Sazuna/UAT_keywords huggingface dataset:
Toward a Live Homogeneous Database of Solar Active Regions Based on SOHO/MDI and SDO/HMI Synoptic Magnetograms. I. Automatic Detection and Calibration. Recent studies indicate that a small number of rogue solar active regions (ARs) may have a significant impact on the end-of-cycle polar field and the long-term behavior of solar activity. The impact of individual ARs can be qualified based on their magnetic field distribution. This motivates us to build a live homogeneous AR database in a series of papers. As the first of the series, we develop a method to automatically detect ARs from 1996 onward based on SOHO/MDI and SDO/HMI synoptic magnetograms. The method shows its advantages in excluding decayed ARs and unipolar regions and being compatible with any available synoptic magnetograms. The identified AR flux and area are calibrated based on the cotemporal SDO/HMI and SOHO/MDI data. The homogeneity and reliability of the database are further verified by comparing it with other relevant databases. We find that ARs with weaker flux have a weaker cycle dependence. Stronger ARs show a weaker cycle 24 compared with cycle 23. Several basic parameters, namely, the location, area, and flux of negative and positive polarities of the identified ARs, are provided in the paper. This paves the way for ARs' new parameters quantifying the impact on the long-term behavior of solar activity to be presented in the subsequent paper of the series. The constantly updated database covering more than two full solar cycles will be beneficial for the understanding and prediction of the solar cycle. The database and the detection codes are accessible online.

Keywords: Solar cycle, Solar active regions, Astronomy databases, Astronomy image processing
A Systematic Observational Study on Galactic Interstellar Ratio <SUP>18</SUP>O/<SUP>17</SUP>O. II. C<SUP>18</SUP>O and C<SUP>17</SUP>O J = 2-1 Data Analysis. To investigate the relative amount of ejecta from high-mass versus intermediate-mass stars and to trace the chemical evolution of the Galaxy, we have performed a systematic study of Galactic interstellar 18O/17O ratios toward a sample of 421 molecular clouds with IRAM 30 m and the 10 m Submillimeter Telescope, covering a galactocentric distance range of ~1-22 kpc. The results presented in this paper are based on the J = 2-1 transition and encompass 364 sources showing both C18O and C17O detections. The previously suggested 18O/17O gradient is confirmed. For the 41 sources detected with both facilities, good agreement is obtained. A correlation of the 18O/17O ratios with heliocentric distance is not found, indicating that beam dilution and linear beam sizes are not relevant. For the subsample of IRAM 30 m high-mass star-forming regions with accurate parallax distances, an unweighted fit gives 18O/17O = (0.12 ± 0.02)R GC + (2.38 ± 0.13) with a correlation coefficient of R = 0.67. While the slope is consistent with our J = 1-0 measurement, the ratios are systematically lower. This should be caused by larger optical depths of C18O 2-1 lines with respect to the corresponding 1-0 transitions, which is supported by RADEX calculations and the fact that C18O/C17O is positively correlated with 13CO/C18O. When we consider that optical depth effects with C18O J = 2-1 typically reach an optical depth of ~0.5, the corrected 18O/17O ratios from the J = 1-0 and J = 2-1 lines are consistent. A good numerical fit to the data is provided by the MWG-12 model, which includes both rotating stars and novae.

Keywords: Interstellar molecules, Isotopic abundances, Radio source counts, Galaxy chemical evolution
Photometric Selection of Unobscured QSOs at the Ecliptic Poles: KMTNet in the South Field and Pan-STARRS in the North Field. We search for quasi-stellar objects (QSOs) in a wide area of the south ecliptic pole (SEP) field, which has been and will continue to be intensively explored through various space missions. For this purpose, we obtain deep broadband optical images of the SEP field covering an area of ∼14.5 × 14.5 deg2 with the Korea Microlensing Telescope Network (KMTNet). The 5σ detection limits for point sources in the BVRI bands are estimated to be ∼22.59, 22.60, 22.98, and 21.85 mag, respectively. Utilizing data from the Wide-field Infrared Survey Explorer, unobscured QSO candidates are selected among the optically pointlike sources using mid-infrared (MIR) and optical─MIR colors. To refine our selection further and eliminate any contamination not adequately removed by the color-based selection, we perform spectral energy distribution fitting with archival photometric data ranging from optical to MIR. As a result, we identify a total of 2383 unobscured QSO candidates in the SEP field. We also apply a similar method to the north ecliptic pole field using Pan-STARRS data and obtain a similar result of identifying 2427 candidates. The differential number count per area of our QSO candidates is in good agreement with those measured from spectroscopically confirmed ones in other fields. Finally, we compare the results with the literature and discuss how this work will impact future studies, especially upcoming space missions.

