Sazuna/UAT_keywords huggingface dataset:
Uncovering Hidden Systematics in Extreme-precision Radial Velocity Measurements. We identify and correct for small but coherent instrumental drifts in 7 yr of radial velocity (RV) data from the EXtreme PREcision Spectrograph (EXPRES). The systematics are most notable for the six months before and after 2022 January, when EXPRES experienced larger temperature variations, and we see a systematic trough-to-peak amplitude of 2.8 m s−1 in the radial velocities. This is large enough to mimic or obscure planetary signatures. To isolate and correct these effects, we develop a suite of diagnostics that track two-dimensional échellogram shifts, scalings, and rotation, as well as line bisector spans derived from laser frequency comb lines. By combining these empirical tracers with instrument telemetry in a multidimensional regression, we reduce the EXPRES instrument trend traced with solar RVs from an rms of 1.32─0.43 m s−1, a 67% improvement, and the aggregate of 12 chromospherically quiet stars shows a 26% reduction in velocity scatter. Our injection/recovery simulations further demonstrate a doubling in sensitivity to low-amplitude planetary signals after correction. When applied to the stellar time series of ρ Coronae Borealis (ρCrB), the correction removes a spurious planet d signal, restoring the integrity of the data. These results highlight the need for long-term monitoring and multidimensional calibration diagnostics on the path toward true centimeter-per-second precision in next-generation extreme precision RV instruments.

Keywords: High resolution spectroscopy, Astronomy data analysis, Spectrometers, Astronomical instrumentation, Radial velocity
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Quasar Survey: Quasar Properties from Data Releases 10 to 12. We present the quasar catalog from Data Releases 10 to 12 of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Quasar Survey, comprising quasars observed between 2021 September and 2024 June. We robustly identified 11,346 quasars, of which 5386 are newly discovered objects not present in the Million Quasars catalog. This release brings the total number of quasars identified by the 12 yr LAMOST survey to 67,521, of which 29,513 are newly discovered. While the absolute flux calibration for LAMOST quasar spectra from Data Releases 6 to 9 was previously performed using the Sloan Digital Sky Survey (SDSS)/PanSTARRS1 multiband photometric data, the inherent variability of quasars can affect the flux accuracy. To address this limitation, we recalibrated the LAMOST spectra using (quasi-)simultaneous photometric data from Zwicky Transient Facility, which has conducted high-cadence sky monitoring since 2018 March. Based on the recalibrated single-epoch spectra, we estimated the emission-line fluxes, continuum fluxes, and virial black hole masses. These improved spectra facilitate direct comparison with the spectra of common quasars from SDSS, enabling searches for rare quasars, such as changing-look quasars exhibiting the appearance or disappearance of broad emission lines and broad absorption line quasars. The combined dataset of photometry and multiepoch spectra will enhance the detections of active galactic nucleus─related transients, such as Bowen fluorescence flares and extreme variability quasars, thereby improving our understanding of quasar variability.

Keywords: Surveys, Active galactic nuclei, Spectroscopy, Quasars
Spectuner-D1: Spectral Line Fitting of Interstellar Molecules Using Deep Reinforcement Learning. Spectral lines from interstellar molecules provide crucial insights into the physical and chemical conditions of the interstellar medium. Traditional spectral line analysis relies heavily on manual intervention, which becomes impractical when handling the massive datasets produced by modern facilities such as the Atacama Large Millimeter/submillimeter Array (ALMA). To address this challenge, we introduce a novel deep reinforcement learning framework to automate spectral line fitting. Using observational data from ALMA, we train a neural network that maps both molecular spectroscopic data and observed spectra to physical parameters such as excitation temperature and column density. The neural network predictions can serve as initial estimates and be further refined using a local optimizer. Our method achieves fitting results consistent with global optimization with multiple runs, while reducing the number of forward modeling runs by an order of magnitude. We apply our method to pixel-level fitting for an observation of the G327.3-0.6 hot core and validate our results using XCLASS. We perform the fitting for typical complex organic molecules of hot cores, including CH3OH, CH3OCHO, CH3OCH3, C2H5CN, and C2H3CN. For a region of 100 × 100 pixels covering 5 GHz bandwidth, the fitting process requires 4.9─41.9 minutes using a desktop with 16 cores and one consumer-grade GPU card.

