Sazuna/UAT_keywords huggingface dataset:
Results from NASA's First Radio Telescope on the Moon: Terrestrial Technosignatures and the Low-frequency Galactic Background Observed by ROLSES-1 on Board the Odysseus Lander. Radio wave Observations on the Lunar Surface of the photo-Electron Sheath (ROLSES-1) instrument on board Intuitive Machines' Odysseus lunar lander represents NASA's first radio telescope on the Moon, and the first United States spacecraft landing on the lunar surface in five decades. Despite a host of challenges, ROLSES-1 managed to collect a small amount of data over fractions of 1 day during cruise phase and 2 days on the lunar surface with four monopole Stacer antennas that were in a nonideal deployment. All antennas recorded shortwave radio transmissions breaking through the Earth's ionosphere—or terrestrial technosignatures—from spectral and raw waveform data. These technosignatures appear to be modulated by density fluctuations in the Earth's ionosphere and could be used as markers when searching for extraterrestrial intelligence from habitable exoplanets. After data reduction and marshalling a host of statistical and sampling techniques, 5 minutes of raw waveforms from the least noisy antenna were used to generate covariances constraining both the antenna parameters and the amplitude of the low-frequency isotropic Galactic spectrum. ROLSES-2 and LuSEE-Night, both lunar radio telescopes launching later in the decade, will have significant upgrades from ROLSES-1 and will be set to take unprecedented measurements of the low-frequency sky, lunar surface, and constrain the cosmological 21 cm signal. ROLSES-1 represents a trailblazer for lunar radio telescopes, and many of the statistical tools and data reduction techniques presented in this work will be useful for upcoming lunar radio telescope missions.

Keywords: Radio spectroscopy, Technosignatures, The Moon, Space telescopes, Galaxy spectroscopy, Radio astronomy, Astronomical methods
Observations of Five Southern-hemisphere Cataclysmic Binary Stars. We present observations and analyses of five little-studied cataclysmic binary stars in the southern celestial hemisphere. Our new observations are from the South African Astronomical Observatory. The objects and salient results are as follows: (i) 6dF0752-54 is a dwarf nova with an orbital period Porb = 5.05 hr that shows a contribution from a mid-M-type secondary in its mean spectrum. (ii) J0916-26 had been suspected of being a magnetic cataclysmic variable with an eclipse period of 3.37 hr. Our spectrum corroborates this classification. (iii) GSC 08944 is a nova-like variable with Porb = 3.80 hr. Archival photometry also shows a persistent photometric period near 4.03 hr, apparently from a positive superhump. Its emission line behavior is consistent with an SW Sextantis-type nova-like. (iv) MGAB-V253, also Gaia20eys, had been identified as a short-period eclipsing nova-like with Porb = 1.44 hr. Our spectrum shows broad emission lines consistent with this, and the extensive Transiting Exoplanet Survey Satellite (TESS) data show a persistent modulation near 1.35 hr, evidently a negative superhump. It is less luminous than most nova-likes, but significantly brighter than quiescent dwarf novae with comparably short periods. (v) Finally, DDE 45 shows a complicated variability history, cycling rapidly between high and low states for a time and more recently showing outbursts resembling a U Gem-type dwarf nova. We find a 2.07 hr radial velocity period, which also appears in archival TESS photometry. The emission lines are double-peaked, with an orbital S-wave similar to low-inclination dwarf novae.

Keywords: Cataclysmic variable stars
Detection of Exoplanets with Machine Learning Techniques Through Transit Light-curve Analysis. Exoplanet detection is an active research area in astronomy. As the volume of astronomical data increases, there is a need for methods that can automate the data processing pipeline efficiently. This study examines how classical machine learning algorithms, can classify exoplanet candidates without using deep learning models. Our comparative analysis of different machine learning techniques shows that classical algorithms can perform at a level comparable to advanced deep learning methods. By utilizing the time series analysis library tsfresh, we were able to extract 740 features from each light curve, effectively capturing its key statistical, temporal, and spectral characteristics. Among the evaluated machine learning techniques, XGBoost and XGBoost calibrated demonstrated the highest predictive performance. XGBoost achieved an accuracy of 89%, followed by histogram gradient boosting at 87%. Sensitivity and precision metrics remained consistent across models, with F1-scores ranging from 82% to 89%. We further employed receiver operating characteristic and precision─recall curves to evaluate model performance, demonstrating their ability to distinguish between positive instances while minimising false positives. Finally, our calibrated XGBoost-based model revalidates 14 exoplanet candidates from NASA's Exoplanet Archive, which were validated against Kepler Robovetter confidence scores and benchmarked with known exoplanet discoveries.

