Sazuna/UAT_keywords huggingface dataset:
Research on Instance Segmentation of Sunspot Groups Based on ConvNeXt-V2. Classification and segmentation of sunspot groups are valuable for analyzing the evolution of sunspot magnetic fields, which is closely associated with solar flare eruptions. This study presents a deep learning-based method tailored for the Mount Wilson magnetic classification and segmentation of sunspot groups. Utilizing data from the Helioseismic and Magnetic Imager collected from 2010 June to 2024 April, we created a labeled data set of 3916 composite images. The data set was split into training and testing sets in a 4:1 ratio to facilitate practical model training and evaluation. The study applies the ConvNeXt-V2 model, which integrating a Fully Convolutional Masked Autoencoder and a Global Response Normalization layer to enhance feature extraction capabilities and computational efficiency. The model achieves significant parameter reduction by leveraging the inverted residual bottleneck structure and depthwise separable convolutions. During training, a combination of Stochastic Gradient Descent and AdamW optimizers improves model accuracy and generalization ability. The model demonstrates strong performance in classification and segmentation tasks, attaining a mean AP@0.5 of 0.90 in classification and 0.88 in segmentation. Mean Precision exceeds 0.9, with mean Recall and F1-Score nearing 0.9 in classification task. Confusion matrix analysis reveals minor confusions between similar categories. Additionally, confidence heatmap analysis shows that smaller sunspots display lower segmentation confidence scores, highlighting challenges in small-target segmentation.

Keywords: Solar activity, Sunspot groups
Comprehensive Tolerance Analysis and Improvement Strategies for the Final 6.5 m Wide-field MUltiplexed Survey Telescope. To fulfill the urgent requirement for large-scale spectroscopic survey telescopes with wide field of view in modern astronomy, the 6.5 m MUltiplexed Survey Telescope (MUST) has been presented by Tsinghua University and the final optical design consisting of a Ritchey─Chretien system and a 1.6 m five-element wide-field corrector has been determined after abundant iterations and communications with vendors. This optical system guarantees excellent performance with the 80% enclosed energy diameter not greater than 0 524 within 2 8 field of view over 55° zenith angle. However, there will be various errors in fabrication and assembly and more dynamic errors induced by environmental temperature and gravity during sky survey, all causing unexpected performance deterioration. To get rid of those errors, the corresponding improvement strategies are proposed and verified. The aberrations caused by fabrication and assembly errors can be optimized by adjusting the position of the secondary mirror and adding spacers between optical components, while the thermal-induced and gravity-induced errors can be compensated by dynamically adjusting the position of the secondary mirror and modifying the surface figure of the primary mirror during tracking. The improvement strategies showing satisfactory results are significant and referenceable for the subsequent construction of MUST.

Keywords: Astronomical instrumentation, Telescopes
Review and Prospects of Hot Exozodiacal Dust Research For Future Exo-Earth Direct Imaging Missions. Hot exozodiacal dust is dust in the innermost regions of planetary systems, at temperatures around 1000 K─2000 K, and commonly detected by near-infrared interferometry. The phenomenon is poorly understood and has received renewed attention as a potential risk to a planned future space mission to image potentially habitable exoplanets and characterize their atmospheres (exo-Earth imaging) such as the Habitable Worlds Observatory (HWO). In this article, we review the current understanding of hot exozodiacal dust and its implications for HWO. We argue that the observational evidence suggests that the phenomenon is most likely real and indeed caused by hot dust, although conclusive proof in particular of the latter statement is still missing. Furthermore, we find that there exists as of yet no single model that is able to successfully explain the presence of the dust. We find that it is plausible and not unlikely that large amounts of hot exozodiacal dust in a system will critically limit the sensitivity of exo-Earth imaging observations around that star. It is thus crucial to better understood the phenomenon in order to be able to evaluate the actual impact on such a mission, and current and near-future observational opportunities for acquiring the required data exist. At the same time, hot exozodiacal dust (and warm exozodiacal dust closer to a system's habitable zone) has the potential to provide important context for HWO observations of rocky, HZ planets, constraining the environment in which these planets exist and hence to determine why a detected planet may be capable to sustain life or not.

