Sazuna/UAT_keywords huggingface dataset:
Multi-wavelength Classification of Active and Star-forming Galaxies on the BPT Diagram with Supervised Machine Learning Models. Distinguishing between active galactic nuclei (AGN) and star-forming galaxies (SFGs) in large astronomical surveys is an important challenge with applications to various subfields of astrophysics and cosmology. In particular, this distinction is especially crucial for informing theories of supermassive black hole formation, which are tied to our understanding of the Big Bang and the early Universe. The Baldwin─Phillips─Terlevich (BPT) diagram, which uses flux ratios of optical emission lines, has been the traditional gold standard for differentiating between these galaxies for nearly four decades. Our aim is to investigate the effect that each spectral line and photometric band has on the accuracy of supervised machine learning models in distinguishing between AGN and SFGs. The data set we employ consists of nearly thirty thousand galaxies in a crossmatch of data from the Sloan Digital Sky Survey Data Release 16 with ultraviolet, X-ray, and infrared surveys. We find that machine learning models trained on and applied to photometry alone, are able to achieve above 90% accuracy. We also find that the addition of multi-wavelength data improves upon both the accuracy and precision of the original BPT diagram, increasing the accuracy to approximately 98% when combined with spectroscopy. We also find that adding in X-ray flux data does not improve the models, which could be an indication that the X-ray properties of AGN and SFGs are more similar than what was previously theorized.

Keywords: Starburst galaxies, Active galactic nuclei, Photometry, Multi-color photometry
The Companion Mass Distribution of Post Common Envelope Hot Subdwarf Binaries: Evidence for Boosted and Disrupted Magnetic Braking?. We measure the mass distribution of main-sequence (MS) companions to hot subdwarf B stars (sdBs) in post-common envelope binaries (PCEBs). We carried out a spectroscopic survey of 14 eclipsing systems ("HW Vir binaries") with orbital periods of 3.8 &lt; Porb &lt; 12 hr, resulting in a well-understood selection function and a near-complete sample of HW Vir binaries with G &lt; 16. We constrain companion masses from the radial velocity curves of the sdB stars. The companion mass distribution peaks at MMS ≈ 0.15 M⊙ and drops off at MMS &gt; 0.2 M⊙, with only two systems hosting companions above the fully convective limit. There is no correlation between Porb and MMS within the sample. A similar drop-off in the companion mass distribution of white dwarf (WD) + MS PCEBs has been attributed to disrupted magnetic braking (MB) below the fully convective limit. We compare the sdB companion mass distribution to predictions of binary evolution simulations with a range of MB laws. Because sdBs have short lifetimes compared to WDs, explaining the lack of higher-mass MS companions to sdBs with disrupted MB requires MB to be boosted by a factor of 20–100 relative to MB laws inferred from the rotation evolution of single stars. We speculate that such boosting may be a result of irradiation-driven enhancement of the MS stars' winds. An alternative possibility is that common envelope evolution favors low-mass companions in short-period orbits, but the existence of massive WD companions to sdBs with similar periods disfavors this scenario.