Keywords: Catalogs, Galaxies, Photometry, Quasars
AutoTAB: Automatic Tracking Algorithm for Bipolar Magnetic Regions. Bipolar magnetic regions (BMRs) provide crucial information about solar magnetism. They exhibit varying morphology and magnetic properties throughout their lifetime, and studying these properties can provide valuable insights into the workings of the solar dynamo. The majority of previous studies have counted every detected BMR as a new one and have not been able to study the full life history of each BMR. To address this issue, we have developed Automatic Tracking Algorithm for BMRs (AutoTAB) that tracks the BMRs for their entire lifetime or throughout their disk passage. AutoTAB uses the binary maps of detected BMRs and their overlapping criterion to automatically track the regions. In this first article of this project, we provide a detailed description of the working of the algorithm and evaluate its strengths and weaknesses by comparing it with existing algorithms. AutoTAB excels in tracking even for the small BMRs (with a flux of ~1020 Mx), and it has successfully tracked 9152 BMRs over the last two solar cycles (1996-2020), providing a comprehensive data set that depicts the evolution of various properties for each BMR. The tracked BMRs exhibit the well-known butterfly diagram and 11 yr solar cycle variation, except for small BMRs, which appear at all phases of the solar cycle and show a weak latitudinal dependence. Finally, we discuss the possibility of adapting our algorithm to other data sets and expanding the technique to track other solar features in the future.

Keywords: Solar cycle, Solar magnetic flux emergence, Sunspot groups, Sunspots, Bipolar sunspot groups, Solar active regions, Solar magnetic fields, Sunspot cycle
Toward Model Compression for a Deep Learning-Based Solar Flare Forecast on Satellites. Timely solar flare forecasting is challenged by the delay of transmitting vast amounts of data from the satellite to the ground. To avoid this delay, it is expected that forecasting models will be deployed on satellites. Thus, transmitting forecasting results instead of huge volumes of observation data would greatly save network bandwidth and reduce forecasting delay. However, deep-learning models have a huge number of parameters so they need large memory and strong computing power, which hinders their deployment on satellites with limited memory and computing resources. Therefore, there is a great need to compress forecasting models for efficient deployment on satellites. First, three typical compression methods, namely knowledge distillation, pruning, and quantization, are examined individually for compressing of solar flare forecasting models. And then, an assembled compression model is proposed for better compressing solar flare forecasting models. The experimental results demonstrate that the assembled compression model can compress a pretrained solar flare forecasting model to only 1.67% of its original size while maintaining forecasting accuracy.

Keywords: Solar flares, Neural networks
RelSIM: A Relativistic Semi-implicit Method for Particle-in-cell Simulations. We present a novel Relativistic Semi-Implicit Method (RelSIM) for particle-in-cell (PIC) simulations of astrophysical plasmas, implemented in a code framework ready for production runs. While explicit PIC methods have gained widespread recognition in the astrophysical community as a reliable tool to simulate plasma phenomena, implicit methods have been seldom explored. This is partly due to the lack of a reliable relativistic implicit PIC formulation that is applicable to state-of-the-art simulations. We propose the RelSIM to fill this gap: our new method is relatively simple, being free of nonlinear iterations and only requiring a global linear solve of the field equations. With a set of one- and two-dimensional tests, we demonstrate that the RelSIM produces more accurate results with much smaller numerical errors in the total energy than standard explicit PIC, in particular when characteristic plasma scales (skin depth and plasma frequency) are heavily underresolved on the numerical grid. By construction, the RelSIM also performs much better than the relativistic implicit-moment method, originally proposed for semi-implicit PIC simulations in the relativistic regime. Our results are promising to conduct large-scale (in terms of duration and domain size) PIC simulations of astrophysical plasmas, potentially reaching physical regimes inaccessible by standard explicit PIC codes.