Keywords: Exoplanet systems, Infrared astronomy, Circumstellar matter, Main sequence stars, Interferometry
Deep Learning-based Detection and Segmentation of Edge-on and Highly Inclined Galaxies. Edge-on galaxies have many important applications in galactic astrophysics, but they can be difficult to identify in vast amounts of astronomical data. To facilitate the search for them, we developed a deep learning algorithm designed to identify and extract edge-on galaxies from astronomical images. We utilized a sample of edge-on spiral galaxies from the Galaxy Zoo database, retrieving the corresponding images from the Sloan Digital Sky Survey (SDSS). Our data set comprised ∼16,000 galaxies, which we used to train the YOLOv5 algorithm for detection purposes. To isolate galaxies from their backgrounds, we trained the SCSS-Net neural network to generate segmentation masks. As a result, our algorithm detected ∼12,000 edge-on galaxies with a high confidence, for which we compiled a catalog including their parameters obtained from the SDSS database. We described basic properties of our sample, finding that most galaxies have redshifts 0.02 &lt; z &lt; 0.10, have low values of b/a and are mostly red, which is expected from edge-on galaxies and is consistent with our training sample, as well as other literature. The cutouts of the detected galaxies can be used for future studies and the algorithm can be applied to data from future surveys as well.

Keywords: Disk galaxies, Spiral galaxies, Astronomy data analysis, Galaxies
The Effect of Vera C. Rubin Observatory Cadence Selections on Kilonova Detectability. The discovery of the optical/infra-red counterpart (AT2017gfo) to the binary neutron star gravitational-wave detection (GW170817), which was followed by a short gamma-ray burst (GRB 170817), marked a groundbreaking moment in multi-messenger astronomy. To date, it remains the only confirmed joint detection of its kind. However, many experiments are actively searching for similar fast-fading electromagnetic counterparts, known as kilonovae. Fortunately, the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) provides excellent prospects for identifying kilonova candidates either from, or independent of, gravitational-wave and GRB triggers. Cadence choices for LSST surveys are especially important for maximising the likelihood of kilonovae detections. In this work, we explore the possibility of optimizing Rubin Observatory's ability to detect kilonovae by implementing a fast transient metric shown to be successful with an existing wide field survey, e.g., the Zwicky Transient Facility. We study existing LSST cadences, how detection rates are affected by filter selections, the return timescales for visits of the same area in the sky, and other relevant factors. Through our analysis, we have found that employing baseline cadences and utilizing triplet families like presto_gap produced the highest likelihood of kilonova detection.

Keywords: Neutron stars, Relativistic binary stars, R-process, Compact binary stars, Transient sources, Gravitational wave sources, Hubble constant, Gravitational wave astronomy, Ground-based astronomy, Optical observatories
Enabling High Mass Accretion Rates Onto Massive Main Sequence Stars by Outer Envelope Mass Removal. Using the one-dimensional numerical code Modules for Experiments in Stellar Astrophysics, we simulate mass accretion at very high rates onto massive main sequence stars, MZAMS = 30, 60, 80M⊙, and find that these stars can accrete up to ≃10% of their mass without expanding much if we consider a simultaneous mass removal by jets. In this jetted-mass-removal accretion scenario, the accretion is through an accretion disk that launches jets. When the star expands due to rapid mass accretion, it engulfs the inner zones of the accretion disk and the jets it launches. We assume that these jets remove the outer layers of the envelope. We mimic this in the one-dimensional numerical code by alternating mass addition and mass removal parts. We add mass and energy, the accretion energy, to the outer layers of the envelope, leading to rapid stellar expansion. When the star expands by a few tens of percent, we stop mass addition and start mass removal until the star returns to its initial radius. We also show that the density of the accretion disk is larger than the density of the outer layers of the inflated envelope, allowing the disk to launch jets inside the outer inflated envelope layers. Our results show that main sequence stars can accrete mass at high rates while maintaining the deep potential well, as some models of eruptive systems require, e.g., some luminous red novae, the grazing envelope evolution, and the 1837–1856 Great Eruption of Eta Carinae.