Keywords: Eclipsing binary stars, B subdwarf stars, Multiple star evolution, Common envelope binary stars
A Search for Self-lensing Binaries with TESS and Constraints on their Occurrence Rate. Five self-lensing binaries (SLBs) have been discovered with Kepler light curves. They contain white dwarfs (WDs) in AU-scale orbits that gravitationally lens solar-type companions. Forming SLBs likely requires common envelope evolution when the WD progenitor is an AGB star and has a weakly bound envelope. No SLBs have yet been discovered with data from the Transiting Exoplanet Survey Satellite (TESS), which observes far more stars than Kepler did. Identifying self-lensing in TESS data is made challenging by the fact that TESS only observes most stars for ∼25 days at a time, so only a single lensing event will be observed for typical SLBs. TESS's smaller aperture also makes it sensitive only to SLBs a factor of ∼100 brighter than those to which Kepler is sensitive. We demonstrate that TESS has nevertheless likely already observed ∼4 times more detectable SLBs than Kepler. We describe a search for non-repeating self-lensing signals in TESS light curves and present preliminary candidates for which spectroscopic follow-up is ongoing. We calculate the sensitivity of our search with injection and recovery tests on TESS and Kepler light curves. Based on the 5 SLBs discovered with Kepler light curves, we estimate that (1.1 ± 0.6)% of solar-type stars are orbited by WDs with periods of 100–1000 days. This implies a space density of AU-scale WD + main sequence (MS) binaries a factor of 20–100 larger than that of astrometrically identified WD + MS binaries with orbits in Gaia DR3. We conclude that the Gaia sample is still quite incomplete, mainly because WD + MS binaries can only be unambiguously identified as such for high mass ratios.

Keywords: Gravitational lensing, White dwarf stars, Binary stars, Astrometry
Radiative Transfer Modeling of Haumea's Dust Ring. Among the growing number of small body rings in the solar system, the ring of Haumea has a special status as it is likely suitable for direct imaging in the visible and submillimeter wavelengths. In this paper, we highlight its sole detectability among Centaur/Trans-Neptunian Object rings using both the Atacama Large Millimeter/submillimeter Array and the James Webb Space Telescope to provide direct constraints on the ring composition for the first time. To overcome the limitations of the currently used simple ring models, we introduce radiative transfer modeling for small body ring systems. Here we perform a thorough analysis of the Haumea ring considering different materials and grain sizes, assuming that the ring consists of small particles with sizes below 1 mm. We present spectral energy distributions of each model for future comparison with multiwavelength measurements, providing a diagnostic tool to determine the dominant grain size and characteristic material of the ring, which are essential inputs for ring formation and evolution theories. Our results also show that for some sub-micron carbon-like or silicate grains, their mid-infrared excess can be detected even if the ring is not resolved, providing a tracer for small grains around the object.

Keywords: Dwarf planets, Planetary rings, Solar system astronomy
CAMO-S: A Meteor-tracking Spectrograph at the Canadian Automated Meteor Observatory. The Canadian Automated Meteor Observatory (CAMO) mirror tracking system has been in operation since 2009 and has, to date, produced more than 20,000 two-station meteor observations at meter-level spatial and 10 ms temporal resolution. In 2020, a spectral tracking camera was added in parallel at one of the CAMO stations. To date, it has recorded the spectra of hundreds of faint meteors. Engineering testing from 2020 to 2023 resulted in the selection of a 150 lpmm grating and an EMCCD camera to achieve a spectral resolution of about 1 nm pixel‑1 in the final configuration. The CAMO spectral system can resolve spectra from individual meteoroid fragments, record spectra for meteors of +2 peak magnitude to as faint as +4 in parts of the lightcurve and produce relative abundance estimates for Mg, Fe and Na. Our preliminary results also show identification of the H and K lines of CA(II). Meteors with strong iron lines were found to have unusual fragmentation behaviour, involving gross fragmentation rather than continuously shedding small particles. The spectra of individual fragments can be resolved in some cases, showing that these Fe-rich objects do not differ in composition among fragments. Our calibration procedure and hardware configuration are discussed together with preliminary results.

