Sazuna/UAT_keywords huggingface dataset:
Detection of Pairwise Kinetic Sunyaev–Zel'dovich Effect with DESI Galaxy Groups and Planck in Fourier Space. We report a ∼5.2σ detection of the kinetic Sunyaev–Zel'dovich (kSZ) effect in Fourier space, by combining the DESI galaxy groups and the Planck data. We use the density-weighted pairwise kSZ power spectrum as the summary statistic, and the detailed procedure of its measurement is presented in this paper. Meanwhile, we analyze the redshift space group density power spectrum to constrain its bias parameters and photo-z uncertainties. These best-fitted parameters are substituted to a nonlinear kSZ model, and we fit the measured kSZ power spectrum with this model to constrain the group optical depth $\bar{\tau }$ . Selected by a varying lower mass threshold M th, the galaxy group catalogs with different median masses ( $\tilde{M}$ ) are constructed from the Data Release 9 data of the DESI Legacy Imaging Surveys. $\tilde{M}$ spans a wide range of ∼1013–1014 M ⊙/h and the heaviest $\tilde{M}\sim {10}^{14}\ {M}_{\odot }/h$ is larger than those of most other kSZ detections. When the aperture photometric filter radius θ AP is set to be 4.'2, the $\tilde{M}=1.75\times {10}^{13}\ {M}_{\odot }/h$ group sample at the median redshift $\tilde{z}=0.64$ has the highest kSZ detection signal-to-noise ratio = 5.2. By fitting $\bar{\tau }{\rm{s}}$ from various samples against their $\tilde{M}$ s, we obtain a linear $\mathrm{log}\bar{\tau }-\mathrm{log}\tilde{M}$ relation: $\mathrm{log}\bar{\tau }=\gamma (\mathrm{log}\tilde{M}-14)+\mathrm{log}\beta $ , in which γ = 0.55 ± 0.1. We also vary the aperture photometric filter radius and measure the $\bar{\tau }$ profiles of group samples, whose constraints on the baryon distribution within and around dark matter halos will be discussed in a companion paper.

Keywords: Cosmic microwave background radiation, Sunyaev-Zeldovich effect, Large-scale structure of the universe
CME Arrival Time Prediction via Fusion of Physical Parameters and Image Features. Coronal mass ejections (CMEs) are among the most intense phenomena in the Sun–Earth system, often resulting in space environment effects and consequential geomagnetic disturbances. Consequently, quickly and accurately predicting CME arrival time is crucial to minimize the harm caused to the near-Earth space environment. To forecast the arrival time of CMEs, researchers have developed diverse methods over the years. While existing approaches have yielded positive results, they do not fully use the available data, as they solely accept either CME physical parameters or CME images as inputs. To solve this issue, we propose a method that extracts features from both CME physical parameters and CME images and uses the attention mechanism to fuse the two types of data. First, we design a parameter feature extraction module that extracts features from CME physical parameters. After that, we adopt an effective convolutional neural network model as our image feature extraction module for extracting features from CME images. Finally, utilizing the attention mechanism, we present a feature fusion module designed to fuse the features extracted from both parameters and images of CMEs. Therefore, our model can fully utilize and combine physical parameters and image features, which allows it to capture significant and comprehensive information about CMEs.

Keywords: Convolutional neural networks, Solar coronal mass ejections
Physical Parameters of 11,100 Short-period ASAS-SN Eclipsing Contact Binaries. Starting from more than 11,200 short-period (less than 0.5 days) EW-type eclipsing binary candidates with the All-Sky Automated Survey for Supernovae V-band light curves, we use the Markov Chain Monte Carlo algorithm and neural networks to obtain the mass ratio (q), orbital inclination (incl), fill-out factor (f), and temperature ratio (T  s /T  p ). After crossmatching with the Gaia DR3 database, the final sample contains parameters of 2399 A-type and 8712 W-type contact binaries (CBs). We present the distributions of parameters of these 11,111 short-period CBs. The mass ratio (q) and fill-out factor (f) are found to obey log-normal distributions, and the remaining parameters obey normal distributions. There is a significant period–temperature correlation of these CBs. Additionally, the temperature ratio (T  s /T  p ) tends to increase as the orbital period decreases for W-type CBs. There is no significant correlation between them for A-type CBs. The mass ratio and fill-out factor (q‑f) diagram suggest there is no significant correlation between these two parameters. A clear correlation exists between the mass ratio and radius ratio. The radius ratio increases with the mass ratio. Moreover, the deep fill-out CBs tend to fall on the upper boundary of the q‑R  s /R  p  distribution, while the shallow fill-out CBs fall on the lower boundary.

