Sazuna/UAT_keywords huggingface dataset:
LATIS Data Release: ∼4200 Spectra of z ∼ 2─3 Galaxies, Redshifts, and Intergalactic Medium Tomography Maps. We present the data release of the Lyα Tomography IMACS Survey (LATIS), one of the largest optical spectroscopic surveys of faint high-redshift galaxies. The survey provides 7408 optical spectra of candidate z ∼ 2─3 galaxies and QSOs in the Canada─France─Hawaii Telescope Legacy Survey D1, D2 (COSMOS), and D4 fields. The R ∼ 1000 spectra were obtained using the Inamori Magellan Areal Camera and Spectrograph (IMACS) at the Magellan Baade telescope, with typical integrations of 12 hr. From these spectra, we measured 5575 high-confidence spectroscopic redshifts, of which 4176 are at z &gt; 1.7, thereby substantially increasing the number of public spectroscopic redshifts at z ≍ 2─3 in COSMOS and the other survey fields. The data release includes Lyα transmission fluctuations measured in 4.7 × 105 pixels, which were used to create 3D maps of the intergalactic medium (IGM) transmission spanning 1.65 deg2 and z = 2.2─2.8 at a resolution of 4 h−1 cMpc. These are the largest such maps to date and provide a novel tracer of large-scale structure in legacy fields. We also provide ancillary data, including mock surveys. The LATIS data will enable a variety of community studies of galaxy evolution, environments, and the IGM around cosmic noon.

Keywords: Intergalactic medium, Lyman-break galaxies, Redshift surveys, Lyman alpha forest
A Catalog of Filaments in the Central Molecular Zone. We present a catalog of 1.28 GHz radio filaments observed by MeerKAT over the innermost 200 pc of the Galaxy (roughly ±1 .° 5), which includes the central molecular zone. The catalog is generated by repurposing software developed for the automated detection of filaments in solar coronal loops. There are two parts to the catalog. The first part, the main catalog, provides a point-by-point listing of locations and basic observational properties along each detected filament. The second part is a summary catalog that provides a listing of mean, median, or total values of various properties for each filament. Tabulated quantities include position, length, curvature, brightness, and spectral index. The catalogs contain a heterogeneous mix of filamentary structures, including nonthermal radio filaments, and parts of supernova remnants and thermally emitting regions (e.g., H II regions). We discuss criteria for selecting useful subsamples of filaments from the catalogs, and some of the details encountered in examining filaments or selections of filaments from the catalogs.

Keywords: Galactic radio sources, Galactic center, Interstellar filaments, Interstellar synchrotron emission
Unveiling New Giant Radio Quasars from the TGSS Sky and Their Large-scale Environment. Giant radio quasars (GRQs) are radiatively efficient radio-loud active galactic nuclei that propel large-scale radio jets with projected lengths of more than 0.7 Mpc. We report the discovery of 53 new GRQs within a redshift range of 0.14─2.38, as well as 316 new nongiant extended radio quasars (NGERQs) within a redshift range of 0.037─3.356, from the TIFR GMRT Sky Survey Alternative Data Release 1. The projected lengths of the new GRQs range from 0.7 to ∼2.2 Mpc, and the projected lengths of the new NGERQs range from 67 to 695 kpc. We found that the spectral indices of GRQs are statistically similar to those of NGERQs. We have also investigated the large-scale environmental and jet asymmetry properties of the combined sample, which includes new sources and previously discovered extended radio quasars (ERQs) from the literature. The results indicate that at least 13% of GRQs and 14% of NGERQs in the sample are located in galaxy groups and cluster environments. Similar lower-bound percentages reside near large-scale filamentary structures, with median projected distances of 5.9 and 4.3 Mpc from their respective host quasars. At the current survey noise levels, we find that the projected lengths of ERQs in our sample at z ≥ 1 are smaller than those at z &lt; 1. Furthermore, GRQs at z ≥ 1 exhibit greater arm-length asymmetry compared to NGERQs, which may be attributed to an asymmetric environment.

