Sazuna/UAT_keywords huggingface dataset:
Reconnection-driven Decaying Pulsations Modulated by Slow Magnetoacoustic Waves. Decaying pulsations have been simultaneously detected in the low-energy X-rays of solar/stellar flares, which are supposed to be associated with standing slow magnetoacoustic or kink-mode waves. The physical mechanism behind rapid decay remains unknown. We present the detection of quasiperiodic pulsations (QPPs) with rapid decay in high-energy emissions produced in two major flares on 2024 January 10 and May 14. Using empirical mode decomposition, decaying QPPs are identified in hard X-ray and microwave emissions during the flare-impulsive phase, suggesting a process of oscillatory magnetic reconnection. The quasi-periods and decay times are determined by a damped harmonic function, which are approximately 177 ± 8 s (249 ± 25 s) and 118 ± 4 s (124 ± 5 s), respectively. The restructured X-ray images reveal double footpoints connected by hot flare loops. Their phase speeds are estimated to be about 400 and 670 km s−1, both below the local sound speed in high-temperature plasmas, indicating the presence of slow-mode waves in hot flare loops. We perform coronal diagnostics based on standing slow-mode waves and derive key physical parameters, including the polytropic index, the thermal ratio, viscous ratio and radiation ratio, which are consistent with previous results. Our observations support the conclusion that decaying QPPs are triggered by oscillatory magnetic reconnection that is modulated by standing slow magnetoacoustic waves, with their rapid decay attributable to a coeffect of viscous damping and localized magnetic reconnection rate.

Keywords: Magnetohydrodynamics, Solar flares, Solar x-ray emission, Solar radio emission, Solar oscillations
Foreground Removal in Ground-based CMB Observations Using a Transformer Model. We present a novel method for cosmic microwave background (CMB) foreground removal based on deep learning techniques. This method employs a Transformer model, referred to as TCMB, which is specifically designed to effectively process HEALPix-format spherical sky maps. TCMB represents an innovative application in CMB data analysis, as it is an image-based technique that has rarely been utilized in this field. Using simulated data with noise levels representative of current ground-based CMB polarization observations, the TCMB method demonstrates robust performance in removing foreground contamination. The mean absolute variance for the reconstruction of the noisy CMB Q/U map is significantly less than the CMB polarization signal. To mitigate biases caused by instrumental noise, a cross-correlation approach using two half-mission maps was employed, successfully recovering CMB EE and BB power spectra that align closely with the true values, and these results validate the effectiveness of the TCMB method. Compared to the previously employed convolutional neural network (CNN)-based approach, the TCMB method offers two significant advantages: (1) It demonstrates superior effectiveness in reconstructing CMB polarization maps, outperforming CNN-based methods. (2) It can directly process HEALPix spherical sky maps without requiring rectangular region division, a step necessary for CNN-based approaches that often introduces uncertainties such as boundary effects. This study highlights the potential of Transformer-based models as a powerful tool for CMB data analysis, offering a substantial improvement over traditional CNN-based techniques.

Keywords: Convolutional neural networks, Observational cosmology, Cosmic background radiation
Physics-guided Deep Neural Network for Extreme Ultraviolet Solar Image Desaturation. EUV imagers on board satellites may experience saturation, resulting in impaired images. To correct this, deep learning has been employed to perform desaturation and eliminate saturation artifacts. It has been observed that deep learning methods have a superior advantage over traditional image restoration methods. However, previous deep learning models did not effectively utilize the physics-related principles of optical imaging, diffraction, and saturation. In this work, we propose a physics-guided deep learning model that incorporates the imaging and saturation principles of the Solar Dynamics Observatory Atmospheric Imaging Assembly into an optimization objective. The experimental results demonstrate the significant superiority of our proposed model over all previous models. Surprisingly, our model achieves excellent image desaturation with solely physics-related principles without customized deep-learning-specific optimization objectives. This result inspires us to solve a well-defined optimization problem that was previously solved by the regularization methods using deep learning. We do not need to reformulate the existing optimization problem to accommodate deep learning. Here, deep learning acts as an advanced solver for an optimization problem, which is exactly suitable for the scenario of artificial intelligence for science with physical laws embedded in neural networks to achieve both knowledge-inspired and data-driven goals.