Keywords: Astrochemistry, Star formation, Interstellar medium, Neural networks
Millimeter-wave and Far-infrared Spectroscopic Characterization of Torsionally Excited Ethylene Glycol. Ethylene glycol has been detected in various astronomical sources, with rotational excitation temperatures ranging from ∼8 to 300 K. The higher end of this range approaches the energies of this molecule's lowest torsionally excited states, suggesting significant population of them in warmer interstellar molecular clouds. This study examines these torsionally excited states through high-resolution millimeter-wave (75─110 GHz and 140─220 GHz) and synchrotron-based far-infrared (50─560 cm−1 (1.5─16.8 THz)) spectroscopy. We observed a dense array of well-resolved rovibrational bands in the far-infrared, involving the two lowest energy conformers, labelled G1 and G2. Ten of the bands were assigned to C─C torsional (ν24) and C─O torsional (ν23 and ν21) transitions that involve a change in the tunneling state (A1↔A2), and two were assigned to the CCO bending (ν20) fundamental (one each for G1 and G2), which do not involve tunneling-state changes. Particular attention is given to the ν23 fundamental, for which we performed a detailed analysis of its lower tunneling subband, νgs(G1,A2) → ν23(G2,A1), which is conveniently well isolated from other features. A combined fit incorporating 1866 far-infrared lines from this subband in addition to 227 submillimeter-wave lines from torsionally excited ethylene glycol was performed, providing an extensive set of spectroscopic constants for the ν23(G2,A1) state. These constants allow for reliable predictions of pure rotational transitions within this excited torsional state to be made, many of which will likely appear in astronomical surveys given the high sensitivity of modern radio telescopes.

Keywords: Molecular physics, Molecular spectroscopy, Interstellar medium
Measuring the Coronal Magnetic Field with 2D Coronal Seismology: A Forward-modeling Validation. In recent years, a two-dimensional (2D) coronal seismology technique applied to spectral-imaging data from the Coronal Multi-channel Polarimeter (CoMP) and Upgraded Coronal Multi-channel Polarimeter (UCoMP) has enabled routine measurement of the global coronal magnetic field. The technique combines coronal transverse wave phase speed from Doppler measurements with electron densities from the Fe XIII 10798/10747 Å intensity ratio to infer the magnetic field strength, while the wave propagation directions from Doppler measurements trace the magnetic field direction. To validate the accuracy and robustness of this method, we use forward modeling of a MURaM simulation that produces open and closed magnetic structures with excited waves. From the synthetic Doppler velocity, Fe XIII infrared line intensities, and linear polarization signals, we apply the 2D coronal seismology technique to estimate the magnetic field strength and direction. A comparison with the simulation ground truth shows close agreement, indicating that the technique can recover the line-of-sight (LOS) emissivity-weighted magnetic field direction and strength with high accuracy. We also perform a parameter-space analysis to quantify the sensitivities of the method to parameter choice. These findings provide practical guidance for CoMP/UCoMP-like analysis and demonstrate that 2D coronal seismology can deliver reliable, LOS emissivity-weighted measurements of the coronal magnetic field from coronal wave observations.

Keywords: Solar coronal seismology, Solar coronal waves, Solar magnetic fields
Asteroseismically Inferred Ages of 132,000 Red Giants with TESS. NASA's Transiting Exoplanet Survey Satellite mission has identified at least 158,000 oscillating red giants, increasing the known sample by roughly an order of magnitude. After validating that these measurements are reliable to 5% for up to 90% of red giants, we make custom stellar evolution models using Modules for Experiments in Stellar Astrophysics in order to estimate ages for ∼132,794 of these stars to an average uncertainty of 23%. We show that these ages follow similar distributions to those observed in other samples such as Kepler, with small differences likely resulting in the Galactic volume probed. We provide these ages to the community to enable future Galactic archeology analyses.