Keywords: Computational methods, Special relativity, Plasma physics
A Systematic Study of Associations between Supernova Remnants and Molecular Clouds. We universally search for evidence of kinematic and spatial correlation of supernova remnant (SNR) and molecular cloud (MC) associations for nearly all SNRs in the coverage of the Milky Way Imaging Scroll Painting CO survey, i.e., 149 SNRs, 170 SNR candidates, and 18 pure pulsar wind nebulae in 1° &lt; l &lt; 230° and -5.°5 &lt; b &lt; 5.°5. Based on high-quality and unbiased 12CO/13CO/C18O (J = 1-0) survey data, we apply automatic algorithms to identify broad lines and spatial correlations for molecular gas in each SNR region. The 91% of SNR-MC associations detected previously are identified in this paper by CO line emission. Overall, there could be as high as 80% of SNRs associated with MCs. The proportion of SNRs associated with MCs is high within the Galactic longitude less than ~50°. Kinematic distances of all SNRs that are associated with MCs are estimated based on systemic velocities of associated MCs. The radii of SNRs associated with MCs follow a lognormal distribution, which peaks at ~8.1 pc. The progenitor initial mass of these SNRs follows a power-law distribution with an index of ~-2.3 that is consistent with the Salpeter index of -2.35. We find that SNR-MC associations are mainly distributed in a thin disk along the Galactic plane, while a small number are distributed in a thick disk. With the height of these SNRs from the Galactic plane below ~45 pc, the distribution of the average radius relative to the height of them is roughly flat, and the average radius increases with the height when above ~45 pc.

Keywords: Supernova remnants, Galaxy structure, Molecular clouds, Interstellar medium
Spectral Features of the Solar Transition Region and Chromospheric Lines at Flare Ribbons Observed with IRIS. We report on the spectral features of the Si IV λ1402.77, C II λ1334.53, and Mg II h or k lines, formed in the layers from the transition region to the chromosphere, in three two-ribbon flares (with X, M, and C class) observed with IRIS. All three lines show significant redshifts within the main flare ribbons, which mainly originate from the chromospheric condensation during the flares. The average redshift velocities of the Si IV line within the main ribbons are 56.6, 25.6, and 10.5 km s-1 for the X-, M-, and C-class flares, respectively, which show a decreasing tendency with the flare class. The C II and Mg II lines show a similar tendency but with smaller velocities compared to the Si IV line. Additionally, the Mg II h or k line shows a blue-wing enhancement in the three flares, in particular at the flare ribbon fronts, which is supposed to be caused by an upflow in the upper chromosphere due to the heating of the atmosphere. Moreover, the Mg II h or k line exhibits a central reversal at the flare ribbons but turns to pure emission shortly after 1-4 minutes. Correspondingly, the C II line also shows a central reversal but in a smaller region. However, for the Si IV line, the central reversal is only found in the X-class flare. As usual, the central reversal of these lines can be caused by the opacity effect. This implies that, in addition to the optically thick lines (C II and Mg II lines), the Si IV line can become optically thick in a strong flare, which is likely related to the nonthermal electron beam heating.

Keywords: Solar flares, Solar ultraviolet emission, Solar flare spectra, Solar transition region, Solar activity, Solar chromosphere
The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog. We present the the new Swift/UVOT+MaNGA (SwiM) catalog (SwiM_v4.1). SwiM_v4.1 is designed to study star formation and dust attenuation within nearby galaxies given the unique overlap of Swift/UVOT near-ultraviolet (NUV) imaging and MaNGA integral field optical spectroscopy. SwiM_v4.1 comprises 559 objects, ∼4 times more than the original SwiM catalog (SwiM_v3.1), spans the redshift range z ≈ 0.0002–0.1482, and provides a more diverse and rich sample. Approximately 5% of the final MaNGA sample is included in SwiM_v4.1, and 42% of the SwiM_v4.1 galaxies are cross-listed with other well-known catalogs. We present the same data as SwiM_v3.1, including UVOT images, Sloan Digital Sky Survey (SDSS) images, and MaNGA emission-line and spectral index maps with the same pixel size and angular resolution for each galaxy, and a file containing galaxy and observational properties. We designed SwiM_v4.1 to be unbiased, which resulted in some objects having low signal-to-noise ratios in their MaNGA or Swift data. We addressed this by providing a new file containing the fraction of science-ready pixels in each MaNGA emission-line map, and the integrated flux and inverse variance for all three NUV filters. The uniform angular resolution and sampling in SwiM_v4.1 will help answer a number of scientific questions, including constraining quenching and attenuation in the local Universe and studying the effects of black hole feedback. The galaxy maps, catalog files, and their associated data models are publicly released on the SDSS website (a description of the SwiM VAC is provided at https://www.sdss4.org/dr17/data_access/value-added-catalogs/?vac_id=swift-manga-value-added-catalog, and the data are stored on the SDSS Science Archive Server at https://data.sdss.org/sas/dr17/manga/swim/v4.1/).