Keywords: Astronomical instrumentation, Meteors, Spectroscopy
Gen TSO: A General JWST Simulator for Exoplanet Times-series Observations. GEN TSO is a noise calculator specifically tailored to simulate James Webb Space Telescope (JWST) time-series observations of exoplanets. GEN TSO enables the estimation of signal-to-noise ratios (S/Ns) for transit or eclipse depths through an interactive graphical interface, similar to the JWST Exposure Time Calculator (ETC). This interface leverages the ETC by combining its noise simulator, PANDEIA, with additional exoplanet resources from the NASA Exoplanet Archive, the Gaia DR3 catalog of stellar sources, and the TrExoLiSTS database of JWST programs. The initial release of GEN TSO allows users to calculate S/Ns for all JWST instruments for the spectroscopic time-series modes available as of the Cycle 4 GO call. Additionally, GEN TSO allows users to simulate target acquisition on the science targets or, when needed, on nearby stellar targets within the visit splitting distance. This article presents an overview of GEN TSO and its main functionalities. GEN TSO has been designed to provide both an intuitive graphical interface and a modular API to access the resources mentioned above, facilitating planing and simulation of JWST exoplanet time-series observations. GEN TSO is available for installation via the Python Package Index and its documentation can be found at pcubillos.github.io/gen_tso.

Keywords: Time series analysis, Astronomy databases, Exoplanets
STIPS: The Nancy Grace Roman Space Telescope Imaging Product Simulator. The Space Telescope Imaging Product Simulator (STIPS) is a Python-based package that can be used to simulate scenes from the upcoming Nancy Grace Roman Space Telescope (Roman). STIPS is able to generate post-pipeline astronomical images of any number of sensor chip assembly (SCA) detectors, up to the entire 18-SCA Wide-Field Instrument array on Roman. STIPS can inject either point spread functions generated with WebbPSF, or extended sources in any of the Roman filters. The output images can include flat field, dark current, and cosmic ray residuals. Additionally, STIPS includes an estimate of Poisson and readout noise, as well as an estimate of the zodiacal background and internal background from the telescope. However, STIPS does not include instrument saturation, nonlinearity, or distortion effects. STIPS is provided as an open source repository on GitHub ✎.

Keywords: Astronomical techniques, Astronomical methods, Telescopes
A 400 Gbit Ethernet Core Enabling High Data Rate Streaming from FPGAs to Servers and GPUs in Radio Astronomy. The increased bandwidth coupled with the large numbers of antennas of several new radio telescope arrays has resulted in an exponential increase in the amount of data that needs to be recorded and processed. In many cases, it is necessary to process this data in real time, as the raw data volumes are too high to be recorded and stored. Due to the ability of GPUs to process data in parallel, GPUs are increasingly used for data-intensive tasks. In most radio astronomy digital instrumentation (e.g., correlators for spectral imaging, beamforming, pulsar, fast radio burst and SETI searching), the processing power of modern GPUs is limited by the input/output data rate, not by the GPU's computation ability. Techniques for streaming ultra-high-rate data to GPUs, such as those described in this paper, reduce the number of GPUs and servers needed, and make significant reductions in the cost, power consumption, size, and complexity of GPU based radio astronomy backends. In this research, we developed and tested several different techniques to stream data from network interface cards (NICs) to GPUs. We also developed an open-source UDP/IPv4 400 GbE wrapper for the AMD/Xilinx IP demonstrating high-speed data stream transfer from a field programmable gate array (FPGA) to GPU.

Keywords: Astronomical techniques, Astronomical instrumentation, Astronomy data acquisition
Picture Perfect: Photometric Transient Classification Using the ParSNIP Model with Roman Hourglass Simulations. The Roman Space Telescope, equipped with a 2.4 m primary mirror and optical─NIR wide-field camera, promises to revolutionize our understanding of dark energy, exoplanets, and infrared astrophysics. One of the Roman Core Community Surveys is the High Latitude Time Domain Survey (HLTDS), which will measure more than 10,000 SN Ia light curves but obtain a fraction of this number with spectra. The remaining SNe will have to be photometrically classified to achieve the full potential of the Roman HLTDS. To investigate transient yields and classifications, Rose et al. updated the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC) framework (originally developed for the Vera Rubin Observatory) for the Roman HLTDS. This study leverages this Roman "Hourglass" data set to train and evaluate the ParSNIP (Parameterized Supernova Identification Pipeline) model. We employ this model to classify various transient types from photometric data, paying particular attention to the types most represented in the data set: normal SNe Ia, 91bg-like SNe Ia, SNe Iax, and CC SNe. The ParSNIP model's performance is assessed through confusion matrices and ROC curves across different redshift ranges. Our analysis reveals that while the model performs robustly at higher redshifts (with the AUC for classification varying between 0.9 and 0.95 in the range 0.5 ≲ z ≲ 2), its accuracy dips at the lowest redshifts of the survey, likely due to limited training data. These findings underscore the importance of ensuring adequate representation of classes in the training set. This work underscores the value of machine learning models for next-generation surveys, paving the way for future studies with the Roman Space Telescope for survey optimization, cosmological forecasts, and synergies with other surveys.