Keywords: Massive stars, Stellar jets, Common envelope evolution, Stellar mass loss
The Effects of Magneto-convection on Short Period Cataclysmic Variables. Many of the current problems related to the evolution of Cataclysmic variables (CVs) revolve around the magnetic nature of the main sequence secondary. It is known that magnetic fields alter the structure of low mass stars. In particular, they inhibit convection, leading to inflated radii. Here we present a simple model to demonstrate the impact of magneto-convection (MC) on the evolution of short period CVs. We find that the inclusion of MC leads to larger secondaries, longer orbital periods and smaller mass-loss rates. When including magnetic effects, the minimum orbital period is increased by 14 minutes, indicating that this could help alleviate the period minimum problem in CV evolution. We also examine the effect of the white dwarf (WD) mass on the minimum period. While increasing the WD mass does increase the minimum period, it is not substantial. Therefore it is unlikely that the period minimum problem can be solved with a larger WD mass or with mass growth of WD.

Keywords: Close binary stars, Cataclysmic variable stars, Magnetic stars, Stellar evolution
Mixed Origins: Strong Natal Kicks for Some Black Holes and None for Others. Using stellar kinematic data from Gaia DR3, we revisit constraints on black hole (BH) natal kicks from observed accreting and detached BH binaries. We compare the space velocities and Galactic orbits of a sample of 12 BHs in the Galactic disk with well-constrained distances to their local stellar populations, for which we obtain proper motions and radial velocities from Gaia DR3. Compared to most previous studies, we infer lower minimum kick velocities, because our modeling accounts for the fact that most BH binaries are old and have likely been kinematically heated by processes other than kicks. Nevertheless, we find that half of the BHs have at least weak evidence for a kick, being kinematically hotter than at least 68% of their local stellar populations. At least 4 BHs are kinematically hotter than 90% of their local stellar populations, suggesting they were born with kicks of ≳100 km s‑1. On the other hand, 6 BHs have kinematics typical of their local populations, disfavoring kicks of ≳50 km s‑1. For two BHs, V404 Cyg and VFTS 243, there is strong independent evidence for a very weak kick ≲10 km s‑1. Our analysis implies that while some BHs must form with very weak kicks, it would be wrong to conclude that most BHs do, particularly given that selection biases favor weak kicks. Although the uncertainties on most individual BHs' kicks are still too large to assess whether the kick distribution is bimodal, the data are consistent with a scenario where some BHs form by direct collapse and receive weak kicks, and others form in supernovae and receive strong kicks.

Keywords: Stellar kinematics, X-ray binary stars, Black holes
The Ambiguous Age and Tidal History for the Ultra-hot Jupiter TOI-1937Ab. Ultra-short-period (USP) planets are a rare but dynamically significant subset of the exoplanet sample, and understanding their dynamical histories and migration processes is necessary to build a complete picture of the outcomes of planet formation. In this work, we present an analysis of system age constraints and the impact of tidal evolution in the TOI-1937A system, a component of a large-separation stellar binary with an ambiguous age constraint that hosts a massive (&gt;2 MJup) USP planetary companion. Through a suite of tidal evolution simulations and analysis of the transit timing variations present in the photometric data, we find that the ultra-hot Jupiter TOI-1937Ab is likely undergoing orbital decay driven by tidal interactions, and we place an observational upper limit on its decay rate of   s yr‑1. We consider three different hypotheses for the system age based on three distinct methods of age estimation. These three age limits are complemented by indirect evidence of the age of the star that comes from our dynamical and transit timing analyses. We discuss the possibility that future data will provide more concrete constraints on the tidal parameters of TOI-1937Ab and its host star.