Keywords: Solar flares, Solar extreme ultraviolet emission, Convolutional neural networks, Solar physics, Solar telescopes
A Large Sample of JWST/NIRSpec Brown Dwarfs: New Distant Discoveries. Brown dwarfs are essential probes of stellar and planetary formation, yet their low luminosities pose challenges for detection at large Galactic distances. The James Webb Space Telescope (JWST), with its unprecedented near-infrared sensitivity, enables the discovery and characterization of distant substellar objects, including those in the Milky Way's thick disk and halo. We conducted a systematic search using over 40,000 publicly available JWST/NIRSpec PRISM/CLEAR spectra and identified 68 brown dwarfs through spectral template matching and visual inspection. Among them, 12 are newly identified candidates, including eight T dwarfs and four M/L dwarfs, most at distances exceeding 1 kpc. Remarkably, two sources—JWST J001418.22−302223.2 and JWST J033240.07−274907.8—are found at distances greater than 5 kpc, making them the most distant brown dwarfs within the Milky Way. Spectral fits were performed using a nested sampling Monte Carlo algorithm with three model grids: Sonora Elf Owl, LOWZ, and SAND. The analysis reveals that cloud-free models are unable to reproduce L/T transition spectra, whereas the SAND model provides a more accurate representation of cloud effects in metal-poor environments. With the newly identified distant brown dwarfs, we also investigated the vertical metallicity gradient of brown dwarfs. Overall, the metallicities do not show an evident trend with Galactic height ∣Z∣, due to the limited sample size and the uncertainties in metallicity measurements.

Keywords: Brown dwarfs, L dwarfs, Milky Way stellar halo, Stellar atmospheres, T dwarfs
The JADES Origins Field: A New JWST Deep Field in the JADES Second NIRCam Data Release. We summarize the properties and initial data release of the JADES Origins Field (JOF), the longest single pointing yet imaged with the James Webb Space Telescope (JWST). This field falls within the GOODS-S region about 8' southwest of the Hubble Ultra Deep Field (HUDF), where it was formed initially in Cycle 1 as a parallel field of HUDF spectroscopic observations within the JWST Advanced Deep Extragalactic Survey (JADES). This imaging was greatly extended in Cycle 2 program 3215, which observed the JOF for 5 days in six medium-band filters, seeking robust candidates for z &gt; 15 galaxies. This program also includes ultradeep parallel NIRSpec spectroscopy (up to 91 hr on source, summing over the dispersion modes) on the HUDF. Cycle 3 observations from program 4540 added 20 hr of NIRCam slitless spectroscopy and F070W imaging to the JOF. With these three campaigns, the JOF was observed for 380 open-shutter hours with NIRCam using 15 imaging filters and two grism bandpasses. Further, parts of the JOF have deep 43 hr MIRI observations in F770W. Taken together, the JOF is one of the most compelling deep fields available with JWST and a powerful window into the early Universe. This paper presents the second data release from JADES, featuring the imaging and catalogs from the year 1 JOF observations.