Keywords: Eclipsing binary stars, Fundamental parameters of stars, Contact binary stars
The Impact of Effective Matter Mixing Based on Three-dimensional Hydrodynamical Models on the Molecule Formation in the Ejecta of SN 1987A. To investigate the impact of matter mixing on the formation of molecules in the ejecta of SN 1987A, time-dependent rate equations for chemical reactions are solved for one-zone and one-dimensional (1D) ejecta models of SN 1987A. The latter models are based on the 1D profiles obtained by angle-averaging of the three-dimensional (3D) hydrodynamical models, which effectively reflect the 3D matter mixing; the impact is demonstrated, for the first time, based on 3D hydrodynamical models. The distributions of initial seed atoms and radioactive 56Ni influenced by the mixing could affect the formation of molecules. By comparing the calculations for spherical cases and for several specified directions in the bipolar-like explosions in the 3D hydrodynamical models, the impact is discussed. The decay of 56Ni, practically 56Co at later phases, could heat the gas and delay the molecule formation. Additionally, Compton electrons produced by the decay could ionize atoms and molecules and could destroy molecules. Several chemical reactions involved with ions such as H+ and He+ could also destroy molecules. The mixing of 56Ni plays a nonnegligible role in both the formation and destruction of molecules through the processes above. The destructive processes of carbon monoxide and silicon monoxide due to the decay of 56Ni generally reduce the amounts. However, if the molecule formation is sufficiently delayed under a certain condition, the decay of 56Ni could locally increase the amounts through a sequence of reactions.

Keywords: Supernova remnants, Core-collapse supernovae, Astrochemistry
Light Bridges and Solar Active Region Evolution Processes. The formation mechanism of light bridges (LBs) is strongly related to the dynamic evolution of solar active regions (ARs). To study the relationship between LB formation and AR evolution phases, we employ 109 LB samples from 69 ARs in 2014 using observational data from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. LBs are well matched with the weak field lanes (WFLs), except those aligned on the polarity inversion line of δ sunspots. For penumbral intrusion (type-A) and umbral-dot emergence (type-C) LBs, the WFLs represent the splitting of magnetic flux systems. The sunspots tend to decay and split into several parts after type-A and type-C LBs are formed. For sunspot/umbra-merging (type-B) LBs, the declining WFLs are caused by collisions of flux systems. The sunspots merged and remained stable after type-B LBs formed. We conclude that type-B LBs are formed by collisions of flux systems, while type-A and type-C LBs are generated by splits. The time differences (δ T) between LBs appearing and ARs peaking have an average value of 1.06, ‑1.60, and 1.82 days for type-A, B, and C LBs, with the standard deviations of 3.27, 2.17, and 1.89, respectively. A positive value of δ T means that the LB appears after the AR peaks, whereas a negative δ T means it appears before the peak. Type-A LBs tend to form in the decaying phase or around the peak time. Type-B LBs are more likely to be formed in the developing phase. Type-C LBs mostly take shape in the decaying phase of ARs.

Keywords: Solar active regions, Sunspots
The EDGE-CALIFA Survey: An Extragalactic Database for Galaxy Evolution Studies. The EDGE-CALIFA survey provides spatially resolved optical integral-field unit and CO spectroscopy for 125 galaxies selected from the Calar Alto Legacy Integral Field Area Survey (CALIFA) Data Release 3 sample. The Extragalactic Database for Galaxy Evolution (EDGE) presents the spatially resolved products of the survey as pixel tables that reduce the oversampling in the original images and facilitate comparison of pixels from different images. By joining these pixel tables to lower-dimensional tables that provide radial profiles, integrated spectra, or global properties, it is possible to investigate the dependence of local conditions on large-scale properties. The database is freely accessible and has been utilized in several publications. We illustrate the use of this database and highlight the effects of CO upper limits on the inferred slopes of the local scaling relations between the stellar mass, star formation rate (SFR), and H2 surface densities. We find that the correlation between H2 and SFR surface density is the tightest among the three relations.