Keywords: Catalogs, Astronomy data analysis, Star formation, Ultraviolet photometry, Spectroscopy, Sloan photometry, Galaxies
JEMS: A Deep Medium-band Imaging Survey in the Hubble Ultra Deep Field with JWST NIRCam and NIRISS. We present JWST Extragalactic Medium-band Survey, the first public medium-band imaging survey carried out using JWST/NIRCam and NIRISS. These observations use ~2 and ~4 μm medium-band filters (NIRCam F182M, F210M, F430M, F460M, F480M; and NIRISS F430M and F480M in parallel) over 15.6 arcmin2 in the Hubble Ultra Deep Field (UDF), thereby building on the deepest multiwavelength public data sets available anywhere on the sky. We describe our science goals, survey design, NIRCam and NIRISS image reduction methods, and describe our first data release of the science-ready mosaics, which reach 5σ point-source limits (AB mag) of ~29.3-29.4 in 2 μm filters and ~28.2-28.7 at 4 μm. Our chosen filters create a JWST imaging survey in the UDF that enables novel analysis of a range of spectral features potentially across the redshift range of 0.3 &lt; z &lt; 20, including Paschen-α, Hα+[N II], and [O III]+Hβ emission at high spatial resolution. We find that our JWST medium-band imaging efficiently identifies strong line emitters (medium-band colors &gt;1 mag) across redshifts 1.5 &lt; z &lt; 9.3, most prominently Hα+[N II] and [O III]+Hβ. We present our first data release including science-ready mosaics of each medium-band image available to the community, adding to the legacy value of past and future surveys in the UDF. This survey demonstrates the power of medium-band imaging with JWST, informing future extragalactic survey strategies using JWST observations.

Keywords: Extragalactic astronomy, High-redshift galaxies, Redshift surveys, Emission line galaxies
A Method to Measure Photometries of Moderately Saturated UVOT Sources. For bright transients such as gamma-ray bursts (GRBs), the Ultra-Violet/Optical Telescope (UVOT) operates under event mode at early phases, which records incident positions and the arrival time for each photon. The event file is able to be screened into many exposures to study the early light curve of GRBs with a high time resolution, including the rapid brightening of the UV/optical emission in particular. Such a goal, however, is hampered for some extremely bright GRBs by the saturation in UVOT event images. For moderately saturated UVOT sources, in this work we further develop the method proposed in Jin et al. to recover their photometries. The basic idea is to assume a stable point-spread function of UVOT images, for which the counts in the core region (i.e., an aperture of a radius of 5″) and the wing region (i.e., an annulus ranging from 15″-25″) should be constant, and the intrinsic flux can be reliably inferred with data in the ring. We demonstrate that in a given band, a tight correlation does hold among the background-removed count rates in the core and the wing. With the new method, the bright limit of measuring range for UVOT V and B bands increases by ~1.7 mag, while only by ~0.7 mag for the U band due to the lack of bright calibration sources. Systematic uncertainties are ~0.2 mag for the V, B, and U bands.

Keywords: Astronomical techniques, Photometry, Flux calibration
The Nuclear Reaction Network WinNet. We present the state-of-the-art single-zone nuclear reaction network WINNET, which is capable of calculating the nucleosynthetic yields of a large variety of astrophysical environments and conditions. This ranges from the calculation of the primordial nucleosynthesis, where only a few nuclei are considered, to the ejecta of neutron star mergers with several thousands of involved nuclei. Here we describe the underlying physics and implementation details of the reaction network. We additionally present the numerical implementation of two different integration methods, the implicit Euler method and Gears method, along with their advantages and disadvantages. We furthermore describe basic example cases of thermodynamic conditions that we provide together with the network and demonstrate the reliability of the code by using simple test cases. With this publication, WINNET will be publicly available and open source at GitHub and Zenodo.