Keywords: Galaxy environments, Extragalactic radio sources, Radio loud quasars, Radio galaxies, Active galactic nuclei, Giant radio galaxies, Radio continuum emission, Radio astronomy, Radio sources
Gamma-Ray Burst Light-curve Reconstruction: A Comparative Machine and Deep Learning Analysis. Gamma-ray bursts (GRBs), observed at high-z, are probes of the evolution of the Universe and can be used as cosmological tools. Thus, we need correlations with small dispersion among key parameters. To reduce such a dispersion, we mitigate gaps in light curves (LCs), including the plateau region, key to building the two-dimensional Dainotti relation between the end time of plateau emission (Ta) and its luminosity (La). We reconstruct LCs using nine models: multilayer perceptron (MLP), Bi-Mamba, Fourier transform, Gaussian process-random forest hybrid, bidirectional long short-term memory, conditional generative adversarial networks, SARIMAX-based Kalman filter, Kolmogorov─Arnold networks, and Attention U-Net. These methods are compared to the Willingale model (W07) over a sample of 521 GRBs. MLP and Attention U-Net outperform other methods, with MLP reducing the plateau parameter uncertainties by 37.2% for  logTa , 38.0% for  logFa , and 41.2% for α (the post-plateau slope in the W07 model), achieving the lowest fivefold cross-validation mean squared error (MSE) of 0.0275. Attention U-Net achieved the lowest uncertainty of parameters, a 37.9% reduction in  logTa , a 38.5% reduction in  logFa , and a 41.4% reduction in α, but with a higher MSE of 0.134. Although Attention U-Net achieves the largest uncertainty reduction, the MLP attains the lowest test MSE while maintaining comparable uncertainty performance, making it the more reliable model. The other methods yield MSE values ranging from 0.0339 to 0.174. These improvements in parameter precision are needed to use GRBs as standard candles, investigate theoretical models, and predict GRB redshifts through machine learning.

Keywords: Gamma-ray bursts
Planets Across Space and Time (PAST). VIII. Kinematic Characterization and Identification of Radial Velocity Variables for the LAMOST─Gaia─TESS Stars. The Transiting Exoplanet Survey Satellite (TESS) has discovered over 6700 nearby exoplanet candidates using the transit method through its all-sky survey. Characterizing the kinematic properties and identifying variable stars for the TESS stellar sample is crucial for revealing the correlations between the properties of planetary systems and the properties of stars (e.g., Galactic components, age, chemistry, dynamics, and radiation). Based on data from TESS, Gaia DR3, and LAMOST DR10, we present a catalog of kinematic properties (i.e., Galactic positions, velocities, orbits, Galactic components, and kinematic age) as well as other basic stellar parameters for ∼660,000 TESS stars. Our analysis of the kinematic catalog reveals that stars belonging to different Galactic components (i.e., thin disk, thick disk, halo, and 12 streams in the disk) display distinctive kinematic and chemical properties. We also find that hot planets with periods less then 10 days in the TESS sample favor thin disk stars compared to thick disk stars, consistent with previous studies. Furthermore, using the LAMOST multiple-epoch observations, we identify 41,445 stars exhibiting significant radial velocity variations, among which 7846 are classified as binary stars. By fitting the radial velocity curves, we further derive orbital parameters (e.g., mass ratio, orbital period, and eccentricity) for 297 binaries. The catalogs constructed in this work have laid a solid foundation for future work on the formation and evolution of stellar and planetary systems in different Galactic environments.