Keywords: Exoplanet dynamics, Exoplanet evolution, Stellar ages
Enhancing Peer Review in Astronomy: A Machine Learning and Optimization Approach to Reviewer Assignments for ALMA. The increasing volume of papers and proposals that undergo peer review emphasizes the pressing need for greater automation to effectively manage the growing scale. In this study, we present the deployment and evaluation of machine learning and optimization techniques to assign proposals to reviewers that were developed for the Atacama Large Millimeter/submillimeter Array (ALMA) during the Cycle 10 Call for Proposals issued in 2023. Using topic modeling algorithms, we identify the proposal topics and assess reviewers' expertise based on their previous ALMA proposal submissions. We then apply an adapted version of the assignment optimization algorithm from PeerReview4All to maximize the alignment between proposal topics and reviewer expertise. Our evaluation shows a significant improvement in matching reviewer expertise: the median similarity score between the proposal topic and reviewer expertise increased by 51 percentage points compared to the previous cycle, and the percentage of reviewers reporting expertise in their assigned proposals rose by 20 percentage points. Furthermore, the assignment process proved highly effective in that no proposals required reassignment due to significant mismatches, resulting in a savings of 3–5 days of manual effort.

Keywords: Algorithms, Astronomers, Astrophysicists, Telescopes
Astronomical Image Quality Assessment Based on Deep Learning for Resource-constrained Environments. This paper presents a highly lightweight model for astronomical image quality assessment, named AQSA-Net, designed to address the challenges of evaluating image quality in scenarios with limited computational resources and rapid decision-making needs. With only 0.15B in computational cost and 0.67M parameters, AQSA-Net significantly reduces memory usage while enhancing inference speed and real-time processing. We construct a data set with eight quality categories based on actual astronomical images. We develop an efficient feature extraction and data processing method that integrates local and global image information, substantially reducing input resolution and training time. We optimize the AQSA-Net architecture and introduce a spatial attention unit, enabling the model to focus on key image areas, enhancing feature extraction while reducing computational overhead. AQSA-Net is compared with several classic deep convolutional neural networks, and experimental results show that AQSA-Net achieves state-of-the-art performance with minimal computational complexity and parameter count. Specifically, AQSA-Net achieves an accuracy of 97.63%, recall of 98.03%, precision of 97.79%, and F1-score of 97.91% on the test set. Additionally, to more accurately assess the quality of usable images, we construct a quantitative image quality factor and a quality grading system, providing quantifiable evaluation criteria for subsequent scientific research. Therefore, our method effectively distinguishes high-quality images from low-quality ones that may impact scientific projects. This provides a reliable automated quality assessment tool for large-scale, complex data sets requiring deep learning inspection. Furthermore, our image quality evaluation could support the assessment of scientific observation data.

Keywords: Astronomical seeing, Convolutional neural networks, Astronomy data analysis, Asteroids
CARRSSPipeline: Flux Calibration and Nonlinear Reprojection for SALT-RSS Multi-Object Spectroscopy over 3500–9500 Å. The Robert Stobie Spectrograph (RSS) on the Southern African Large Telescope (SALT) offers multi-object spectroscopy over an 8' field-of-view at resolutions up to R ∼ 3000. Reduction is typically conducted using RSSMOSPipeline, which performs basic data calibrations, sky subtraction, and wavelength calibration. However, flux calibration of SALT-RSS using spectrophotometric standard star observations is difficult due to variable primary mirror illumination. We describe a novel approach where stars with Sloan Digital Sky Survey spectra are included as alignment stars on RSS slitmasks and then used to perform a rough flux calibration of the resulting data. RSS offers multiple settings that can be pieced together to cover the entire optical range, utilizing grating angle dithers to fill chip gaps. We introduce a nonlinear reprojection routine that defines an exponential wavelength array spanning 3500–9500 Å with gradually decreasing resolution and then reprojects several individual settings into a single 2D spectrum for each object. Our flux calibration and nonlinear reprojection routines are released as part of the Calibration And Reprojection for RSS Pipeline (CARRSSPipeline), that enables the extraction of full-optical-coverage, flux-calibrated, medium-resolution one-dimensional spectra.