Keywords: Extragalactic astronomy, Galaxy formation
Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond. In the era of the James Webb Space Telescope (JWST), with its unprecedented sensitivity and spectral resolution, infrared spectral surveys have revealed a rich inventory of ices, including complex organic molecules (COMs), in young stellar objects. However, robust methods to decompose and quantify these absorption features, particularly across broad spectral ranges, are still under investigation. We present the Ice-fitting with NNLS-based Decomposition and Retrieval Algorithm (INDRA), a fully Python-based tool that performs continuum and silicate removal, global ice fitting using weighted nonnegative least-squares (NNLS), and estimates column densities and statistical significance. We apply INDRA to NGC 1333 IRAS 2A, a target from the JWST Observations of Young protoStars (JOYS+) program previously studied using local fitting. We derive optical depths via polynomial continuum subtraction and remove silicate absorption using a synthetic model, isolating ice features for global MIRI fitting. Our results are consistent with previous local fits, confirming simple species and COMs, and expand the inventory by identifying additional absorption features from CO2 and NH 4+ . We also propose the presence of organic refractories contributing up to 9.6% in the spectral region of ∼5─8 μm among the various ice components, whose inclusion significantly improves the global spectral fitting. These broad absorption features, extending across ∼5.5─11 μm, are likely produced by large, complex molecules containing carbonyl (C=O), hydroxyl (O─H), amine (N─H), and C─H bending modes. Our expanded inventory, now incorporating these organic residues, offers new insights into the chemical evolution of ices in star-forming regions and highlights the importance of global spectral fitting in constraining ice compositions.

Keywords: Protostars, James Webb Space Telescope, Star formation, Astrochemistry
Properties of Flare Quasiperiodic Pulsations Based on a New TESS Flare Catalog. Stellar flares are important indicators of stellar magnetic activity and have been widely studied. Detailed studies of flares have raised new questions. For example, the quasiperiodic pulsation (QPP) phenomenon in flares challenges standard flare models, yet the underlying mechanism of this phenomenon remains poorly understood. We utilize the 2 minute cadence light-curve data from TESS Sectors 1─74 prior to 2024 January 30. By combining the previously published convolutional neural network─based machine learning flare identification method with traditional flare detection techniques, we have obtained a flare sample consisting of 208,280 flare events from 29,280 flare stars. In our flare events sample, flares with rise times within 10 minutes and decay times within 50 minutes account for more than 90% of the total number of flares. The proportion of flare stars is higher in binaries, the main sequence, and stars with KM spectral types compared to single stars, giants, and stars with spectral types other than KM. The fitted α index results for the flare frequency distributions across different evolutionary stages indicate a general trend of decreasing α index from main-sequence stars to giants. Except for M-type stars, the α index also gradually decreases from K-type to O-type stars. Using the flare QPP identification method, based on the fully convolutional networks published by previous researchers, we have also identified flare events with QPP, and through flare parameter constraints, we selected 10,465 flares with QPP features from M-type stars and qualitatively investigated their correlations with stellar parameters.

Keywords: Stellar flares, Stellar activity
1FLAT: A Firmamento-based Catalog of Active Galactic Nuclei in Fermi-LAT High-Galactic-latitude γ-Ray Sources. We present a systematic reassessment of 5062 high-Galactic-latitude γ-ray sources from the Fermi-Large Area Telescope (LAT) 4FGL-DR4 catalog using Firmamento, a web-based platform for multifrequency source discovery and analysis. Our goal is to provide an independent evaluation of LAT γ-ray source associations using alternative spectral and spatial methods that integrate both recent and legacy survey data. The evaluation is further refined through human supervision of spectral energy distributions, source morphology, flux variability, and template-based comparisons. Firmamento confirms the 4FGL-DR4 and 4LAC-DR3 counterparts or unassociated sources in 4493 cases (88.8%), demonstrating the robustness of both approaches. Beyond this general agreement, we identify 421 new blazar counterparts among previously unassociated sources, thereby reducing the fraction of unidentified extragalactic Fermi-LAT sources from 25% to 17%. In addition, in 64 cases, we find alternative blazar associations, while in 49 instances, we do not confirm the 4FGL-DR4 association. For all confirmed blazar counterparts, we provide homogeneous estimates of synchrotron peak frequency and peak flux using machine learning and template-based methods. The results agree with 4LAC-DR3 values in most cases, though significant discrepancies appear for a few dozen sources, often due to improved X-ray coverage. The primary outcome of this work is the First Firmamento LAT AGN Table, made publicly available through the Firmamento platform (https://firmamento.nyuad.nyu.edu), where all related multiwavelength data and images are available. The project involved extensive manual validation and benefited from the active participation of graduate and undergraduate students, highlighting the platform's value for both research and education.