Keywords: Exoplanet detection methods, Transit photometry, Time series analysis
52 Eclipsing Quadruple Star Candidates Discovered in TESS Full Frame Images. We present the discovery of 52 eclipsing quadruple star candidates detected in TESS Full Frame Image ELEANOR data by machine learning and citizen scientists. The uniformly vetted and validated targets exhibit two sets of eclipses following two distinct periods, representing quadruple systems with a 2+2 hierarchical configuration. Detailed photocenter measurements confirmed that both sets of eclipses originate within ∼0.1─0.2 pixels (∼2″─4″) of the corresponding target, and ruled out resolved nearby field stars. The catalog includes a number of systems producing prominent eclipse timing variations and/or apsidal motion, a quadruple with an outer period of ∼1400 days, and even a 2+2 quadruple in a likely wide quintuple with a resolved comoving star. Additionally, two systems have complete astrometric solutions for the outer orbits from Gaia. We provide the measured ephemerides, eclipse depths and durations, and overall statistical properties, and we highlight potentially interesting systems that merit further investigations.

Keywords: Eclipsing binary stars, Multiple stars
Surprise Nondetection of Upsilon Andromedae b with MIRC-X and MYSTIC at the CHARA Array. Ground-based long baseline interferometry is a powerful tool for characterizing exoplanets that are too close to their host star to be imaged with single-dish telescopes. The CHARA Array can resolve companions down to 0.5 mas, allowing us in principle to directly measure the near-infrared spectra of nontransiting "hot Jupiter" exoplanets. We present data taken with the Michigan InfraRed Combiner-Exeter (MIRC-X) and MYSTIC instruments at the CHARA Array on the hot Jupiter Upsilon Andromedae b. By resolving the star─planet system, we attempt to directly detect the flux from the planet. We describe our self-calibration methods for modeling systematics in the closure phase data, which allows us to reach subdegree precision. Through combining multiple nights of data across two MIRC-X runs in 2019 and 2021, we achieved a very tentative detection of Ups And b in the H band at a planet/star contrast of 2─3 × 10−4. Unfortunately, we cannot confirm this detection with 2021 MYSTIC data in the K band, or in a 2023 joint MIRC-X and MYSTIC data set. We run updated global circulation models and create post-processed spectra for this planet, and report the resulting model spectra in H- and K bands as a function of orbital phase. We then run planetary injection tests to explore H/K-band contrast limits, and find that we can confidently recover planets down to a planet/star contrast of 1─2 × 10−4. We show that we are probing contrasts fainter than predicted by the model, making our nondetection surprising. We discuss prospects for the future in using this method to characterize companions with interferometry.

Keywords: Exoplanet astronomy, Exoplanet detection methods
The Library of Exoplanet Atmospheric Composition Measurements: Population-level Trends in Exoplanet Composition with ExoComp. The present-day bulk elemental composition of an exoplanet can provide insight into a planet's formation and evolutionary history. Such information is now being measured for dozens of planets with state-of-the-art facilities using Bayesian atmosphere retrievals. We collect measurements of exoplanet composition of gas giants into a Library of Exoplanet Atmospheric Composition Measurements for comparison on a population level. We develop an open-source tool kit, ExoComp, to standardize between solar abundance, metallicity, and C/O ratio definitions. We find a systematic enhancement in the metallicity of exoplanets compared to T dwarf and stellar populations, a strict bound in C/O between 0 and 1, and statistically significant differences between measurements from direct, eclipse, and transmission spectroscopy. In particular, the transit spectroscopy population exhibits a systematically lower C/O ratio compared to planets observed with eclipse and direct spectroscopy. While such differences may be astrophysical signals, we discuss many of the challenges and subtleties of such a comparison. We characterize the mass─metallicity trend, finding a slope consistent between planets measured in transit versus eclipse, but offset in metallicity. Compared to the solar system and constraints from interior modeling, gas giant atmospheres appear to exhibit a steeper mass─metallicity trend. We hope that the tools available in ExoComp and the data in the Library of Exoplanet Atmospheric Composition Measurements can enhance the science return of the wide-array of space- and ground-based exoplanet science being undertaken by the community.