Keywords: Molecular gas, Astronomy databases, Spiral galaxies, Star formation, Galaxy evolution
A Star-based Method for the Precise Flux Calibration of the Chinese Space Station Telescope Slitless Spectroscopic Survey. The upcoming Chinese Space Station Telescope (CSST) slitless spectroscopic survey poses a challenge of flux calibration, which requires a large number of flux-standard stars. In this work, we design an uncertainty-aware residual attention network, the UaRA-net, to derive the CSST spectral energy distributions (SEDs) with a resolution of R = 200 over the wavelength range of 2500─10000 Å using LAMOST normalized spectra with a resolution of R = 2000 over the wavelength range of 4000─7000 Å. With the special structure and training strategy, the proposed model provides accurate predictions not only of SEDs, but also of their corresponding errors. The precision of the predicted SEDs depends on the effective temperature (T eff), wavelength, and the LAMOST spectral signal-to-noise ratios (S/Ns), particularly in the GU band. For stars with T eff = 6000 K, the typical SED precisions in the GU band are 4.2%, 2.1%, and 1.5% at S/N values of 20, 40, and 80, respectively. As T eff increases to 8000 K, the precision increases to 1.2%, 0.6%, and 0.5%, respectively. The precision is higher at redder wavelengths. In the GI band, the typical SED precisions for stars with T eff = 6000 K increase to 0.3%, 0.1%, and 0.1% at S/N values of 20, 40, and 80, respectively. We further verify our model using empirical MILES spectra and find a good performance. The proposed method will open up new possibilities for the optimal use of slitless spectra of the CSST and other surveys.

Keywords: Fundamental parameters of stars, Spectroscopy, Flux calibration
The ALCHEMI Atlas: Principal Component Analysis Reveals Starburst Evolution in NGC 253. Molecular lines are powerful diagnostics of the physical and chemical properties of the interstellar medium (ISM). These ISM properties, which affect future star formation, are expected to differ in starburst galaxies from those of more quiescent galaxies. We investigate the ISM properties in the central molecular zone of the nearby starburst galaxy NGC 253 using the ultrawide millimeter spectral scan survey from the Atacama Large Millimeter/submillimeter Array Large Program ALCHEMI. We present an atlas of velocity-integrated images at a 1.″6 resolution of 148 unblended transitions from 44 species, including the first extragalactic detection of HCNH+ and the first interferometric images of C3H+, NO, and HCS+. We conduct a principal component analysis (PCA) on these images to extract correlated chemical species and to identify key groups of diagnostic transitions. To the best of our knowledge, our data set is currently the largest astronomical set of molecular lines to which PCA has been applied. The PCA can categorize transitions coming from different physical components in NGC 253 such as (i) young starburst tracers characterized by high-excitation transitions of HC3N and complex organic molecules versus tracers of on-going star formation (radio recombination lines) and high-excitation transitions of CCH and CN tracing photodissociation regions, (ii) tracers of cloud-collision-induced shocks (low-excitation transitions of CH3OH, HNCO, HOCO+, and OCS) versus shocks from star formation-induced outflows (high-excitation transitions of SiO), as well as (iii) outflows showing emission from HOC+, CCH, H3O+, CO isotopologues, HCN, HCO+, CS, and CN. Our findings show these intensities vary with galactic dynamics, star formation activities, and stellar feedback.

Keywords: Interstellar molecules, Starburst galaxies, Interstellar medium, Astrochemistry
Identifying Flare-indicative Photospheric Magnetic Field Parameters from Multivariate Time-series Data of Solar Active Regions. Photospheric magnetic field parameters are frequently used to analyze and predict solar events. Observation of these parameters over time, i.e., representing solar events by multivariate time-series (MVTS) data, can determine relationships between magnetic field states in active regions and extreme solar events, e.g., solar flares. We can improve our understanding of these events by selecting the most relevant parameters that give the highest predictive performance. In this study, we propose a two-step incremental feature selection method for MVTS data using a deep-learning model based on long short-term memory (LSTM) networks. First, each MVTS feature (magnetic field parameter) is evaluated individually by a univariate sequence classifier utilizing an LSTM network. Then, the top performing features are combined to produce input for an LSTM-based multivariate sequence classifier. Finally, we tested the discrimination ability of the selected features by training downstream classifiers, e.g., Minimally Random Convolutional Kernel Transform and support vector machine. We performed our experiments using a benchmark data set for flare prediction known as Space Weather Analytics for Solar Flares. We compared our proposed method with three other baseline feature selection methods and demonstrated that our method selects more discriminatory features compared to other methods. Due to the imbalanced nature of the data, primarily caused by the rarity of minority flare classes (e.g., the X and M classes), we used the true skill statistic as the evaluation metric. Finally, we reported the set of photospheric magnetic field parameters that give the highest discrimination performance in predicting flare classes.