Keywords: Astronomy web services, Celestial objects catalogs, Blazars
Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies. The Vera C. Rubin Observatory will conduct the Legacy Survey of Space and Time (LSST), promising to discover billions of galaxies out to redshift 7, using six photometric bands (ugrizy) spanning the near-ultraviolet to the near-infrared. The exact number of and quality of information about these galaxies will depend on survey depth in these six bands, which in turn depends on the LSST survey strategy, i.e., how often and how long to expose in each band. u-band depth is especially important for photometric redshift (photo-z) estimation and for detection of high-redshift Lyman-break galaxies (LBGs). In this paper, we use a simulated galaxy catalog and an analytic model for the LBG population to study how recent updates and proposed changes to Rubin's u-band throughput and LSST survey strategy impact photo-z accuracy and LBG detection. We find that proposed variations in u-band strategy have a small impact on photo-z accuracy for z &lt; 1.5 galaxies, but the outlier fraction, scatter, and bias for higher-redshift galaxies vary by up to 50%, depending on the survey strategy considered. The number of u-band dropout LBGs at z ∼ 3 is also highly sensitive to the u-band depth, varying by up to 500%, while the number of griz-band dropouts is only modestly affected. Under the new u-band strategy recommended by the Rubin Survey Cadence Optimization Committee, we predict u-band dropout number densities of 110 deg−2 (3200 deg−2) in year 1 (10) of LSST. We discuss the implications of these results for LSST cosmology.

Keywords: Lyman-break galaxies, Observational cosmology, High-redshift galaxies, Large-scale structure of the universe
Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology. Particle acceleration during magnetic reconnection is a key process in space physics and astrophysics, yet the direct role of induced electric fields in fully time-dependent three-dimensional (3D) topologies remains poorly quantified. In true 3D reconnection, incorporating full temporal evolution into analytical theory is exceptionally challenging, and in existing 3D simulations, the role of the time-varying induced electric field is not easily isolated, since it is inherently entangled with other contributions. Moreover, no systematic study has compared particle acceleration across the primary 3D topologies, non-null, spine, and fan, including A-type, B-type, and X-type null geometries, within a unified, time-dependent framework. Here, we develop the first analytical, time-dependent models for these configurations, with the background magnetic field decaying as B(t) ∝ exp(−kt), allowing the decay rate k to serve as an independent control parameter for temporal dynamics. By systematically comparing electron energy spectra, representative trajectories, and field distributions, we establish a clear hierarchy of acceleration efficiency among topologies and identify the physical mechanisms that govern these differences. We further reveal a quadratic scaling of mean energy gain with k, ∆W ∝ k2, a signature that emerges when the global induced electric field becomes the dominant driver of acceleration. Collectively, these findings reveal how magnetic geometry and the global field decay rate jointly control acceleration efficiency and its scaling, which might also provide a predictive physical basis for interpreting particle energization in extreme astrophysical events.

Keywords: Interplanetary particle acceleration, Solar magnetic reconnection
Probing the Low-radio-frequency Emission in PG Quasars with the uGMRT. II. We present results from uGMRT 685 MHz observations of 87 QSOs belonging to the Palomar─Green (PG) quasar sample with z &lt; 0.5. Radio emission is detected in all sources except for three radio-quiet (RQ) sources, namely PG 0043+039, PG 1121+422, and PG 1552+085. The radio-loud (RL)─RQ dichotomy persists at 685 MHz with only one source, PG 1216+069, changing its classification from RQ to RL. Approximately one-third of the detected RQ quasars display active galactic nucleus─dominated radio emission while the rest may show additional contributions from stellar-related processes. Consistent with this, the RL and RQ quasars occupy distinct tracks on the "fundamental plane" of black hole activity. We find that RL quasars have  log10(L685MHz/WHz−1)&gt;25.5 , while RQ quasars have  log10(L685MHz/WHz−1)&lt;23.5 . Furthermore, the radio sizes display the RQ−RL divide as well with RQ sources typically having sizes ≲30 kpc, with only 16 (∼22%) of RQ sources having sizes between 30 and 100 kpc, where there is an overlap with RL quasar sizes. A strong correlation exists between 685 MHz radio luminosity and black hole mass that is tightened when accretion rate is considered, highlighting the important role played by the accretion rate and accretion disk structure in jet production. We found no difference in the minimum-energy magnetic field strengths of the radio cores of RL and RQ quasars; however, different assumptions of source volume and volume-filling factors may apply. High-resolution X-ray observations and radio-X-ray flux comparisons are needed to independently test the "magnetic flux paradigm."