Keywords: Observational cosmology, Core-collapse supernovae, Neural networks
Lucky Imaging Based Blind Deconvolution Algorithm for Wide Field-of-view Solar GLAO Image. This paper proposes a lucky imaging based blind deconvolution algorithm for wide field-of-view (FoV) ground layer adaptive optics (GLAO) solar images. Our method effectively combines the advantages of traditional lucky imaging and blind deconvolution techniques, by segmenting and reconstructing sub-images in different field directions of the captured image sequence, as well as stitching and fusing reconstructed results of multiple regions, which significantly improves the robustness of reconstruction results. High quality wide FoV reconstruction results were obtained for actual GLAO solar images collected by a 1 m New Vacuum Solar Telescope in experiments. After processing, the Image Sharpness Metric Based on the Notion of Just Notifiable Blur improved by 51.39% and 53.65% compared to the average frame of the input image. The algorithm proposed can help achieve good results in every field direction for wide FoV images, which can provide important data support for subsequent research.

Keywords: Solar optical telescopes, Field of view, Solar observatories, Astronomy data analysis
Leveraging Movement Representation from Contrastive Learning for Asteroid Detection. To support asteroid-related studies, current motion detectors are utilized to select moving object candidates based on their visualizations and movements in sequences of sky exposures. However, the existing detectors encounter the manual parameter settings which require experts to assign proper parameters. Moreover, although the deep learning approach could automate the detection process, these approaches still require synthetic images and hand-engineered features to improve their performance. In this work, we propose an end-to-end deep learning model consisting of two branches. The first branch is trained with contrastive learning to extract a contrastive feature from sequences of sky exposures. This learning method encourages the model to capture a lower-dimensional representation, ensuring that sequences with moving sources (i.e., potential asteroids) are distinct from those without moving sources. The second branch is designed to learn additional features from the sky exposure sequences, which are then concatenated into the movement features before being processed by subsequent layers for the detection of asteroid candidates. We evaluate our model on sufficiently long-duration sequences and perform a comparative study with detection software. Additionally, we demonstrate the use of our model to suggest potential asteroids using photometry filtering. The proposed model outperforms the baseline model for asteroid streak detection by +7.70% of f1-score. Moreover, our study shows promising performance for long-duration sequences and improvement after adding the contrastive feature. Additionally, we demonstrate the uses of our model with the filtering to detect potential asteroids in wide-field detection using the long-duration sequences. Our model could complement the software as it suggests additional asteroids to its detection result.

Keywords: Computational astronomy, Convolutional neural networks, Astronomy data analysis, Asteroids
Real-time Collision Detection of Dual Rotating Arm Positioner for Multi-object Fiber-fed Spectrographs. Multi-object fiber spectroscopic survey is pivotal to astronomical research. Most spectroscopic telescopes are equipped with thousands of robotic fiber positioners designed to observe multiple celestial objects simultaneously. Despite this advancement, the risk of potential collisions between adjacent positioners, due to overlapping work zones, poses a significant challenge that could limit the telescope's observing efficiency. In this study, we present a method based on deep learning to detect the collision of dual rotating arm positioner using the front-illuminated image from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). We employ a deep learning detection model based on the YOLOv5 object detection algorithm to identify and locate the collision zones. Furthermore, the BiSeNet image segmentation algorithm is applied to determine the positioners within these collision zones, ultimately identifying the collided positioners. Experimental results reveal a precision and recall of 90.20% and 85.44% respectively for our method. To verify our results further, we conducted a correlation analysis on the spectral flux in LAMOST survey data via direct measurement. The collision types of the LAMOST positioners are also analyzed, which provides guidance for optimizing the anti-collision algorithm in the future.