Keywords: Exoplanet atmospheric composition , Exoplanet formation, Infrared spectroscopy, Transmission spectroscopy
Modeling Atmospheric Phase Corruptions in High-frequency Very-long-baseline Interferometry Using Gaussian Processes. Using very-long-baseline interferometry (VLBI) observations at (sub)millimeter wavelengths, the Event Horizon Telescope (EHT) currently achieves the finest angular resolution of any astronomical facility, necessary for imaging the horizon-scale structure around supermassive black holes. A significant calibration challenge for high-frequency VLBI stems from rapid variations in the atmospheric water vapor content above each telescope in the array, which induce corresponding fluctuations in the phase of the correlated signal that limit the coherent integration time and thus the achievable sensitivity. In this paper, we introduce a model that describes station-based phase corruptions jointly with a parameterization for the source structure. We adopt a Gaussian process (GP) prescription for the time evolution of these phase corruptions, which provides sufficient flexibility to capture even highly erratic phase behavior. The use of GPs permits the application of a Kalman filtering algorithm for numerical marginalization of these phase corruptions, which permits efficient exploration of the remaining parameter space. Our model also removes the need to specify an arbitrary "reference station" during calibration, instead establishing a global phase zero-point by enforcing the GPs at all stations to have fixed mean and finite variance. We validate our method using a real EHT observation of the blazar 3C 279, demonstrating that our approach yields calibration solutions that are consistent with those determined by the EHT Collaboration. The model presented here can be straightforwardly extended to incorporate frequency-dependent phase behavior, such as is relevant for the frequency phase transfer calibration technique.

Keywords: Calibration, Very long baseline interferometry, Radio interferometry, Interferometry
Machine Learning for Radial Velocity Analysis. I. Vision Transformers as a Robust Alternative for Detecting Planetary Candidates. Extreme precision radial velocity (EPRV) surveys usually require extensive observational baselines to confirm planetary candidates, making them resource-intensive. Traditionally, periodograms are used to identify promising candidate signals before further observational investment, but their effectiveness is often limited for low-amplitude signals due to stellar jitter. In this work, we develop a machine learning (ML) framework based on a transformer architecture that aims to detect the presence and likely period of planetary signals in time-series spectra, even in the presence of stellar activity. The model is trained to classify whether a planetary signal exists and assign it to one of several discrete period and amplitude bins. Injection-recovery tests on randomly selected 100 epoch observation subsets from NEID solar data (2020─2022 period) show that for low-amplitude systems (&lt;1 m s−1), our model improves planetary candidate identification by a factor of 2 compared to the traditional Lomb─Scargle periodogram. Our ML model is built on a Vision Transformer architecture that processes reduced representations of solar spectrum observations to predict the period and semi-amplitude of planetary signal candidates. By analyzing multiepoch spectra, the model reliably detects planetary signals with semi-amplitudes as low as 65 cm s−1. Even under real solar noise and irregular sampling, it identifies signals down to 35 cm s−1. Comparisons with the Lomb─Scargle periodogram demonstrate a significant improvement in detecting low-amplitude planetary candidates, particularly for longer orbital periods. These results underscore the potential of ML to identify planetary candidates early in EPRV surveys, even from limited observational counts.