Keywords: Binary stars, Stellar ages, Exoplanets, Stellar kinematics, Catalogs
Capturing Turbulence with Numerical Dissipation: A Simple Dynamical Model for Unresolved Turbulence in Hydrodynamic Simulations. Modeling unresolved turbulence in astrophysical gasdynamic simulations can improve the modeling of other subgrid processes dependent on the turbulent structure of gas: from flame propagation in the interiors of combusting white dwarfs to star formation and chemical reaction rates in the interstellar medium, and nonthermal pressure support of circum- and intergalactic gas. We present a simple method for modeling unresolved turbulence in hydrodynamic simulations via tracking its sourcing by local numerical dissipation and modeling its decay into heat. This method is physically justified by the generic property of turbulent flows that they dissipate kinetic energy at a rate set by the energy cascade rate from large scales, which is independent of fluid viscosity, regardless of its nature, be it physical or numerical. We calibrate and test our model against decaying supersonic turbulence simulations. Despite its simplicity, the model quantitatively reproduces multiple nontrivial features of the high-resolution turbulence run: the temporal evolution of the average small-scale turbulence, its dependence on spatial scale, and the slope and scatter of the local correlation between subgrid turbulent velocities, gas densities, and local compression rates. As an example of practical applications, we use our model in isolated galactic disk simulations to model locally variable star formation efficiency at the subresolution scale. In the supersonic, star-forming gas, the new model performs comparably to a more sophisticated model where the turbulent cascade is described by explicit subgrid terms. Our new model is straightforward to implement in many hydrodynamic codes used in galaxy simulations, as it utilizes already existing infrastructure to implicitly track the numerical dissipation in such codes.

Keywords: Hydrodynamical simulations, Galaxy formation, Star formation, Interstellar medium, Astrophysical fluid dynamics
Classification for 969 Double-mode RR Lyrae Stars from Zwicky Transient Facility. RR Lyrae (RRL) variable stars are cornerstone distance indicators. In particular, double-mode RR Lyrae (RRd) stars enable period─luminosity relations (PLRs) that are less sensitive to metallicity, reducing systematic biases in distance measurements. However, their utility has been limited by a global sample of only ∼3000 objects. We develop an automated RRd-screening pipeline and apply it to a crossmatched sample between the Gaia DR3 RRL catalog and Zwicky Transient Facility (ZTF) DR22 time-series photometry. The workflow combines Lomb─Scargle period searches, iterative prewhitening, period-ratio constraints that suppress ∼1 day sampling aliases, and amplitude-based quality cuts, enabling large-scale RRd star screening. We produce two ZTF-based catalogs: (i) 39,322 reliable single-mode RRL stars (40.5% of the crossmatched set) and (ii) 969 RRd stars. Among the RRd stars, 614 objects are newly identified, substantially enlarging this previously scarce sample; the catalog achieves an estimated completeness of 47.7%. The PLR derived from the newly discovered RRd stars agrees with the LMC-based relation, though with larger uncertainties. Incorporating these stars will help tighten the RRd PLR and improve distance measurements. Looking ahead, systematic RRd searches with upcoming surveys such as the Legacy Survey of Space and Time and the China Space Station Telescope should further extend high-accuracy distances across the Local Group and strengthen their cosmological applications.

Keywords: RRd variable stars, Periodic variable stars, Double-mode variable stars, RR Lyrae variable stars
Active Young Stars in the LAMOST─Kepler Survey. In the early stages of their lives, young stars harbor diverse processes exhibiting strong signatures, making them ideal targets for investigating stellar accretion, dynamo actions, and exoplanet formation. However, the current samples of active stars are highly limited in both number and parameter space, suffering from significant statistical uncertainties. By simultaneously measuring the activity proxy, the Balmer Hα 6563 Å line emission, and the youth indicator, the lithium 6708 Å line, with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectra, we have identified more than 1000 candidates of active young stars (aYSs) with Teff ≤ 7000 K and  logg≥3.5  in the Kepler prime field. Then we matched 660 stars with the Kepler light curves, and determined their periods and variable types. Based on these light curves, we are left with 78 dubious and 52 stable stars, and we have identified 22 eclipsing binaries, 3 heartbeat binaries, 1 transiting exoplanetary system candidate, 13 long-period variables, 61 pulsating stars, 18 irregular variables, 57 T Tauri stars, 173 flaring stars, and 435 rotational variables (the numbers are not exclusive). Supplementing the cluster-based samples, this sample has a broader parameter space coverage. This work will be beneficial for identifying aYSs in much larger datasets, such as the one produced by crossmatching between the LAMOST and Transiting Exoplanet Survey Satellite surveys, and the future survey conducted by the Chinese Space Station Survey Telescope.