Keywords: Astronomical techniques, Astronomical instrumentation, Astronomical methods
Morphological and Spectral Characterization of Lunar Regolith Breakdown due to Water Ice. Remote sensing observations of the Moon suggest that the lunar polar regolith environment is affected by several natural processes that may cause the regolith in these regions to become more porous and fine particulate. One of these processes may be the mechanical breakdown of regolith particles through the interaction of water ice and regolith by frost wedging. We present morphological and spectral analyses of high-fidelity lunar regolith simulants LHS-1 (lunar highlands simulant-1) and LMS-1 (lunar mare simulant-1) that have been exposed to varying concentrations of water ice (1, 10, and 30 wt%) over extended periods of time (1, 3, and 6 months) to evaluate the extent at which lunar regolith may be weathered by ice-regolith interactions in the Moon's polar regions. To characterize changes in regolith particle morphology, we explored grain size and shape parameters with the CILAS ExpertShape suite and characterized the abundance and evolution of clinging fines with scanning electron microscopy and energy dispersive X-ray spectroscopy. Reflectance spectra were taken from 1.0-22.5 μm (444.4-10,000 cm-1) to characterize any differences in spectral features that may occur as a result of regolith breakdown. Both the morphological and spectral investigations display trends that show simulant particle degradation as a function of composition, increasing water concentration, and freezing time. Our study demonstrates that the lunar regolith is susceptible to mechanical breakdown in the presence of water ice and that water ice is likely a contributor to the weathering environment within permanently shadowed regions on the lunar surface.

Keywords: Planetary surfaces, Infrared spectroscopy, Lunar regolith, The Moon, Lunar science, Lunar surface, Surface ices, Planetary science, Regolith
A New 2D Energy Balance Model for Simulating the Climates of Rapidly and Slowly Rotating Terrestrial Planets. Energy balance models (EBMs), alongside radiative-convective climate models and global climate models (GCMs), are useful tools for simulating planetary climates. Historically, planetary and exoplanetary EBMs have solely been 1D latitudinally dependent models with no longitudinal dependence, until the study of Okuya et al., which focused on simulating synchronously rotating planets. Following the work of Okuya et al., I have designed the first 2D EBM (PlaHab) that can simulate N2-CO2-H2O-H2 atmospheres of both rapidly and synchronously rotating planets, including Mars, Earth, and exoplanets located within their circumstellar habitable zones. PlaHab includes physics for both water and CO2 condensation. Regional topography can be incorporated. Here, I have specifically applied PlaHab to investigate the present Earth, early Mars, TRAPPIST-1 e, and Proxima Centauri b, representing examples of habitable (and potentially habitable) worlds in our solar system and beyond. I compare my EBM results against those of other 1D and 3D models, including those of the recent Trappist-1 Habitable Atmosphere comparison project. Overall, the EBM results are consistent with those of other 1D and 3D models, although inconsistencies among all models continue to be related to the treatment of clouds and other known differences between EBMs and GCMs, including heat transport parameterizations. Although 2D EBMs are a relatively new entry in the study of planetary/exoplanetary climates, their ease of use, speed, flexibility, wide applicability, and greater complexity (relative to 1D models) may indicate an ideal combination for the modeling of planetary and exoplanetary atmospheres alike.

Keywords: Extrasolar rocky planets, Mars, Planetary atmospheres, Solar system terrestrial planets, Earth (planet), Planetary climates, Habitable planets, Exoplanet atmospheres