC3 data sets previously reduced with the same software. Across our target sample, we observe significant divergence among multiple observations conducted with the same STIS grating at various epochs, while we do not detect variations in the WFC3 data sets. These results are suggestive of stellar contamination, which we have investigated further using known Bayesian tools and other tailored metrics, facilitating a more objective assessment of stellar activity intensity within each system. Our findings reveal that stellar activity contaminates up to half of the studied exoplanet atmospheres, albeit at varying extents. Accounting for stellar activity can significantly alter planetary atmospheric parameters like molecular abundances (up to 6 orders of magnitude) and temperature (up to 145%), contrasting with the results of analyses that neglect activity. Our results emphasize the importance of considering the effects of stellar contamination in exoplanet transit studies; this issue is particularly true for data sets obtained with facilities that do not cover the optical and/or UV spectral range where the activity is expected to be more impactful but also more easily detectable. Our results also provide a catalog of potentially active stars for further investigation and monitoring.

Keywords: Bayesian statistics, Astronomy data reduction, Surveys, Hubble Space Telescope, Stellar activity, Exoplanet atmospheres
Testing General Relativity Using Large-scale Structure Photometric Redshift Surveys and the Cosmic Microwave Background Lensing Effect. The EG statistic provides a valuable tool for evaluating the predictions of general relativity (GR) by probing the relationship between gravitational potential and galaxy clustering on cosmological scales within the observable Universe. In this study, we constrain the EG statistic using photometric redshift data from the Dark Energy Survey (DES) MagLim sample in combination with the Planck 2018 cosmic microwave background (CMB) lensing map. Unlike spectroscopic redshift surveys, photometric redshift measurements are subject to significant redshift uncertainties, making it challenging to constrain the redshift distortion parameter β with high precision. We adopt a new definition for this parameter, β(z) = fσ8(z)/bσ8(z). In this formulation, we reconstruct the growth rate of structure, fσ8(z), using the artificial neural network method, while simultaneously utilizing model-independent constraints on the parameter bσ8(z), directly obtained from the DES collaboration. After obtaining the angular power spectra   (galaxy–galaxy) and   (galaxy–CMB lensing) from the combination of DES photometric data and Planck lensing, we derive new measurements of the EG statistic: EG = 0.354 ± 0.146, 0.452 ± 0.092, 0.414 ± 0.069, and 0.296 ± 0.069 (68% confidence limit) across four redshift bins z = 0.30, 0.47, 0.63, and 0.80, respectively, which are consistent with the predictions of the standard Lambda cold dark matter model. Finally, we forecast the EG statistic using future photometric redshift data from the China Space Station Telescope, combined with lensing measurements from the CMB-S4 project, indicating an achievable constraint on EG of approximately 1%, improving the precision of tests for GR on cosmological scales.

Keywords: Weak gravitational lensing, Observational cosmology, Cosmic microwave background radiation, Large-scale structure of the universe
The Hobby─Eberly Telescope Dark Energy Experiment Survey (HETDEX) Active Galactic Nuclei Catalog: The Fourth Data Release. We present the active galactic nuclei (AGN) catalog from the fourth data release (HDR4) of the Hobby─Eberly Telescope Dark Energy Experiment Survey (HETDEX). HETDEX is an untargeted spectroscopic survey. HDR4 contains 345,874 Integral Field Unit observations from 2017 January to 2023 August covering an effective area of 62.9 deg2. With no imaging preselection, our spectroscopic confirmed AGN sample includes low-luminosity AGN, narrow-line AGN, and/or red AGN down to g ∼ 25. This catalog has 15,940 AGN across the redshifts of z = 0.1 ∼ 4.6, giving a raw AGN number density of 253.4 deg−2. Among them, 10,499 (66%) have redshifts either confirmed by line pairs or matched to the Sloan Digital Sky Survey Quasar Catalog. For the remaining 5441 AGN, 2083 are single broad-line AGN candidates, while the remaining 3358 are single intermediate broad-line (full width at half-maximum, FWHM ∼1200 km s−1) AGN candidates. A total of 4060 (39%) of the 10,499 redshift-confirmed AGN have emission-line regions 3σ more extended than the image quality, which could be strong outflows blowing into the outskirts of the host galaxies or ionized intergalactic medium.