Keywords: Solar active region magnetic fields, Solar flares, Space weather, Multivariate analysis, Solar physics, Time series analysis
Toward Precision Cosmology with Improved Planetary Nebula Luminosity Function Distances Using VLT-MUSE. II. A Test Sample from Archival Data. Thanks to the MUSE integral field spectrograph on board the Very Large Telescope (VLT), extragalactic distance measurements with the [O III] λ5007 planetary nebula luminosity function (PNLF) are now possible out to ∼40 Mpc. Here we analyze the VLT/MUSE data for 20 galaxies from the ESO public archive to identify the systems' planetary nebulae (PNe) and determine their PNLF distances. Three of the galaxies do not contain enough PNe for a robust measure of the PNLF, and the results for one other system are compromised of the galaxy's internal extinction. However, we obtain robust PNLF distances for the remaining 16 galaxies, two of which are isolated and beyond 30 Mpc in a relatively unperturbed Hubble flow. From these data, we derive a Hubble constant of 74.2 ± 7.2 (stat) ±3.7 (sys) km s−1 Mpc−1, a value that is very similar to that found from other quality indicators (e.g., Cepheids, the tip of the red giant branch, and surface brightness fluctuations). At present, the uncertainty is dominated by the small number of suitable galaxies in the ESO archive and their less-than-ideal observing conditions and calibrations. Based on our experience with these systems, we identify the observational requirements necessary for the PNLF to yield a competitive value for H 0 that is independent of the Type Ia supernova distance scale.

Keywords: Hubble constant, Planetary nebulae, Galaxies, Distance indicators
S-PLUS: Photometric Recalibration with the Stellar Color Regression Method and an Improved Gaia XP Synthetic Photometry Method. We present a comprehensive recalibration of narrowband/medium-band and broadband photometry from the Southern Photometric Local Universe Survey (S-PLUS) by leveraging two approaches: an improved Gaia XP synthetic photometry (XPSP) method with corrected Gaia XP spectra, and the stellar color regression (SCR) method with corrected Gaia Early Data Release 3 photometric data and spectroscopic data from LAMOST Data Release 7. Through the use of millions of stars as standards per band, we demonstrate the existence of position-dependent systematic errors, up to 23 mmag for the main survey region, in the S-PLUS iDR4 photometric data. A comparison between the XPSP and SCR methods reveals minor differences in zero-point offsets, typically within the range of 1–6 mmag, indicating the accuracy of the recalibration, and a twofold to threefold improvement in the zero-point precision. During this process, we also verify and correct for systematic errors related to CCD position. The corrected S-PLUS iDR4 photometric data will provide a solid data foundation for conducting scientific research that relies on high-precision calibration. Our results underscore the power of the XPSP method in combination with the SCR method, showcasing their effectiveness in enhancing calibration precision for wide-field surveys when combined with Gaia photometry and XP spectra, to be applied for other S-PLUS subsurveys.