Keywords: Astronomy data modeling, Stellar ages, Stellar evolutionary models, Red giant stars, Stellar evolution
ExoClock Project. IV. A Homogeneous Catalog of 620 Updated Exoplanet Ephemerides. The ExoClock project is an open platform aiming to monitor exoplanets by integrating observations from space- and ground-based telescopes. This study presents an updated catalog of 620 exoplanet ephemerides, integrating 30,000 measurements from ground-based telescopes (the ExoClock network), literature, and space telescopes (Kepler, K2 and TESS). The updated catalog includes 277 planets from TESS which require special observing strategies due to their shallow transits or bright host stars. This study demonstrates that data from larger telescopes, and the employment of new methodologies such as synchronous observations with small telescopes, are capable of monitoring special cases of planets. The new ephemerides show that 45% of the planets required an update while the results show an improvement of 1 order of magnitude in prediction uncertainty. The collective analysis also enabled the identification of new planets showing transit-timing variations, highlighting the importance of extensive observing coverage. Developed in the context of the ESA's Ariel space mission, with the goal of delivering a catalog with reliable ephemerides to increase the mission efficiency, ExoClock's scope and service have grown well beyond the remit of Ariel. The ExoClock project has been operating in the framework of open science, and all tools and products are accessible to everyone within academia and beyond, to support efficient scheduling of future exoplanet observations, especially from larger telescopes where the pressure for time allocation efficiency is higher (Ariel, JWST, VLT, ELT, Subaru etc.). The inclusion of diverse audiences in the process and the collaborative mode not only foster democratization of science but also enhance the quality of the results.

Keywords: Transit photometry, Open source software, Amateur astronomers, Exoplanet catalogs
Overview of the JWST Advanced Deep Extragalactic Survey (JADES). We present an overview of the James Webb Space Telescope (JWST) Advanced Deep Extragalactic Survey (JADES), an ambitious program of infrared imaging and spectroscopy in the GOODS-S and GOODS-N deep fields, designed to study galaxy evolution from high redshift to cosmic noon. JADES uses about 770 hr of Cycle 1 guaranteed time largely from the Near-Infrared Camera (NIRCam) and Near-Infrared Spectrograph (NIRSpec) instrument teams. In GOODS-S, in and around the Hubble Ultra Deep Field and Chandra Deep Field South, JADES produces a deep imaging region of ∼42 arcmin2 with over 100 hr of exposure time spread over nine NIRCam filters, including two medium-band filters. This is extended at medium depth in GOODS-S and GOODS-N with NIRCam imaging of ∼167 arcmin2, averaging 25 hr of exposure over 8─10 filters. In both fields, we conduct extensive NIRSpec multiobject spectroscopy, including two deep pointings of 55 hr exposure time, 14 medium pointings of ∼12 hr, and 15 shallower pointings of ∼4 hr, targeting over 5000 Hubble Space Telescope─ and JWST-detected faint sources with five low-, medium-, and high-resolution dispersers covering 0.6─5.3 μm. Finally, JADES extends redward via coordinated parallels with the JWST Mid-Infrared Instrument, featuring ∼10 arcmin2 with 43 hr of exposure at 7.7 μm and thrice that area with 1.4─6.8 hr of exposure at 12.8 and 15 μm. For nearly 30 yr, the GOODS-S and GOODS-N fields have been developed as the premier deep fields on the sky; JADES is now providing a compelling start on JWST's legacy in these fields.

Keywords: Lyman-break galaxies, Sky surveys, Galaxy evolution
A Machine Learning Approach for Identifying Coronal Mass Ejection─associated Stellar Flares in TESS Observations. Coronal mass ejections (CMEs) are major drivers of stellar space weather and can strongly influence the habitability of exoplanets. However, compared to the frequent occurrence of white-light flares, confirmed stellar CMEs remain extremely rare. Whether such flares are commonly accompanied by CMEs is a key question for solar-stellar comparative studies. Using Sun-as-a-star soft X-ray flare light curves observed by the Geostationary Operational Environmental Satellites (GOES) X-ray Sensor (XRS) 1─8 Å channel, we compiled a sample of 1766 M-class and larger solar flares and extracted features with both deep convolutional neural networks and manual methods. Five machine learning classifiers were trained to distinguish eruptive from confined flares, with the random forest (RF) model achieving the best performance (true skill statistic; TSS = 0.31). This TSS value indicates that the model possesses a moderate ability to discriminate between eruptive and confined flares. Normalized white-light and GOES XRS flare light curves show broadly consistent temporal evolution, reflecting their shared energy-release history and supporting a probabilistic transfer of the model to white-light flare data. We applied the best-performing RF model to 41,405 Transiting Exoplanet Survey Satellite─detected flares on FGKM-type main-sequence stars, predicting that approximately 47% of events show CME-like morphological characteristics, with the model-implied intrinsic association fraction lying in the range 35%─60%. Intriguingly, the CME occurrence rate decreases with increasing flare energy, indicating that the most energetic flares may be more strongly confined by overlying magnetic fields. These results provide new insight into flare─CME connections in diverse stellar environments and have important implications for assessing the impact of stellar eruptive activity on exoplanetary atmospheres.