Keywords: Zero-age main sequence stars, Pre-main sequence, Stellar accretion, Stellar activity
Influence of Magnetic Complexity of Active Regions on Solar Wind Properties during Solar Cycles 23 and 24. Linking the properties of solar wind to the activity and characteristics of its source regions can enhance our understanding of its origin and generation mechanisms. Using the Mount Wilson magnetic classification, we categorize all active regions (ARs) between 1999 and 2020 into three groups: α, β, and complex ARs. Subsequently, we classify the near-Earth AR solar wind into the corresponding three types based on the magnetic type of ARs. Our results show that α, β, and complex ARs account for 19.99%, 66.67%, and 13.34% of all ARs, respectively, while their corresponding AR solar wind proportions are 16.96%, 45.18%, and 37.86%. The properties of solar wind from different types of ARs vary significantly. As the magnetic complexity of ARs increases, the corresponding AR solar wind exhibits higher magnetic field strength, charge states, helium abundance (AHe), and first ionization potential bias. Our results demonstrate that complex ARs are more effective at generating solar wind. Additionally, the strong magnetic fields and frequent magnetic activity in complex ARs can heat the plasma to higher temperatures and effectively transport helium-rich material from the lower atmosphere to the upper corona.

Keywords: Solar cycle, Sunspots, Solar wind, Solar active regions, Solar activity
Robust Forecasting and Physical Interpretability of Geomagnetic Storms Using XGBoost and SHAP. Accurate forecasting of the disturbance storm time (Dst) index is critical for timely space weather alerts and for understanding solar wind─magnetosphere interactions. In this study, we develop a robust and interpretable Dst prediction model based on the XGBoost algorithm, optimized through Bayesian tuning and designed to handle missing data and class imbalance in continuous solar wind records. The resulting model predicts the Dst index 1 hr ahead with high accuracy (global mean absolute error (MAE) ≍ 2.21 nT, storm-time MAE ≍ 5.62 nT, R2 ≍ 0.96), significantly outperforming a persistence baseline. Leveraging Shapley Additive Explanations, we demonstrate the physical consistency of the model, showing how feature contributions dynamically shift across 34 storms of varying intensities. For moderate events (minimum Dst &gt; ─121 nT), forecasts are driven primarily by autoregressive Dst memory, supplemented by solar wind coupling indicators, southward interplanetary magnetic field trends, and solar wind velocity fluctuations. Conversely, for extreme storms (minimum Dst ≤ ─121 nT), cumulative energy injection and prolonged southward interplanetary magnetic field conditions become markedly more influential, reflecting intensified magnetospheric energy injection during severe geomagnetic events. These findings highlight the dynamic redistribution of driver relevance with storm intensity and demonstrate the model's capacity to capture physically meaningful relationships underlying geomagnetic variability.

Keywords: Time series analysis, Space weather, Nonlinear regression, Solar-terrestrial interactions, Magnetic storms
Self-attention-enhanced Deep Neural Networks for Simulating Post-Newtonian Dynamics of Three-body Systems. Simulating the long-term evolution of three-body systems remains a computational challenge due to the high cost of numerical integration, especially when incorporating post-Newtonian (PN) corrections. The first-order PN formulation introduces over 10 additional terms beyond the classical Newtonian equations, significantly increasing complexity. Although traditional neural networks have been used to approximate Newtonian dynamics, they struggle to capture PN effects, which are several orders of magnitude smaller. We propose a deep learning framework that combines a BERT-based encoder with an artificial neural network to model relativistic orbital dynamics. The motion is decomposed into two components—classical Newtonian and PN deviations—each learned independently and subsequently integrated to produce the final prediction. This architecture enables direct inference of positions and velocities at any target time from initial conditions, eliminating the need for stepwise acceleration-based integration. To ensure physical reliability, we introduce a relative energy error criterion derived from orbital energy conservation. During inference, predictions that exceed a predefined error threshold trigger local re-evaluation using smaller time steps. Applied to a hierarchical three-body system composed of a supermassive─intermediate-mass black hole binary and a star, the hybrid model achieves over 160× acceleration (100 s versus 5 hr) compared to full numerical integration when predicting the system's state 150 yr into the future, while maintaining relative energy errors below 1%. These results demonstrate the framework's potential for efficient and accurate simulation of relativistic multibody systems.