Keywords: Emission line galaxies, Flux calibration, Spectroscopy, Galaxy spectroscopy, Astronomy data reduction
ELT-METIS Imaging Simulations for Disks and Envelopes Associated with FU Ori-type Objects. We investigate the detectability of extended mid-infrared (MIR) emission associated with FU-Ori type objects (FUors) using the Mid-infrared ELT Imager and Spectrograph (METIS) coronagraphs on the 39 m Extremely Large Telescope. The imaging simulations were made for three representative filters (λ = 3.8, 4.8, and 11.3 μm) of the METIS instrument. We demonstrate that the detectability of the extended MIR emission using these coronagraphs is highly dependent on the uncertain nature of the central FUor and its circumstellar environment in various contexts. These contexts are: (A) whether the central radiation source is either a flat self-luminous accretion disk or a star at near-infrared (NIR) wavelengths, (B) the size of the accretion disk for the bright central MIR emission at milliarcsecond scales, (C) whether the extended emission is due to either an optically thick disk or an optically thin envelope, and (D) dust grain models. Observations at λ = 3.8 μm will allow us to detect the extended emission in many cases, while the number of cases with detection may significantly decrease toward longer wavelengths due to the fainter nature of the extended emission and high thermal background noise. In some cases, the presence of a binary companion can significantly hamper detections of the extended MIR emission. NIR and MIR imaging observations at existing 8 m class telescopes, prior to the METIS observations, will be useful for (1) reducing the many model uncertainties and (2) searching for binary companions associated with FUors, therefore determining the best observing strategy using METIS.

Keywords: Circumstellar envelopes, FU Orionis stars, Coronagraphic imaging, Circumstellar disks, Circumstellar dust
10 Years of Archival High-resolution NIR Spectra: The Raw and Reduced IGRINS Spectral Archive (RRISA). The Immersion GRating INfrared Spectrometer (IGRINS) is a compact, high-resolution (R ∼ 45,000) near-infrared spectrograph spanning 1.45─2.45 μm in a single exposure. We introduce the Raw and Reduced IGRINS Spectral Archive (RRISA), which provides public data access for all non-proprietary IGRINS data taken at McDonald Observatory's Harlan J. Smith Telescope, the Lowell Discovery Telescope (formerly Discovery Channel Telescope), and Gemini South. RRISA provides access to raw files, reduced data products, and cross-matched IGRINS targets with the SIMBAD, 2MASS, Gaia DR3, APOGEE2 DR17, and PASTEL catalogs. We also introduce version 3 of the IGRINS data reduction pipeline, IGRINS PLP v3, which implements an improved cosmic ray correction, pattern noise removal, and a new flexure correction that reduces telluric residuals. RRISA and supporting information can be found at http://igrinscontact.github.io.

Keywords: High resolution spectroscopy, Catalogs, Astronomy data reduction, Near infrared astronomy
What to Expect: Kilonova Light Curve Predictions via Equation of State Marginalization. Efficient multi-messenger observations of gravitational waves from compact object mergers rely on data products reported in low-latency by the International Gravitational-wave Network (IGWN). While data products such as HasNS, the probability of at least one neutron star, and HasRemnant, the probability of remnant matter forming after merger, exist, these are not direct observables for a potential kilonova. Here, we present new kilonova light curve and ejecta mass data products derived from merger quantities measured in low latency, by marginalizing over our uncertainty in our understanding of the neutron star equation of state and using measurements of the source properties of the merger, including masses and spins. Two additional types of data products are proposed. The first is the probability of a candidate event having mass ejecta (mej) greater than 10‑3M⊙, which we denote as HasEjecta. The second are mej estimates and accompanying ugrizy and HJK kilonova light curves predictions produced from a surrogate model trained on a grid of kilonova light curves from POSSIS, a time-dependent, three-dimensional Monte Carlo radiative transfer code. We are developing these data products in the context of the IGWN low-latency alert infrastructure, and will be advocating for their use and release for future detections.

Keywords: Neutron stars, Nuclear astrophysics, Gravitational wave astronomy