Keywords: Solar flares, Solar coronal mass ejections, Stellar flares, Stellar coronal mass ejections, Random Forests
Gamma-Ray Millisecond Pulsars: Off-pulse Emission Characteristics, Phase-resolved Pseudoluminosity─Cutoff Energy Correlation, and High-energy Pulsed Emission. We investigate the γ-ray emission from 38 millisecond pulsars using 15 years of Fermi-LAT Pass 8 data in the 0.3─500 GeV range. Off-pulse intervals defined objectively with the Bayesian blocks algorithm reveal significant off-pulse emission from 15 sources. Ten exhibit clear spectral cutoffs indicative of magnetospheric origin, while the remaining five show no compelling evidence for nonmagnetospheric origins, as their off-pulse emission is spatially unresolved and inconsistent with hadronic, inverse Compton, or intrabinary contributions, implying a likely magnetospheric origin. We perform phase-resolved spectral fits for these 15 sources. In 11 of them, the cutoff energy Ecut varies markedly with rotation phase and correlates positively with the phase-resolved photon counts. Defining a phase-resolved pseudoluminosity, these 11 pulsars follow a linear relation between  log10L  and  log10Ecut , with slope  α=2.31−0.25+0.22 , consistent with curvature radiation predictions from the equatorial current sheet (α ≍ 2.29). The same relation appears in the bright pulsar J0614−3329, implying the existence of the same emission mechanism across all rotational phases. We detect pulsed emission above 10 GeV from 19 sources, and a significant fraction of these also exhibit robust off-pulse emission. The coexistence of robust off-pulse flux and pulsed emission extending to high energies challenges standard outer gap models. While other frameworks can also produce off-pulse flux, the phase-resolved L─Ecut correlation could provide a key diagnostic, and our measured slope may provide new evidence supporting the equatorial current sheet scenario as an important γ-ray emission mechanism in millisecond pulsars.

Keywords: Gamma-ray sources, High energy astrophysics, Millisecond pulsars
HyperAIRI: A Plug-and-play Algorithm for Precise Hyperspectral Image Reconstruction in Radio Interferometry. The next-generation radio-interferometric (RI) telescopes require imaging algorithms capable of forming high-resolution, high-dynamic-range images from large data volumes spanning wide frequency bands. Recently, AIRI, a plug-and-play approach utilizing the forward─backward (FB) algorithmic structure, has demonstrated state-of-the-art performance in monochromatic RI imaging by alternating a data fidelity step with a regularization step via learned denoisers. In this work, we introduce HyperAIRI, its hyperspectral extension, underpinned by learned hyperspectral denoisers enforcing a power-law spectral model. For each spectral channel, the HyperAIRI denoiser takes as input its current image estimate, alongside estimates of its two immediate neighboring channels and the spectral index map, and provides as output its associated denoised image. To ensure convergence of HyperAIRI, the denoisers are trained with a Jacobian regularization enforcing nonexpansiveness. To accommodate varying dynamic ranges, we assemble a shelf of pretrained denoisers, each tailored to a specific dynamic range. At each HyperAIRI iteration, the spectral channels of the target image cube are updated in parallel using dynamic-range-matched denoisers from the pretrained shelf. The denoisers are also endowed with a spatial image faceting functionality, enabling scalability to varied image sizes. Additionally, we formally introduce Hyper-uSARA, a variant of the optimization-based algorithm HyperSARA, promoting joint sparsity across spectral channels via the ℓ 2,1 norm, also adopting FB. We evaluate HyperAIRI's performance on simulated and real observations. We showcase its superior performance compared to its optimization-based counterpart Hyper-uSARA, CLEAN's hyperspectral variant in WSClean, and the monochromatic imaging algorithms AIRI and uSARA. HyperAIRI's MATLAB implementation is available in the BASPLib (https://basp-group.github.io/BASPLib/) code library.