Keywords: Computational methods, Three-body problem, Black holes, General relativity
SIP-IFVM: An Observation-based Magnetohydrodynamic Model of a Coronal Mass Ejection. Currently, achieving a balance between computational efficiency, accuracy, and numerical stability in coronal mass ejection (CME) simulations, particularly in the sub-Alfvénic coronal region, remains a significant challenge. This paper aims to address the challenge by integrating observational data and developing advanced numerical algorithms, focusing on reproducing large-scale CME evolutions consistent with observations in the coronal region. Based on the recently developed fully implicit thermodynamic magnetohydrodynamic (MHD) coronal model, we further use an observation-based regularized Biot─Savart law flux rope to trigger a CME event during Carrington rotation 2111. Additionally, we improve the temporal accuracy using a second-order accurate explicit singly diagonally implicit Runge─Kutta method and improve its numerical stability by applying approximate linearization in the implicitly solved intermediate stages. Furthermore, we adjust the time-evolving magnetic field to zero at the end of each physical time step to further validate the extended magnetic field decomposition approach proposed by H. P. Wang et al. It is noticed that the model successfully reproduces the CME evolution consistent with white-light coronagraph observations, enables faster-than-real-time CME propagation simulations from the solar surface to 0.1 au using only a couple hundred CPU cores, and remains numerically stable in CME simulations involving low-β regions. The simulation results show that this novel MHD coronal model, combined with an observation-based magnetic flux rope, is sufficiently numerically stable and computationally efficient to reproduce real CME events propagating through the sub-Alfvénic coronal region. Thus, this approach is well suited for practical applications in daily space weather forecasting.

Keywords: Solar corona, Solar coronal mass ejections, Magnetohydrodynamical simulations
Optical Monitoring and Spectral Analysis of OJ 287. We present a comprehensive multiband optical monitoring and spectral analysis of the blazar OJ 287, conducted using the 1.26 m National Astronomical Observatory─Guangzhou University Infrared/Optical telescope (NGT). During an intensive 17 day observational campaign from 2022 December to 2023 January, we obtained 2716 high-quality photometric observations (929 in the g band, 887 in the r band, and 900 in the i band). The data reveal significant variability across all bands. Our main findings are as follows. (1) Significant magnitude variations were detected: ∆mg = 0.945 ± 0.048 mag (g band), ∆mr = 0.648 ± 0.023 mag (r band), and ∆mi = 0.945 ± 0.051 mag (i band). (2) Numerous intraday variability (IDV) events were identified, with characteristic parameters (∆m, ∆T, and  VR=∆m∆T ) showing consistent patterns between the g and r bands but distinct behavior in the i band. (3) Successful modeling of intraday light curves using a multi-Gaussian function, yielding brightening ( ∆Tb' ) and dimming ( ∆Td' ) timescales, and revealing an average peak separation of ∆Tc = 42.96 ± 0.99 minutes that appears to be frequency independent. (4) Development of a novel radiation framework suggesting that the observed IDV phenomena originate from multiple components—with the frequency-independent variations attributable to the central black hole, while frequency-dependent variations stem from jet and accretion disk processes.

Keywords: Blazars, CCD photometry, Active galaxies
Energy Flux Densities in Electron-only Magnetic Reconnection in Space Plasma. Electron-only magnetic reconnection, a novel form of magnetic reconnection recently discovered in plasma turbulence, exhibits distinct features from the well-studied standard magnetic reconnection with ion coupling. Our study investigates its energy partition features by utilizing in situ measurements from the Magnetospheric Multiscale mission. Electron enthalpy flux exhibits a strong linear relationship with electron velocity. The spatial distributions of electron kinetic energy and enthalpy fluxes are influenced by the asymmetric effects and guide fields in a similar manner to how the spatial distributions of electron velocity are affected. The guide field enhances Poynting flux to a magnitude that rivals, or even surpasses, electron enthalpy flux, while also deflects it toward the outflow direction. These findings impact the understanding of energy partition in magnetic reconnection.

Keywords: Space plasmas