Keywords: Stellar photometry, Calibration, Astronomy data analysis
A Closer Look at Small-scale Magnetic Flux Ropes in the Solar Wind at 1 au: Results from Improved Automated Detection. Small-scale interplanetary magnetic flux ropes (SMFRs) are similar to ICMEs in magnetic structure, but are smaller and do not exhibit coronal mass ejection plasma signatures. We present a computationally efficient and GPU-powered version of the single-spacecraft automated SMFR detection algorithm based on the Grad–Shafranov (GS) technique. Our algorithm can process higher resolution data, eliminates selection bias caused by a fixed threshold, has improved detection criteria demonstrated to have better results on an MHD simulation, and recovers full 2.5D cross sections using GS reconstruction. We used it to detect 512,152 SMFRs from 27 yr (1996–2022) of 3 s cadence Wind measurements. Our novel findings are the following: (1) the SMFR filling factor (∼ 35%) is independent of solar activity, distance to the heliospheric current sheet, and solar wind plasma type, although the minority of SMFRs with diameters greater than ∼0.01 au have a strong solar activity dependence; (2) SMFR diameters follow a log-normal distribution that peaks below the resolved range (≳104 km), although the filling factor is dominated by SMFRs between 105 and 106 km; (3) most SMFRs at 1 au have strong field-aligned flows like those from Parker Solar Probe measurements; (4) the radial density (generally ∼1 detected per 106 km) and axial magnetic flux density of SMFRs are higher in faster solar wind types, suggesting that they are more compressed. Implications for the origin of SMFRs and switchbacks are briefly discussed. The new algorithm and SMFR dataset are made freely available.

Keywords: Interplanetary turbulence, Solar wind, Interplanetary physics, Transient detection
Science Opportunities for IMAP-Lo Observations of Interstellar Neutral Hydrogen and Deuterium during a Maximum of Solar Activity. Direct-sampling observations of interstellar neutral gas, including hydrogen and deuterium, have been performed for more than one cycle of solar activity by IBEX. The IBEX viewing is restricted to directions perpendicular to the spacecraft–Sun line, which limits the observations to several months each year. This restriction is removed in the forthcoming mission called Interstellar Mapping and Acceleration Probe. The IMAP-Lo instrument will have the capability of adjusting the angle of its boresight with the spacecraft rotation axis. We continue a series of studies of the resulting science opportunities. We adopt the schedule of adjusting the boresight angle suggested by Kubiak et al. and focus on interstellar hydrogen and deuterium during solar maximum. Based on an extensive set of simulations, we identify the times during the calendar year and the elongation angles of the boresight needed to measure the abundance of D/H at the termination shock and to unambiguously observe interstellar H without a contribution from interstellar He. Furthermore, IMAP-Lo will be able to resolve the primary and secondary populations, in particular, to view the secondary population with little contribution from the primary. We show that the expected signal is sensitive to details of radiation pressure, particularly its dependence on the radial speed of the atoms, and to details of the behavior of the distribution function of the primary and secondary populations at the heliopause. Therefore, IMAP-Lo will be able to provide the observations needed to address compelling questions in heliospheric physics and even in general astrophysics.

Keywords: Interstellar atomic gas, Heliosphere, Neutral hydrogen clouds, Interstellar magnetic fields, Interstellar medium, Heliosheath, Magnetic fields
High-dimensional Statistical Analysis and Its Application to an ALMA Map of NGC 253. In astronomy, if we denote the dimension of data as d and the number of samples as n, we often find a case with n ≪ d. Traditionally, such a situation is regarded as ill-posed, and there was no choice but to discard most of the information in data dimensions to let d &lt; n. The data with n ≪ d is referred to as the high-dimensional low sample size (HDLSS). To deal with HDLSS problems, a method called high-dimensional statistics has rapidly developed in the last decade. In this work, we first introduce high-dimensional statistical analysis to the astronomical community. We apply two representative methods in the high-dimensional statistical analysis methods, noise-reduction principal component analysis (NRPCA) and automatic sparse principal component analysis (A-SPCA), to a spectroscopic map of a nearby archetype starburst galaxy NGC 253 taken by the Atacama Large Millimeter/submillimeter Array (ALMA). The ALMA map is an example of a typical HDLSS data set. First, we analyzed the original data, including the Doppler shift due to the systemic rotation. High-dimensional PCA can precisely describe the spatial structure of the rotation. We then applied to the Doppler-shift corrected data to analyze more subtle spectral features. NRPCA and R-SPCA were able to quantify the very complicated characteristics of the ALMA spectra. Particularly, we were able to extract information on the global outflow from the center of NGC 253. This method can also be applied not only to spectroscopic survey data, but also to any type of data with a small sample size and large dimension.

Keywords: Starburst galaxies, Molecular gas, Millimeter astronomy, Astrostatistics techniques, Molecular spectroscopy, Submillimeter astronomy, Radio astronomy