Keywords: Active galactic nuclei
The Eclipsing Binaries via Artificial Intelligence. II. Need for Speed in PHOEBE Forward Models. In modern astronomy, the quantity of data collected has vastly exceeded the capacity for manual analysis, necessitating the use of advanced artificial intelligence (AI) techniques to assist scientists with the most labor-intensive tasks. AI can optimize simulation codes where computational bottlenecks arise from the time required to generate forward models. One such example is PHOEBE, a modeling code for eclipsing binaries (EBs), where simulating individual systems is feasible, but analyzing observables for extensive parameter combinations is highly time consuming. To address this, we present a fully connected feedforward artificial neural network (ANN) trained on a data set of over one million synthetic light curves generated with PHOEBE. Optimization of the ANN architecture yielded a model with six hidden layers, each containing 512 nodes, providing an optimized balance between accuracy and computational complexity. Extensive testing enabled us to establish ANN's applicability limits and to quantify the systematic and statistical errors associated with using such networks for EB analysis. Our findings demonstrate the critical role of dilution effects in parameter estimation for EBs, and we outline methods to incorporate these effects in AI-based models. This proposed ANN framework enables a speedup of over 4 orders of magnitude compared to traditional methods, with systematic errors not exceeding 1%, and often as low as 0.01%, across the entire parameter space.

Keywords: Astronomy data modeling, Binary stars, Astronomy software, Neural networks, Light curves, Eclipsing binary stars
An Overview of Solar Orbiter Observations of Interplanetary Shocks in Solar Cycle 25. Interplanetary (IP) shocks are fundamental constituents of the heliosphere, where they form as a result of solar activity. We use previously unavailable measurements of IP shocks in the inner heliosphere provided by Solar Orbiter, and present a survey of the first 100 shocks observed in situ at different heliocentric distances during the rising phase of solar cycle 25. The fundamental shock parameters (shock normals, shock normal angles, shock speeds, compression ratios, Mach numbers) have been estimated and studied as a function of heliocentric distance, revealing a rich scenario of configurations. Comparison with large surveys of shocks at 1 au shows that shocks in the quasi-parallel regime and with high speed are more commonly observed in the inner heliosphere. The wave environment of the shocks has also been addressed, with about 50% of the events exhibiting clear shock-induced upstream fluctuations. We characterize energetic particle responses to the passage of IP shocks at different energies, often revealing complex features arising from the interaction between IP shocks and preexisting fluctuations, including solar wind structures being processed upon shock crossing. Finally, we give details and guidance on the access use of the present survey, available on the EU-project "Solar Energetic Particle Analysis Platform for the Inner Heliosphere" website. The algorithm used to identify shocks in large data sets, now publicly available, is also described.

Keywords: Solar activity, Space plasmas, Interplanetary particle acceleration, Interplanetary shocks
GR-Athena++: General-relativistic Magnetohydrodynamics Simulations of Neutron Star Spacetimes. We present the extension of GR-Athena++ to general-relativistic magnetohydrodynamics (GRMHD) for applications to neutron star spacetimes. The new solver couples the constrained transport implementation of Athena++ to the Z4c formulation of the Einstein equations to simulate dynamical spacetimes with GRMHD using oct-tree adaptive mesh refinement. We consider benchmark problems for isolated and binary neutron star spacetimes demonstrating stable and convergent results at relatively low resolutions and without grid symmetries imposed. The code correctly captures magnetic field instabilities in nonrotating stars with total relative violation of the divergence-free constraint of 10‑16. It handles evolutions with a microphysical equation of state and black hole formation in the gravitational collapse of a rapidly rotating star. For binaries, we demonstrate correctness of the evolution under the gravitational radiation reaction and show convergence of gravitational waveforms. We showcase the use of adaptive mesh refinement to resolve the Kelvin–Helmholtz instability at the collisional interface in a merger of magnetised binary neutron stars. GR-Athena++ shows strong scaling efficiencies above 80% in excess of 105 CPU cores and excellent weak scaling is shown up to ∼5 × 105 CPU cores in a realistic production setup. GR-Athena++ allows for the robust simulation of GRMHD flows in strong and dynamical gravity with exa-scale computers.