Keywords: Radio continuum emission, Radio interferometry, Radio loud quasars, Radio quiet quasars
A Comparison of Star Formation Rates by Different Tracers in Nearby Galaxies. We utilize a large sample of ∼113,000 galaxies (z &lt; 0.3) from the Sloan Digital Sky Survey with high-quality data to compare star formation rates (SFRs) across multiple diagnostic methods and examine their connection to the strength of active galactic nuclei (AGNs), indicated by Eddington ratio. Our sample encompassed star-forming, composite, Seyfert, and LINER galaxies. Our analysis utilizes various SFR indicators, including observed infrared flux (SFRFIR) from AKARI/Herschel (∼4100 sources), the MPA-JHU catalog ( SFRDn4000 ), the artificial neural network (ANN) catalog (SFRANN), the GSWLC catalog (SFRSED and SFRMIR), as well as [O II] and Hα emission lines (SFR[O II] and SFRHα). Within star-forming galaxies, SFR measurements from different tracers exhibited differences, with offsets and scatter below 0.26 and 0.29 dex, respectively. Moreover, non-star-forming galaxies (composite, Seyfert, and LINER) displayed discrepancies among SFR tracers, particularly for LINER galaxies, with offsets below 0.86 dex and a scatter of 0.57 dex. Additionally, our findings revealed robust correlations between SFRs and specific SFRs (sSFRs) with Eddington ratios. The Eddington ratio exhibited gradual transitions in the (s)SFRs─stellar mass diagrams. Galaxies with high Eddington ratios displayed high star formation activity, similar to blue star-forming galaxies. Furthermore, we observed decreasing sSFR trends from star-forming galaxies to composite, Seyfert, and LINER galaxies. Our results may provide insight into our understanding of (s)SFRs traced by different approaches and their connection to AGN activities.

Keywords: Active galaxies, Star formation
Refined M-type Star Catalog from LAMOST DR10: Measurements of Radial Velocities, T<SUB>eff</SUB>, log g, [M/H], and [α/M]. Precise stellar parameters for M-type stars, the Galaxy's most common stellar type, are crucial for numerous studies. In this work, we refined the LAMOST DR10 M-type star catalog through a two-stage process. First, we purified the catalog using techniques including deep learning and color─magnitude diagrams to remove 22,496 non-M spectra, corrected 2078 dwarf/giant classifications, and updated 12,900 radial velocities. This resulted in a cleaner catalog containing 870,518 M-type spectra (820,493 dwarfs, 50,025 giants). Second, applying a label transfer strategy using values from APOGEE DR16 for parameter prediction with a tenfold cross-validated convolutional neural network ensemble architecture, we predicted Teff,  logg , [M/H], and [α/M] separately for M dwarfs (dMs) and giants (gMs). The average internal errors for dMs/gMs are, respectively, Teff 30/17 K, log g 0.07/0.07 dex, [M/H] 0.07/0.05 dex, and [α/M] 0.02/0.02 dex. Comparison with APOGEE demonstrates external precisions of 34/14 K, 0.12/0.07 dex, 0.09/0.04 dex, and 0.03/0.02 dex for dMs/gMs, which represent precision improvements of over 20% for dMs and over 50% for gMs compared to previous literature results. The catalog is available at doi:10.12149/101668.

Keywords: Fundamental parameters of stars, Convolutional neural networks, Astronomy data analysis, M stars, Radial velocity, Catalogs