Keywords: Exoplanet detection methods, Radial velocity, Algorithms, Stellar activity
PEPSI Investigation, Retrieval, and Atlas of Numerous Giant Atmospheres (PIRANGA). IV. High-resolution Phased-resolved Spectroscopy of the Ultra-hot-Jupiter KELT-20 b. We present five datasets of high-resolution optical emission spectra of the ultra-hot-Jupiter KELT-20 b with the PEPSI spectrograph. Using a Bayesian retrieval framework, we constrain its dayside pressure─temperature profile and abundances of Fe, Ni, and Ca, providing the first measurements for Ni and Ca for KELT-20 b in emission. We retrieve the preeclipse and posteclipse datasets separately (corresponding to the evening and morning sides, respectively), and compare the constraints on their thermal structures and chemical abundances. We constrain lower abundances in the pre-eclipse datasets compared to the posteclipse datasets. We interpret these results with an equilibrium chemistry model which suggests ∼10─30× supersolar refractory abundances. Due to the well-known degeneracy between absolute abundances and continuum opacities, the abundance ratios are more precise probes of the planetary abundances. Therefore we measure the abundance ratios [Ni/Fe] and [Ca/Fe] across these datasets and find they agree within 1σ. We constrain [Ni/Fe] to be consistent with solar within 2σ, and [Ca/Fe] to be 0.001─0.01× solar, not accounting for ionization. We compare these abundance ratios with literature results for KELT-20 b in transmission, and find they agree within 2σ, suggesting that even though the abundances vary significantly as a function of phase, the abundance ratios of these species remain relatively constant. We find a ∼100 K difference in temperature at the top of the thermal inversion, suggesting a hotter evening side than morning side and underscoring the importance of considering 3D effects when studying ultrahot Jupiters.

Keywords: High resolution spectroscopy, Exoplanet atmospheric composition , Extrasolar gaseous giant planets, Exoplanet atmospheres
The Relation between the Radio Emission of the Core and Host Galaxy Properties in Fanaroff─Riley Type I Radio Galaxies. The Fanaroff─Riley radio galaxies exhibit the most extensive radio emissions derived from the active nuclei of galaxies. They morphologically differ from the highly compact and bright radio galaxies observed as gigahertz peaked spectrum and compact steep spectrum sources. Their emissions include jets, lobes, and a central core component, which may expand to larger scales in the future. We study the cores of extended radio galaxies by comparing samples of core-dominated and core-poor populations from FRI radio galaxies. Matching them in redshift, stellar mass, and total radio luminosity, we found no statistically significant differences between the two samples. However, core-dominated FRIs exhibit slightly higher [O III] luminosity compared to core-poor FRIs. Additionally, the hosts of core-dominated FRIs demonstrate slightly higher surface mass density and lower specific star formation rate. The p-values for the observed differences fall within the marginal range (p ≲ 0.1), suggesting that the differences may be meaningful and warrant further consideration, although they do not meet the conventional significance threshold (p &lt; 0.05). We also discuss the possible influences of obscuration, recycling activity, and relativistic beaming that may cause uncertainties and compare the results with those of Mazoochi et al. for FRII radio galaxies.

Keywords: AGN host galaxies, Radio cores, Fanaroff-Riley radio galaxies
CoronaGraph Instrument Reference Stars for Exoplanets (CorGI-REx). I. Preliminary Vetting and Implications for the Roman Coronagraph and Habitable Worlds Observatory. The upcoming Roman Coronagraph will be the first high-contrast instrument in space capable of high-order wave front sensing and control technologies, a critical technology demonstration for the proposed Habitable Worlds Observatory (HWO) that aims to directly image and characterize habitable exoEarths. The nominal Roman Coronagraph observing plan involves alternating observations of a science target and a bright, nearby reference star. High contrast is achieved using wave front sensing and control, also known as "digging a dark hole," where performance depends on the properties of the reference star, requiring V &lt; 3, a resolved stellar diameter &lt;2 mas, and no stellar multiplicity. The imposed brightness and diameter criteria limit the sample of reference star candidates to high-mass main-sequence and post-main-sequence objects, where multiplicity rates are high. A future HWO coronagraph may have similarly restrictive criteria in reference star selection. From an exhaustive literature review of 95 stars, we identify an initial list of 40 primary and 18 reserve reference star candidates relevant to both the Roman Coronagraph and HWO. We present results from an initial survey of these candidates with high-resolution adaptive optics imaging and speckle interferometry and identify no new companions. We discuss the need for higher-contrast observations to sufficiently vet these reference star candidates prior to Roman Coronagraph observations, along with the implications of reference star criteria on observation planning for Roman and HWO.