Keywords: Neutron stars, Magnetohydrodynamics, Black holes, Astronomy software, Compact binary stars, General relativity, Gravitational waves, Magnetohydrodynamical simulations
JADES Data Release 3: NIRSpec/Microshutter Assembly Spectroscopy for 4000 Galaxies in the GOODS Fields. We present the third data release of the JWST Advanced Deep Extragalactic Survey (JADES), providing both imaging and spectroscopy in the two GOODS fields. Spectroscopy consists of medium-depth and deep NIRSpec/microshutter assembly spectra of 4000 targets, covering the spectral range 0.6─5.3 μm and observed with both the low-dispersion prism (R = 30─300) and all three medium-resolution gratings (R = 500─1500). We describe the observations, data reduction, sample selection, and target allocation. We measured 2375 redshifts (2053 from multiple emission lines); our targets span the range from z = 0.5 up to z = 13, including 404 at z &gt; 5. The data release includes 2D and 1D fully reduced spectra, with slit-loss corrections and background subtraction optimized for point sources. We also provide redshifts and signal-to-noise ratio &gt; 5 emission-line flux catalogs for the prism and grating spectra, and concise guidelines on how to use these data products. Alongside spectroscopy, we are also publishing fully calibrated NIRCam imaging, which enables studying the JADES sample with the combined power of imaging and spectroscopy. Together, these data provide the largest statistical sample to date to characterize the properties of galaxy populations in the first billion years after the Big Bang.

Keywords: Early universe, Galaxy formation, Surveys, Galaxy evolution, Reionization
GECAM Observations of the Galactic Magnetar SGR J1935+2154 during the 2021 and 2022 Burst Active Episodes. I. Burst Catalog. Magnetars are neutron stars with ultrahigh magnetic fields (~1014─1015 G). The magnetar SGR J1935+2154 is not only one of the most active magnetars detected so far, but also the unique confirmed source of fast radio bursts. The Gravitational Wave High-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is dedicated to monitor gamma-ray transients all over the sky, including magnetar short bursts. Here we report the GECAM observations of the burst activity of SGR J1935+2154 from 2021 January to 2022 December, which results in a unique and valuable data set for this important magnetar. With a targeted search of GECAM data, 159 bursts from SGR J1935+2154 are detected by GECAM-B while 97 bursts are detected by GECAM-C, including the X-ray burst associated with a bright radio burst. We find that both the burst duration and the waiting time between two successive bursts follow lognormal distributions. The period of burst activity is 134 ± 20 days, thus the burst activity could be generally divided into four active episodes over these two years. Interestingly, the hardness ratio of X-ray bursts tends to be softer during these two years, especially during the active episode with radio bursts detected.

Keywords: Neutron stars, Magnetars, Soft gamma-ray repeaters
Photometric Stellar Parameters for 195,478 Kepler Input Catalog Stars. The stellar atmospheric parameters and physical properties of stars in the Kepler Input Catalog (KIC) are of great significance for the study of exoplanets, stellar activity, and asteroseismology. However, despite extensive effort over the past decades, accurate spectroscopic estimates of these parameters are available for only about half of the stars in the full KIC. In our work, by training relationships between photometric colors and spectroscopic stellar parameters from Gaia DR3, the Kepler-INT Survey, Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR10, and Galactic Evolution Experiment at Apache Point Observatory DR17, we have obtained atmospheric parameter estimates for over 195,000 stars, accounting for 97% of the total sample of KIC stars. We obtain 1σ uncertainties of 0.1 dex on metallicity [Fe/H], 100 K on effective temperature Teff, and 0.2 dex on surface gravity log g. In addition, based on these atmospheric parameters, we estimated the ages, masses, radii, and surface gravities of these stars using the commonly adopted isochrone-fitting approach. External comparisons indicate that the resulting precision for turnoff stars is 20% in age; for dwarf stars, it is 0.07 M⊙ in mass, 0.05 R⊙ in radius, and 0.12 dex in surface gravity; and for giant stars, it is 0.14 M⊙ in mass, 0.73 R⊙ in radius, and 0.11 dex in surface gravity.