Keywords: Computational methods, Nuclear astrophysics, Nucleosynthesis, Nuclear reaction cross sections
Novel Cosmological Joint Constraints in Multidimensional Observable Space with Redshift-free Inferences. Cosmology constraints serve as a crucial criterion in discriminating cosmological models. The traditional combined method to constrain the cosmological parameters designates the corresponding theoretical value and observational data as functions of redshift; however, sometimes the redshift cannot be measured directly, or the measurement error is large, or the definition of redshift is controversial. In this paper, we propose a novel joint method to constrain parameters that eliminates the redshift z and makes full use of the multiple observables $\left\{{{ \mathcal F }}_{1,\mathrm{obs}},{{ \mathcal F }}_{2,\mathrm{obs}},\cdots ,{{ \mathcal F }}_{M,\mathrm{obs}}\right\}$ spanning in M-dimensional joint observable space. Considering the generality of the mathematical form of the cosmological models and the guidance from low to high dimensions, we first validate our method in a 3D joint observable space spanned by H(z), f σ 8(z), and D  A (z), where the three coordinates can be considered redshift-free measurements of the same celestial body (or shared-redshift data-reconstructed model independently). Our results are consistent with the traditional combined method but with lower errors, yielding H 0 = 68.7 ± 0.1 km s-1 Mpc-1, Ω m0 = 0.289 ± 0.003, and σ 8 = 0.82 ± 0.01 and showing alleviated parametric degeneracies to some extent. In principle, our joint constraint method allows an extended form keeping the redshift information as an independent coordinate and can also be readily degraded to the form of a traditional combined method to constrain parameters.

Keywords: Cosmological parameters, Observational cosmology, Astronomy data analysis, Computational methods, Astrostatistics strategies
Unbiased CLEAN for STIX in Solar Orbiter. CLEAN is an iterative deconvolution method for radio and hard-X-ray solar imaging. In a specific step of its pipeline, CLEAN requires the convolution between an idealized version of the instrumental point-spread function (PSF), and a map collecting point sources located at positions from where most of the flaring radiation is emitted. This step has highly heuristic motivations and the shape of the idealized PSF, which depends on the user's choice, impacts the shape of the reconstruction. This study introduces a user-independent release of CLEAN for image reconstruction from observations recorded by the Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter. Specifically, we show here that this unbiased release of CLEAN outperforms the standard version of the algorithm, with reconstructions in line with the ones offered by other imaging methods developed in the STIX framework.

Keywords: X-ray telescopes, Interdisciplinary astronomy, Astronomy image processing, Solar x-ray flares
Prediction of the Transit Time of Coronal Mass Ejections with an Ensemble Machine-learning Method. Coronal mass ejections (CMEs), a kind of violent solar eruptive activity, can exert a significant impact on space weather. When arriving at the Earth, they interact with the geomagnetic field, which can boost the energy supply to the geomagnetic field and may further result in geomagnetic storms, thus having potentially catastrophic effects on human activities. Therefore, accurate forecasting of the transit time of CMEs from the Sun to the Earth is vital for mitigating the relevant losses brought by them. XGBoost, an ensemble model that has better performance in some other fields, is applied to the space weather forecast for the first time. During multiple tests with random data splits, the best mean absolute error (MAE) of ~5.72 hr was obtained, and in this test, 62% of the test CMEs had absolute arrival time error of less than 5.72 hr. The average MAE over all random tests was ~10 hr. It indicates that our method has a better predictive potential and baseline. Moreover, we introduce two effective feature importance ranking methods. One is the information gain method, a built-in method of ensemble models. The other is the permutation method. These two methods combine the learning process of the model and its performance to rank the CME features, respectively. Compared with the direct correlation analysis on the sample data set, they can help select the important features that closely match the model. These two methods can assist researchers to process large sample data sets, which often require feature selection in advance.

Keywords: Solar-terrestrial interactions, Solar coronal mass ejections