Keywords: High contrast techniques, Binary stars, Adaptive optics, Exoplanet astronomy, Direct imaging, Astronomical instrumentation, Speckle interferometry, Near infrared astronomy
robostrategy: Field and Target Assignment Optimization in the Sloan Digital Sky Survey V. We present an algorithmic method for efficiently planning a long-term, large-scale multiobject spectroscopy program. The Sloan Digital Sky Survey V (SDSS-V) Focal Plane System performs multiobject spectroscopy using 500 robotic positioners to place fibers feeding optical and infrared spectrographs across a wide field. SDSS-V uses this system to observe targets throughout the year at two observatories in support of the science goals of its Milky Way Mapper and Black Hole Mapper programs. These science goals require observations of objects over time with preferred temporal spacings (referred to as "cadences"), which can differ from object to object even in the same area of sky. robostrategy is the software we use to construct our planned observations so that they can best achieve the desired goals given the time available as a function of sky brightness and local sidereal time, and to assign fibers to targets during specific observations. We use linear programming techniques to seek optimal allocations of time under the constraints given. We present the methods and example results obtained with this software.

Keywords: Astronomy software
Anchoring Stellar Age Indicators: A Cross Calibration of [C/N] and Gyrochronology Ages via the Age─Velocity Dispersion Relation. Determining stellar ages is challenging, as it depends on other stellar parameters in a nonlinear way and often relies on stellar evolution models to infer the underlying relation between these parameters and age. This complexity increases when comparing different age-dating methods, as they rely on distinct indicators and are often applicable to nonoverlapping regions of the color─magnitude diagram. Moreover, many empirical calibration methods rely on predetermined ages, often from open clusters or asteroseismology, which only cover a limited parameter space. Fortunately, the age─velocity dispersion relation (AVR), in which the velocity dispersion increases with age, is a universal feature among stars of all evolutionary stages. In this paper, we (1) explore the parameter space in which [C/N] and gyrochronology are applicable, extending beyond the domains probed by asteroseismology and open clusters, and (2) assess whether the traditionally assumed [C/N] and gyrochronology relations yield ages on a consistent physical scale, after calibrating both using the same AVR. We find gyrochronology can be applied to all partially convective stars after they have converged onto the slow rotating sequence and before they experience weakened magnetic braking; [C/N] can be used to infer ages for all giants with metallicity &gt;−0.8 dex and [C/N] &lt; −0.05 dex, and can be used as an age indicator down to [Fe/H] of −1 dex if only selecting the low-α disk. Lastly, ages obtained from [C/N] and gyrochronology agree within uncertainty after accounting for systematic offsets.

Keywords: Stellar kinematics, Stellar abundances, Stellar rotation, Stellar ages
JWST Reveals Carbon-rich Chemistry in a Transitional Disk. We present JWST-MIRI Medium Resolution Spectrometer observations of the Classical T Tauri stars GM Aur and RX J1615.3-3255 (J1615), both hosting transitional disks. Despite their similar stellar and disk properties, the two systems differ strikingly in their carbon-bearing molecular emission. Using local thermodynamic equilibrium slab models to analyze spectral lines within the 13.6─17.7 μm wavelength range, we find that J1615 exhibits strong emission from H2O, HCN, C2H2, 12CO2, 13CO2, OH, and 13C12CH2, whereas GM Aur shows only H2O and OH. We measure the accretion rates of both objects using contemporaneous optical spectra and find that J1615's accretion rate is lower than that of GM Aur. We constrain the properties of the dust in both disks using spectral energy distribution modeling and find elevated amounts of crystalline silicates and larger dust grains in the disk of J1615. The enhanced carbon emission in J1615 may result from a combination of lower accretion rate and larger and more processed dust grains in the inner disk, conditions that together may allow for carbon-rich gas to persist and be detected. These results expand the sample of protoplanetary disks around solar-mass stars with strong CO2 and C2H2 emission and identify J1615 as a carbon-rich transitional disk, providing new insights into the chemical diversity of planet-forming environments.

Keywords: Stellar accretion disks, Pre-main sequence stars, Protoplanetary disks