Keywords: Fundamental parameters of stars, Sky surveys, Metallicity, Stellar ages
Stellar Loci. VIII. Photometric Metallicities for 100 Million Stars Based on Synthetic Gaia Colors. We apply the stellar locus method to synthetic (BP–RP)XPSP and (BP–G)XPSP colors derived from corrected Gaia BP/RP (XP) spectra to obtain precise estimates of metallicity for about 100 million stars in the Milky Way (34 million giants in the color range 0.6 &lt; (BP–RP)0 &lt; 1.75 and 65 million dwarfs in the color range 0.2 &lt; (BP–RP)0 &lt; 1.5). The submillimagnitude precision of the derived synthetic stellar colors enables estimates of metallicity for stars as low as [Fe/H] ∼ ‑4. Multiple validation tests indicate that the typical metallicity precision is between 0.05 and 0.1 dex for both dwarfs and giants at [Fe/H] = 0, as faint as G ∼ 16, and decreases to 0.15–0.25 dex at [Fe/H] = ‑2.0. For ‑4.0 &lt; [Fe/H] &lt; ‑3.0, the typical metallicity precision decreases to on the order of 0.4–0.5 dex, based on the results from the reference sample. Our achieved precision is comparable to or better than previous efforts using the entire XP spectra and about 3 times better than our previous work based on Gaia EDR3 colors. This opens up new opportunities for investigations of stellar populations, the formation and chemical evolution of the Milky Way, the chemistry of stars and star clusters, and the identification of candidate stars for subsequent high-resolution spectroscopic follow-up. The catalog is publicly available at doi:10.12149/101548.

Keywords: Fundamental parameters of stars, Metallicity, Astronomy data analysis, Milky Way Galaxy
Modeling Complex Organic Molecules' Formation in Cold Cores: Multiphase Models with Nonthermal Mechanisms. In recent years, a significant number of oxygen-bearing complex organic molecules (COMs) have been detected in the gas phase of cold dark clouds such as TMC-1. The formation of these COMs cannot be explained by diffusive mechanisms on grains and gas-phase reactions. This study investigates the formation of oxygen-bearing COMs in cold dark clouds using multiphase gas–grain models that incorporate cosmic ray-induced nondiffusive radiation chemistry and nonthermal sputtering desorption mechanisms. Additionally, we present the effects of varying elemental C/O ratio and different sputtering rates. We utilized an accelerated Gillespie algorithm, based on the regular Gillespie algorithm. The results of our models for dimethyl ether (CH3OCH3), methyl formate (HCOOCH3), acetaldehyde (CH3CHO), ethanol (C2H5OH), and methanol (CH3OH) show reasonable agreement with observations toward TMC-1, within a factor of 3. Out of the 94 species compared with observations, 63 show agreement within 1 order of magnitude, accounting for 67.02%. Overall inclusion of nonthermal mechanisms in multiphase models shows notable improvement of modeling on oxygen-bearing COMs in the interstellar medium.

Keywords: Interstellar medium, Astrochemistry
Energetic Transients Joint Analysis System for Multi-INstrument (ETJASMIN) for GECAM. II. Search, Verification, and Classification of Bursts. The Gravitational Wave High-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a dedicated mission consisting of multiple instruments on different spacecraft to monitor gamma-ray transients. To meet the requirement of GECAM, we developed the Energetic Transients Joint Analysis System for Multi-INstrument (ETJASMIN) pipeline, which has been extended to incorporate other instruments (such as Fermi-GBM, SVOM/GRM). In this work, we introduce the ETJASMIN pipeline with focus on the search, verification, and classification of gamma-ray transients (especially weak bursts) using data from GECAM-B, GECAM-C, and Fermi-GBM. For this pipeline, we implement a coherent algorithm to search for simultaneous signals in the light curves of multiple instruments, conduct a series of Monte Carlo simulations, and validate the pipeline performance with in-flight observation data. The results demonstrate that ETJASMIN can yield not only higher significance of burst search but also more reliable verification and classification of bursts jointly with multiple instruments compared to those derived with an individual instrument. Thus, ETJASMIN is particularly suitable for the exploitation of gamma-ray transients associated with multimessenger multiwavelength sources.

Keywords: Gamma-ray detectors, Gamma-ray transient sources, Astronomy data analysis