Keywords: Computational methods, Radio interferometry, Astronomy image processing, Neural networks
Bayesian Model Comparison and Significance: Widespread Errors and How to Correct Them. Bayes factors have become a popular tool in exoplanet spectroscopy for testing atmosphere models against one another. We show that the commonly used method for converting these values into significance "sigmas" is invalid. The formula is neither justified nor recommended by its original paper, and overestimates the confidence of results. We use simple examples to demonstrate the invalidity and prior sensitivity of this approach. We review the standard Bayesian interpretation of the Bayes factor as an odds ratio and recommend its use in conjunction with the Akaike information criterion or Bayesian predictive information criterion simplified in future analyses (Python implementations are included). As a concrete example, we refit the WASP-39 b NIRSpec transmission spectrum to test for the presence of SO2. The prevalent, incorrect significance calculation gives 3.67σ, whereas the standard Bayesian interpretation yields a null model probability  p(B∣y)=0.0044 . Surveying the exoplanet atmosphere literature, we find widespread use of the erroneous formula. In order to avoid overstating observational results and estimating observation times too low, the community should return to the standard Bayesian interpretation.

Keywords: Bayesian statistics, Exoplanets, Akaike information criterion, Model selection, Hot Jupiters, Nested sampling, Astrostatistics, Transmission spectroscopy, Bayes factor, Markov chain Monte Carlo, Bayesian information criterion
A Catalog of 971 FR I Radio Galaxies from the FIRST Survey via Hybrid Deep Learning and Ridgeline Flux Density Distribution Analysis. We present a catalog of 971 FR I radio galaxies (FR Is) identified from the Very Large Array Faint Images of the Radio Sky at Twenty centimeters (FIRST) survey. The identifications were made using a hybrid method that combines deep learning with ridgeline flux density distribution analysis. Among these sources, 845 are new discoveries. The catalog comprises sources characterized by edge-darkened double jets, an absence of significant bent morphology, and angular sizes ranging from 23″ to 159″. Optical and/or infrared counterparts have been identified for 813 FR Is. Among these, the host galaxies are predominantly (88.1%) red galaxies, with the remainder (11.9%) being blue galaxies; notably, most blue galaxies exhibit high radio power. The FR I sample spans a radio power range of 1.20 × 1021 ≤ P1400 ≤ 3.55 × 1027 W Hz−1 at 1400 MHz and reaches redshifts up to z = 2.307. The host galaxies have r-band absolute magnitudes in the range of −24 ≲ Mr ≲ −20 mag. For the 512 FR Is with estimates, the black hole masses fall within 107 ≲ MBH ≲ 7.94 × 109 M⊙. Based on optical emission-line ratios and mid-infrared colors, spectroscopic classification shows that 571 hosts are low-excitation radio galaxies and 59 are high-excitation radio galaxies.

Keywords: Extragalactic radio sources, Active galactic nuclei, Radio galaxies, Radio astronomy
Searching for Solar-like Oscillations Using TESS 2 minute Cadence in the Southern Ecliptic Hemisphere. The TESS space mission has generated an extensive collection of light curves, providing a valuable opportunity to search for solar-like oscillations. Numerous studies have utilized TESS observations to search for solar-like oscillations and achieved excellent results. However, the number of oscillators found by the previous works may be incomplete and significantly below the predicted count. Therefore, we employed a novel method to search for solar-like oscillations. In this work, we utilized TESS 2 minute cadence data to identify solar-like oscillators in the southern ecliptic hemisphere, detecting the presence of oscillations by identifying an excess power hump in the spectrum and combining visual inspection. As a result, we identified 10,548 stars exhibiting solar-like oscillations including 2972 that had not been reported in previous studies. The νmax and ∆ν of oscillators were determined using the fitting and autocorrelation, and the reliability of the ∆ν measurements was further evaluated using the Fourier spectrum of the autocorrelation function. Based on this assessment, 4775 oscillators were classified as having reliable ∆ν, including 1920 that have ∆ν measured for the first time.

Keywords: Light curves, Asteroseismology, Red giant stars